Importance of test code quality in continuous testing of financial applications

The global pandemic (2020-2021) had led to unanticipated issues such as economic crisis and credit risk. The upcoming years looked uncertain while facing a critical time. To protect from the economic fallout, the leading business entrepreneurs focused on finding out possible solutions that they thought would help them in stabilizing business continuity and serving their customers better.

One of the Gartner’s Business Continuity Survey reveals that as less as 12 per cent of organizations were prepared to combat the effect of a deadly catastrophe like coronavirus. Amidst the threat of spreading COVID-19, the leading financial institutions considered evaluating their business continuity plans and pandemic planning initiatives to ensure they put safety and efficiency first.

Banking and financial institutions considered agile methodology to adapt to the changing global scenario. The unforeseen event urged the BFSI sectors to reflect on their fundamental practices and how prepared were they for the future. The impact of the pandemic was so widespread that banks faced a weak investment return leading to future credit risks and economic uncertainties. Reportedly, the European banks collectively have experienced an estimated credit loss of an average of €700m in Q1 2020. Meanwhile, in the US three popular banks informed that they noticed a significant credit loss of $25b in Q2 2020.

Current Trend and Opportunities

To prevent the pitfall and evolve from this economic crisis, banks seized available opportunities and prepared their next business module. This catastrophe has urged banks to re-evaluate and analyze their core and non-core assets. Under this scenario, 60% of the banks considered the divestment option, a plan to divest in the next 12 months.

The possibility is likely to play a massive role in understanding the type of organizations banks would like to connect with in the future and how conveniently they can transform their existing process. A growing interest in digitalization is driving banks to adopt digital banking products and solutions to cater to customer requirements. They are taking steps to boost their digital transformation plans.

With a growing threat during a pandemic and different phases of the lockdown being imposed everywhere, financial institutions had adopted remote working policies. It provided an opportunity for the business leaders to reconsider working remotely, operating in the long-term, and consider the monetary impact this approach could have.

This situation enabled many banks to understand their resilience and capabilities. They also reconsidered their cost transformation programs to move in tune with the new challenges of this crisis. The future from here on looks promising and inspiring.

From the online purchase of grocery items to electronic goods, banking and financial institutions, companies introduced promotions, special services, and reward points to re-establish their position in the market. The customers’ purchase behavior was requirement-based, as a product was bought and sold based on bare necessity.

Customers were driven more by emotion during the crisis. Hence, for organizations, brand messaging, tone and purpose became extremely important while connecting with their customers at an emotional level. It helped in establishing customer brand loyalty. Customer purchase behavior depends on four principles, as stated below:

  • As customers remain indecisive, empathy and commitment become two ways to win their trust. During the pandemic, consumers reacted positively to inspiring content that highlighted social, financial, and other real-life aspects.
  • Brands should keep informing their customers about the crisis, how to protect themselves and change in the situation. Customers are likely to trust brands that provide reliable and accurate information about the current situation.
  • Engaging and connecting your customers by facilitating and extending social support are assured ways of improving brand loyalty. Social engagement with customer support and responding instantly during this pandemic have helped build brand loyalty.
  • Offering new schemes, promotions, and offers helps your brands to evolve through endorsement. These efforts have an impact on your customers.

Digital Transformation

Digital banking solutions, which have been brewing for a long time, have accelerated during this unprecedented time. This pandemic situation profoundly changed the behavior of retail and corporate banking clients and facilitated the use of digital banking.

A recent survey done by Ernst and Young, reveals that 62% of consumers said they would use less cash in the future, while 59% will opt for contactless payments. The use of digital services and products propelled more expansion when some of the bank branches were closed, and in response, banks accelerated digital and technology transformation programs.

The small and mid-size companies started adopting digital solutions faster than anticipated. There was an increase of new digital accounts by 2.4 times in the first quarter of 2020 as compared to the first quarter of 2019, and a 49% rise in SME digital loan applications in 2020 as compared to 30% in 2019, in one of the Singapore-based banks.

The concurrent situation has led to massive economic uncertainty, and there is a requirement for the bank to endure this sudden disruption. With a low margin, banks opted for digital tools and focused on sustainable digital enablement that helped them save cost and time. Their motto was, “Grow your business with digital innovations to live up to your customer’s expectations”.

When assessing customers’ requirements, it was observed that a combination of UI and UX of a digital platform contributed to customer satisfaction and experience. Since banking and financial institutions were turning their services online, they needed a platform that could improve the appeal and undisrupted performance.

The following instance supports the claim of how banking is relying on digital and online platforms. In April 2020, Lloyds Banking Group decided to provide a tablet to their 2,000 customers over the age of 70. The objective was to provide training and support to help them access online banking. As banks are now adopting the best digital practices and customer-centric solutions, they form a well-connected digital ecosystem and unique value propositions for their clients. The whole objective shifts to serving their customers better through an outstanding and uninterrupted online banking experience.

Banking has been evolving even before the pandemic swept the entire world. Based on customer requirements and expectations, banks are compelled to leverage digital channels, accounts payments or transfers and online wallets. To avoid the risk of spreading the infection, consumers opted for cashless payments during this pandemic situation. Consumers who did not consider online payment and transactions as options were encouraged to migrate to a digital platform. Since many consumers were not fully familiar with the digital platform, banks have taken it upon them to educate their customers for an outstanding experience.

As the cashless transaction became the new reality of the ongoing situation, banking and financial sectors had to speed up their digital innovation process in response to customer needs by leveraging cross-channel, customer-centric metrics and tracking the success of digital banking. To re-align sales, reduce operational costs, and offer excellent customer experience, data and analytics, AI and automation played a significant role.

A Cost-effective Managed Services

A well-panned managed service can offer operational flexibility and ensure uninterrupted business-continuity plans against unanticipated challenges during the global crisis. With the pace at which the market situation changed, the banks and financial institutions could not afford to hold back the digital revolution for long. Organizations realized that if they suspend their online operational transformation, they will suffer business loss. They understood the competitive edge the change would bring and hence started managing the costs more carefully.

A well-managed service allowed the banks to reduce operating expenses for the long term, and the sudden outburst gave a reason to the bank to adopt managed services. Managed services helped banks to formulate a strong business continuity plan. It is during the time of crisis that managed services helped the banks to maintain the system stability.

The financial instability during this challenging time urged banks to develop strategies to encourage their customer to move online and prove their operational flexibility. With this rapid digital growth, banks were compelled to invest in security, virtual collaboration and cloud infrastructure, analytics, artificial intelligence, and automation. The banks and financial institutions were quick to adopt digital transformation. And the one who did could recover from the economic setback and establish a strong foothold.

Since banking operations largely depend on customer behavior and satisfaction, the banks must face and overcome the challenges of maintaining their standard of customer services, while mitigating operational hurdles.

Current Contact Centers

Digital and mobile banking witnessed a sharp rise during this critical situation, along with the voice channel to serve consumers well. Despite the fully functional digital operation, a few of the banks were operating from branches in different locations. It proved that even if we were relying on a digital platform, we still needed human interventions. We realized the importance of both during a crisis like the current one. AI-driven technology replaced this to achieve the objective. AI could smartly detect the call intention and provide real-time data to the users. This technology helped in reducing call time, and improved efficiency, and customer satisfaction.

Rise of Open Banking Solutions

The situation gave rise to open banking solutions as there has been an 832% increase in open banking during the global lockdown. Banks took more interest in the open banking payment initiative to gain more understanding of their financial situation. Consequently, more and more banks used the opportunity and invested in open banking solutions. The European financial institutions witnessed a steady increase, and globally the organizations were eager to have a different perspective. They did not mind sharing the information on an open platform. A recent report revealed that there was a rise of 20-29% of investments in open banking services for two-thirds of the respondents.

Partnering with FinTech

Banks were simultaneously looking to speed up the digital innovations during the prevailing global situation when the economies across the globe were slowing down. Also, during this pandemic situation, many venture capitalists were restricted from investing in FinTechs. Hence, partnering with FinTech in this situation proved to be economically and mutually beneficial.

Many governments slowly eased rules and regulations in FinTech companies to encourage the growth of innovations and balance out economic disruption. It came as a relief against the long-standing rules, which were once imposed on them.

The current situation provided opportunities for FinTechs to strike a balance between digital transformation while creating a secure financial backbone. As banks and FinTechs together collaborated, it helped them to bridge the funding gap.

As banks were in the earlier stages of digital transformation, partnering with FinTech companies proved to be helpful in terms of improving technological expertise. Banks in collaboration with FinTechs could develop platforms for financial inclusion, analyze transactions and other data for deep insights, capability development and deploy automation for compliance.

Mortgage Refinancing & Payment Deferral

The crisis raised lots of dependability on banks as to how they are addressing their customer’s issues. Due to low-interest rates, there was a steady rise in mortgage refinancing in April and May 2020, resulting in high loan volumes for lenders. As the whole world was suffering because of layoffs, and pay cuts, the homeowners found it to be challenging to pay their instalments on time. This catastrophe has left many customers asking for mortgage deferrals.

Many banks waived fees, increased credit card limits, and granted mortgage payment holidays in response to customers’ inability to keep up the monthly mortgage payments. They made a few adjustments with the short-term and long-term financial changes. Banks provided tailored solutions based on the customer’s requirements by leveraging machine learning, AI and analytics and driving improved engagement.

Managing System Performance and Unexpected Risks through QA

The customers looked for additional support during this crisis in terms of credit facilities from the banks globally. Banks had to be prepared for the upcoming risks and take measures to keep their business and customers protected from the financial debacle, as default and bad loan cases were expected to rise in numbers.

Banks had to build a powerful fraud and risk management and strengthen their portfolio using their analytical capabilities. It helped them to generate useful insights, improve the operational process, and decide quickly on process-related matters. The impact of the global setback urged the banks to focus, assess and review their stress testing models. Since banks actively took steps towards digital transformation, they had to ensure that their systems had seamless performance, system integration and customer acceptance of their digital platform.

Efficient software and algorithm were needed to detect fraud and reevaluate the risk modelling. It allowed banks to calculate pricing, and evaluate and measure the credit risk of borrowers. Banks needed real-time data and an advanced risk calculator, as the economic impact during this time turned a large amount of data unreliable. Banks had to develop advanced analytical capabilities to filter data accurately and spot anomalies quickly.

Since the outbreak of the global pandemic, there has been a significant rise in criminal activities, increasing the threat of money laundering. Banks will also have to strengthen their KYC and Anti-money Laundering (AML) programs. It helped the banks and financial sectors to manage risks and keep pace with changing regulatory scenarios.  

Journey Ahead from Here

The rising concern and uncertainty of this pandemic situation have made the global banks sort out multiple ways to address their customer requirements. The customers require extensive support and flexible services, and interaction. As the situation demanded high technical upliftment, banks were likely to adopt the followings that allowed and helped them to meet their customer expectations. 

  • Accelerated digitalization efforts
  • Cloud migration
  • Intelligent workflow management
  • Partnerships with the BFS sector and FinTechs
  • Embedding security and governance across operations
  • Advanced risk modelling

The current condition posed multiple challenges and compelled banks and financial institutions to invest more in the digital future. They are now improving their operations by leveraging innovative technologies and continuing to inspire other industries that have not reached digital excellence. The financial sector is on the right track to reap the benefits and enjoy the success of its cost transformation programs for the future.

Ensure Credit Quality in Digital Lending Applications

The digital lending market is exploding with growing apps and fintechs. As per a report IIFL FinTech, the digital lending market is expected to grow to a whopping USD 515 billion by 2030. Lending services are no longer about hard-copy documentation. The lending process has moved far beyond becoming completely digital. From recording queries and customer financial details to credit underwriting and loan disbursal, the process is increasingly becoming online.

The online lending process saves time and effort for customers from physically visiting the bank branches to either sign the documents or verify their identity. Digital lending platforms have reduced foot traffic in branch offices, increasing the dependencies on digital applications, which leads to frequent updates and changes in digital applications. These regular updates require continuous monitoring to create a secure, scalable, and efficient digital lending application.

Why gradually industry shifted towards digital lending from traditional processes?

The traditional lending process was inefficient, filled with errors, and time-consuming. It involved managing hard copies of required documentation, frequent bank visits, and prolonged verification of borrowers’ loan profile, credibility and repayment history. The issues were further amplified if the borrower did not meet the eligibility criteria and underwriting based on their past credit history. Securing loans from the banks remained a matter of speculation for the borrowers. This is where digital lending came into the picture and steadily captured the market.

The current scenario of digital lending

Factors like unlimited access to the internet at an affordable price, smartphones penetrating the market, and applications and software available for loan applications facilitate digital lending. Digital lending in India is expected to touch $350 billion by the end of 2023.  

A report states 36 RBI Approved Loan Apps. These names are independent of banks that already offer lending services at a reasonable interest rate. The lending app comes with instant approval and disbursal within 24 hours, which is extremely convenient for borrowers seeking small and medium-sized loan amounts in case of emergency.

But how the lengthy traditional lending processes become so convenient?

The bank lending apps can access the customer data stored in their in-house server and system. However, the fintech organizations procure this information from various sources like banks and third parties through the Application Programming Interface or APIs.

The fintech applications have to obtain the data from diverse sources. To maintain the turn-around-time and live up to their service reputation, they must send the request data access from multiple sources like credit bureaus for borrower past credit history, link to the bank server for bank account verification and auto debit facility, and more to access borrowers’ details.

The lending process through these applications can be extremely critical if the essential quality checks are not done. There can be rising security concerns, performance & functionality errors, delayed access to customer credit history and a cluttered user interface. Let’s look at the complications or bottlenecks in digital lending applications and what problem it may lead to if remains unresolved.

  1. Security and privacy – Customer data is the most sensitive. Digital lending applications procure customer data directly from the bank server and from a third-party vendor. These transactions can be highly sensitive, and if attacked by malicious malware, they can lead to terrible issues if unresolved. It is crucial to ensure robust security measures and compliance with data privacy regulations.

  2. Data protection from risk and fraud – Understanding the current trend of digital lending platforms protecting customer data from risk and fraud is essential but challenging too. Protecting the sensitive credit details of customers are a complex process if the fintechs do not have adequate mechanism to analyze user behaviour and identify the potential risk.

  3. Scalability – As the number of users and loan applications grows, the application needs to scale efficiently to handle increased traffic and processing demands. Inadequate scalability can lead to slow response times and system crashes during peak usage times.

  4. Migration from Legacy systems – As per a report, over two-thirds of organizations are still using and relying on legacy systems. Legacy systems are non-adaptable and inflexible. They are not compatible with digital lending platforms. Integrating the digital lending platform with the legacy platform can be challenging and may require extensive effort and expert resources. And yet enterprises cannot abandon the legacy platform as they have been running for more than 30 years with an estimated over £2 trillion transactions every day.

  5. Integration with the main banking server – This brings us to the next bottleneck. It is a significant effort to integrate the digital lending platform with banks’ legacy platform. Moreover, the legacy systems are not equipped to manage the integration with the digital platform. They also cannot offer innovative offerings like banking-as-a-service (BaaS) as it does not support application programming interfaces (API) integration with third-party services. However, since the upgradation of these legacy systems is time-consuming, banks resist the changes leading it as a bottleneck in the digital transformation process.

  6. Regulatory compliance – Digital lending applications must be compliant with financial regulations. Frequent regulatory changes also demand financial institutions keep up with the changes and update their applications. With frequent changes in features and functionalities, keeping up with regulatory compliance can be complex.

  7. Data transactions – The digital lending platform pulls large amounts of user data from the main banking systems. It requires robust infrastructure and seamless data integration & management systems to eliminate bottlenecks and ensure smooth operations.

  8. Customer satisfaction – Customers require a fast loan approval and disbursement cycle. Hence, to ensure optimum customer satisfaction, lending institutions validate application workflow that expedites the decision-making process, minimizes delay and conforms to user experience. Also, recurring functionality, performance, and security errors can cause potential application issues that damage the brand’s reputation.

  9. Verification of data quality – Digital lending does not pull irrelevant data. They pull only required customer information. Banking systems may store multiple data but not all data are accurate and useful for digital lending platforms. Choosing the relevant data helps fintechs arrive at an informed essential lending decision. However, verifying the data quality can be complex due to the unavailability of relevant and accurate data.  

  10. Mobile responsiveness – The current trend in digital applications demands high mobile responsiveness. The process can be extremely complex in the absence of a mobile responsiveness platform. Hence, the digital lending platform requires extensive validation to ensure that the platform continues to deliver high-quality services and offer optimized user experience.

Digital lending apps became prominent during the pandemic, and customers are embracing it, because of fast approval and disbursal. But the credit quality remains under the scanner.

How reliable is the credit quality in digital lending applications?

A long-standing business lending process is more effective with manual review, cross-verification, and years of root-cause analysis of defaults and assessments compared to digital platforms. The former could be time-consuming, but it helps to achieve the desired risk outcome. It also helps the banks achieve low default rates.

However, the industry cannot avoid the trend of digital adoption. To adapt to the model, financial institutions have found a middle ground to amalgamate the digital model with the accuracy of data-driven model-based decision-making. As digital lending continues to improve, risk managers can take a calculated approach towards automation.

How can we improve the credit quality of digital lending apps?

Banks are testing the automated digital engine based on data-driven assessments and a structured credit framework to assess credit quality based on predictive default risk. As a result, the decision will be more consistent, accurate, fast and cost-effective.

Is quality assurance and testing essential to ensure the credit quality of digital lending apps? Can quality assurance and testing ensure the credit quality of digital lending apps?

Digital lending apps or fintechs pull data from the banks’ main servers. They also coordinate with TSPs like credit bureaus, collections and more. They handle critical transactions 24/7*365 days and customer details, making QA strategy an essential step. QA and testing confirm that the application and platforms are free from defects and errors before production and market launch. It also must offer outstanding client experience with high-quality mobile apps. Quality assurance and testing helps lenders to improve the credit quality of digital lending application.

Some factors are important here to ensure the credit quality of digital lending applications. API functionality and performance, digital application features and timely response of digital apps.

Though digital lending applications require end-to-end test coverage, including functional testing, reliability testing, validation testing, load testing, UI Testing, Security Testing, Penetration Testing and more, there is one more crucial aspect when it comes to validating digital lending applications.

Our understanding from the projects we have handled is that these applications have a few restrictions and limitations. We have also observed a reliability on API functionality and performance if digital lending platforms have to function without any technical glitches.

As high as the dependency on API, the risk with digital lending keeps increasing. API testing is conducted on Encrypted and Unencrypted APIs, multiple encryption levels and data formats, API tunnelling, instability/availability, handling many security protocols, and more.

We offer manual and automated API testing, validating requests and responses at various API layers. We also validate the accessibility of the API level and check the functionality, reliability, performance, and security of the programming interfaces.

Our intuitive robotic test automation solution, Tenjin, is a functional test automation solution. It is a seamless & effective test automation tool for BA and functional testers. Tenjin Test Automation solution is REST and SOAP API ready. Its features like auto-learn, auto-discover and auto-execute help to learn application interface automatically

We support financial institutions with end-to-end testing of their digital lending platforms.

Both banks and fintechs have brought their lending processes to digital platforms for quick approval and disbursal. It allows the borrower to avail loans in case of an emergency. But like all other platforms, digital lending apps require thorough testing to ensure higher customer satisfaction with lower TAT and improved credit quality. This is where Yethi’s domain expertise and industry come into the picture. We have delivered over 500+ projects for over 130 clients across 30+ countries in various LOBs in banks and financial institutions.

10 Critical Steps in Testing the Business and System Upgrade Projects of Banks

Banking businesses thrive on market relevance and ever-evolving customer preferences. It matters a lot for banks to ensure the highest level of customer satisfaction. They can never compromise business quality as it may harm their reputation, incur a monetary loss, and take away their customer reliability. Compromising the quality of their services and systems may lead them to pay a significant penalty. Hence, testing is crucial in the event of new system installation or upgrades in banks.

Banks ensure to reform their services based on current trends and technologies as customer demands and preferences keep evolving. To stay relevant to their customers and stay ahead of their competitors, banks incorporate the latest technologies and improve their services, eventually improving the business metrics.  Hence, banks must validate every business and system upgrade to retain customers and offer them a seamless experience.

Testing is an integral part of the banking systems which demands a more strategic approach than a random one. It involves a great amount of strategy and planning to ensure that the projects go live successfully without any glitches. As so it may look simple on the surface, testing the business and system upgrades are usually a critical process. There are many steps that an enterprise must consider during the testing of the upgrade projects. Here we have discussed 10 critical steps in testing that the enterprise business must not overlook if their end goal is to serve their customers well and succeed.

Steps in testing the banking business and system upgrades:

Before we consider the step for the execution of successful testing of the business and system, it is important to define the goals and objectives of the testing projects. Here are key considerations to make while determining testing projects of banks once you have determined the objectives of your testing project. 

    1. Requirement gathering based on the project scope.

The testing projects of the business and system upgrade begin with an understanding of the project requirements. The scope of testing, the banking modules, menus, submenus and more are the essential components of any project.

Understanding the project requirements is a complex task as banking applications are quite diverse with multiple features and functionalities. The QA team must have a thorough understanding & awareness of banking modules, functionalities, various layers of application integration and more. The process can be complicated and the project scope may remain unidentified if the teams don’t gather adequate project requirements.

Is it an elaborate exercise to gather project requisites?

Requirement gathering is the entry phase of the software testing project. As a part of the project strategy, it is essential to gather the project requirements and understand the scope of the projects.

By gathering project requirements and understanding the project scope, it is easy to strategize, define, and measure the testing project outcome. It also helps in deploying manpower and determining the time and cost of the project. The team understands what is to be tested; they also understand if they are missing out on any important components, or any potential risk involved so that they can discuss with the stakeholders to have a detailed knowledge of requirements. The team also creates the requirement traceability matrix (RTM) to map the test cases.

    • Requirement validation based on available resources (Time, money, and manpower)

Validating requirements helps the team streamline the testing projects and segregate them into categories to individually address the issues in each category and allow to resolve them immediately. Based on the project categories the requirements can vary. After gathering the project requirements, the team takes an overview of the available resources and validates if the available resources match the project requirements and identify the test environment.

Banking applications are usually complicated with multiple requirements. Also, based on new trends and customer requirements, the application features may change frequently. This dynamic nature of the requirements can further add complexity to the validation process, as they are subject to frequent changes based on the changing application features. Additionally, resource availability in terms of time, funds, and manpower may experience small variations, influenced by the specific project requirements and scope.

Can project requirements change frequently? Does frequent changing project requirements affect the testing project outcome?

Frequent changes in project requirements may not affect the project if requirement gathering is done considering all aspects. The diversions are evaluated by the project team to ensure they can accommodate frequent changes without affecting the project or workflow. Changes in applications are part of the project plan, so a pre-defined strategy and a thorough requirement validation can help the team to prepare with the time, money, and manpower for a successful test execution of business and system upgrades. The frequent changes will significantly not impact the project outcome if the requirements are gathered, assessed, and validated adequately before initiating the project.

    • Planning tests under the scope of the AUT

Planning the test is a critical step for the effective execution of the software testing life cycle. Testers define the test plan, application under test, scope of testing and more to yield expected results. Based on requirement gathering and validation, the team also effectively calculates the effort, time and cost required for testing. The project team also develops the test strategies, methods, and techniques during this stage. They also identify the test cases, test deliverables and milestones. The planning stage will only be successful when a detailed plan is presented, reviewed, and approved.

The test planning stage can be complicated because this is the stage when all the essential components are defined. If one or more project components are not added, then there will be a lack of clear understanding of the project, testing objectives, and scopes, leading to issues in deliverables. Since the executable test cases are identified in this phase, if the roles and responsibilities are not assigned, and test plans are not reviewed and approved, it will be tough for the project team to move on to the next step.  

Can the project team accommodate application changes if the request is raised at the later testing phases? Will it harm the project plan?  

Application changes are normal and can be raised at any stage. The changes are purely based on regulatory and technology updates as well as customer demands. Hence, the updates may come frequently, which the team must accommodate accordingly. Since the application changes are flexible there are greater need to incorporate these changes. Feature and functionality changes are integral parts of project plans.

    • Selecting the test cases for the sanity check

This is an interesting phase in the testing project where you identify the new functionalities, feature changes, and any bug fixes. Since the objective is to perform a quick and fast sanity check, there is no requirement to write new tests. This step ensures that the newly implemented changes are working without any errors.

The process can be complicated as only a small portion of test cases are selected for sanity checks. The team will fail to determine the impact ratio if the right test cases are not selected. The project team must thoroughly understand the project requirements and select only those test cases that might have the highest impact on the application’s functionality and performance.  

What is essential to identify the test cases for sanity checks?

Based on the project, application under test, project scope and test environment, the project team can identify the test cases based on their test predictability. The project team usually handles multiple test scenarios to understand the test cases that can have the maximum impact on application features, functionality and performance and choose the most probable test cases. Usually, the requirement gathering and analysis, understanding of AUT, project scope and the test environment are the essential aspects to identify the test cases for sanity checks.

    • Designing and developing the actual test cases

This is the actual phase when the testing team starts designing and developing the test cases. The team prepares the required test data for testing, and the quality assurance team reviews it. The team identifies the test cases that must be designed and developed and writes them to ensure that the written test cases are easy to understand. They also create test data and scenarios for test cases, identify probable results, and review and validate test cases. They update the requirement traceability matrix (RTM) with new changes.

The main objective for the team in this phase is to have a set of accurate and relevant test cases to ensure that they provide complete test coverage of the software and application. It helps the team to have a 360-degree overview of software quality. A comprehensive testing process allows the team to detect potential errors in the software before it is released. The team prepares the test data and keeps it ready for test execution. In the test case development phase, the testing team creates, verifies, and reworks test cases and manual and automated test scripts.

Banks may face two types of complications at this stage. First, if the team lacks the skill and knowledge to identify accurate and relevant test cases, and second, if due to multiple changes, the number of rework test cases increases. It may consume an ample amount of time and money to find skilled people for the job and validate the increasing number of test cases due to frequent changes in applications.

Can there be a possible solution to reduce the effort and time of rework?

It is time-consuming to find skilled developers and testers when your projects are time-bound. Even if you manage to put the entire team together, you might have to meet with one more challenge of accommodating frequent reworks. The project team might have very less time to meet the project deadline and time-to-market. So, banks hire third-party vendors to handle the testing projects to ensure they go live confidently without worrying about software quality. Since the amount of rework increases with application changes, it occupies a significant segment of the software testing lifecycle compared to new changes. Hence, the team selects a robust test automation solution to reduce the rework or regression test time.

    • Understanding the available test environment

Some banks and financial institutions have a conducive test environment with the necessary hardware, software, and network configuration for test execution. While the team designs and develops test cases, they can simultaneously evaluate the existing test environment. If the test environment does not support the massive business and system transformation and upgrade projects. The team must consider setting up the test environment for an effortless test execution project.

The process is complicated if the bank runs long on its legacy system and has a massive amount of data to migrate. Banks find it tough and time-consuming for seamless execution of the testing process without a favourable test environment. Moreover, they must delegate skilled people for the projects or hire a new team.

What is the possible solution if you do not have the required team strength, bandwidth, and allocated budget to set up a test environment?

Banks can consider hiring a third-party vendor to take care of all their test requirements and deliver the project on time by meeting all the quality standards and regulatory compliance. The QA solution providers have the required test environment or can set up one to ensure timely project completion.

    • Setting up the right test environment for seamless test execution

The test environment defines the condition on which the software is validated. Setting up a test environment can be simultaneously conducted with designing and developing test cases. In this stage, the project team determines the software and hardware conditions for testing the product. As the activity is done by the development team, the testing team may or may not be involved in the process. However, they check the readiness of the available environment, and this is known as smoke testing.

The first step in setting up the right environment is to understand the required architecture. The team must be skilled and aware of the available architecture. The test environment needs to be adaptable for seamless test execution. The process can be complicated if the environment is not favourable for test execution and is not ready with the test data set up.

How can the team ensure that the environment is built-ready for seamless test execution?

The team must validate the readiness of the test environment to ensure seamless test execution through smoke testing. They must understand the hardware, software, and network configuration well to ensure that the environment supports the test execution without any disruption.

    • Executing the test cases

In this phase, the test cases and test scripts that were created in the design and development phase are executed to detect defects or issues or errors in banking software. The evaluated results are gathered and assessed by the team. Test execution combines the two phases, planning and developing that verify the software quality. The activity also helps report bugs or technical glitches in the software. If the testers report bugs, the errors are reported to the developers who fix the bugs, and the testers test the software again.

The process can be complicated if there is no adequate test, or if there were any issues in the planning and development of the test cases. Also, if the test environment is not favourable or the test execution did not happen as per the test plan. The team must also put the stages together to finally execute the test cases.

Can multiple test execution degrade the software quality?

The objective of software testing is to validate the accuracy, stability, reliability, usability, efficiency, flexibility, portability and more. Software is tested to ensure that it successfully passes all the criteria. Multiple test execution does not degrade the software quality, instead, it delays the product release. It may not be necessary to test the same feature again and again. Moreover, testing the same feature repeatedly can be time-consuming. It is a good practice to test only applicable changes, performance, and security instead of testing the complete software functionality and menus. It saves time and effort and does not disturb the existing feature of the software.

    • Tracking and reporting defects

Tracking and reporting defects is one of the objectives of testing the software and its quality. The defects or issues are logged in defect tracking systems that are raised during the test execution. The details of the defects include descriptions, defect severity, priority, and more. The test execution results are examined to verify the software functionality and performance and simultaneously detect defects if any.

If the team identifies defects, it is sent to the developers for resolving the errors and retested again to ensure that the defects are fixed. After the defects are fixed team documents and report the test results to the stakeholders. The end objective is to identify and resolve the defects to ensure that the software can be released without any errors. Hence the software must be tested multiple times to ensure all defects are resolved. The process can be complicated if the team does not have an adequate mechanism to identify defects. Finding defects manually is a complicated process.

What solutions can organizations opt for to reduce the rework and multiple retests?

Multiple defect-tracking tools in the market can reduce the manual effort of identifying defects in the software and reduce the rework. For its benefits, organizations use defect-tracking tools that can be easily integrated with testing or test automation solutions. This saves time and effort and reduces rework. The team can confidently fast-track product releases.

    • Planning exit test followed by test closure

This is the final stage of the test execution and a critical one. In this final stage, the quality evaluation of the software is completed and determined if the product is ready for release. In this phase, all testing-related activities and formalities are concluded and documented. The testing team by now must have a clear understanding of the software quality and reliability. Whatever issues have been detected this far must be resolved. The team must document the testing process and improve the testing processes based on their experiences. It helps in removing the bottleneck from future testing projects.

The stage comprises preparing test summary reports, defect tracking and reporting, cleaning up the test environment, preparing test closure reports, transferring knowledge, and providing feedback for process improvement. The main objective of test closure is to validate the software quality and ensure the product market launch. It also confirms that the test execution was organized and completed efficiently. The process will be complicated if there is a lack of relevant information, or the team fails to capture feedback and critical lesson learnt from the project.

How to ensure that the report is whole and comprehensive?

Recording the project reports manually will be liable to errors as there can be a chance of missing out on information. There are a few test automation solutions in the market that comes with easy reporting solution. As reporting is a tedious, elaborate, and time-consuming exercise, these solutions are convenient and useful for the project team.

Conclusion

The steps, scenarios, and situations mentioned above are our understanding of the business and system upgrade projects we delivered. Yethi has supported 125+ banks and financial institutions in 30+ countries in their transformation and upgrade projects. In the 700+ projects we have completed so far, we have achieved quality and punctuality by completing the projects within strict deadlines.

We manage end-to-end test lifecycles efficiently to ensure customers receive quality outcomes within the project deadline. We have conducted end-to-end functional testing and non-functional testing in upgrade testing projects. We have also validated the robustness and responsiveness of systems while ensuring stability and flexibility in data migration and systems performance testing.

We leverage the highest potential of our robotic codeless test automation solution Tenjin during repeated regression cycles in a project. Our intuitive and intelligent solution comes with banking and FI-specific plug-and-play adapters that reduce implementation hassles with banking applications. Tenjin offers data-driven test execution and covers pre- and post-regression cases and effortless system integration testing, user functionality testing, user acceptance, regression testing and more. It comes with easy report generation capabilities and integration with defect management tools to generate test summary reports.

Rising Customer Risks in Digital Lending, how efficient test automation can help?

Digital Lending for test automation

The traditional lending process was time-consuming as the time for credit appraisal and disbursal used to be around three to four weeks, and the average time for account/money processing used to be approximately 60 – 70 days. In the traditional lending process, customers have complained that due to 30 days of the moratorium, the EMI would have started way ahead of the lending amount credited in their account. Often, customers used to opt for 6o days of the moratorium to avoid the inconvenience.

Soon organizations realized the need for digitalization to reform the lending process. Leading banks worldwide adopted digital lending to slash down the processing time to 24-hours. Digitalization brought a transformative change to the entire lending process. There has been a significant shift in end-to-end credit journeys, including the customer experience. Digital transformation has supported the credit processes. Digital transformation has improved revenue growth and achieved significant cost savings.

Digital lending allows customers to submit loan applications online. From applications, to documentation, verification and amount credited to your bank account, the entire process is carried out on mobile applications, and it takes less than a day to credit the principal amount to the customer’s bank account. From three weeks and 60-days, the time to cash is now reduced to 24-hours.

Rising customer risk in digital lending

Banks are enhancing the process by adopting paperless loan approval. They are automating the entire process to improve time and quality. But digital advancement has its own limitations. There is a rising concern for customer risk associated with digital lending. Customers share account details, personal information, credit history, and more on these applications. Hence, organizations must ensure that they maintain the stability, security, performance, and accessibility of these platforms.

The organizations are currently digitizing the credit and lending process. The banks are focusing more on improving customer experience by reducing the time taken for lending process. While organizations reduce the lending time, there is a major concern arising from customer risk. Let us look into the types of customer risks associated with the digital lending process.

  1. Multi-layered transaction process – The digital lending transacti0n is multi-layered as various lending services are outsourced to different entities. Multiple Fintech companies operate behind the operation to create a platform for transactions. As the customer uses these tech platforms for transactions, it becomes increasingly complicated in the cases of grievance redressal, like who will address the customer complaints, what actions should be taken and by whom to ensure that the services are more effective.

The platforms are integrated by embedded finance that forms a layer of services by different fintech modules. These platforms also work based on an algorithm that matches borrowers to lenders. While this algorithm creates efficiencies because several activities are performed simultaneously in a broader lending spectrum by outsourcing it to many Fintechs, there can also be certain drawbacks. If the borrower has appointed a defaulter as a guarantee, Fintech will address the loss. However, at the time of collection, customers will face many challenges.

  • Irregularity in information during loan origination process – The terms and conditions in the lending process are lengthy. The lending process becomes complex because not all organizations will have similar terms and conditions; some will have more than others. It increases the customer risk because customers may not have thorough knowledge and understanding of the repayment terms while signing the loan agreement. The customers may not comprehend the information like the interest rate, processing fees, overdue charges, annual percentage rate and more if not informed by the lenders. They would also not know the consequences of repayment delay, credit score impact, and implications of NPA.

Customers are also not aware of the payment recovery actions that organizations adopt. All this inadequate information makes borrowers make uninformed choices and affect their credit ratings. The loan disbursal is quick in digital lending, but without adequate information about the charges and consequences of non-repayment, the risk will increase.

  • Effects on unfavourable credit history – The previous point brings me to the current one that if the customers are not informed about the adversities of repayment delay or repayment overdue for months, it will affect their credit records. Most customers are not even aware that non-repayment or delays can affect their credit eligibility for future loans. Once the credit score is evaluated low, the customers must take multiple measures to rectify them or obtain credit approval to avail future loans. A low credit profile can lower the credit records making it difficult to apply for a new loan.
  • Lack of communication and transparency on assessment of creditworthiness – Digital lending, unlike the traditional lending process, which follows a thorough process of evaluation of customers’ credit profiles, does not engage in interaction with the customers, which is a requirement to analyse the customers’ creditworthiness. Digital lenders spend a lot of time on automated IVR, text messages, and social media advertisements to create awareness and push their services. Borrowers are not even aware of how the lenders have procured their contact details and credit history. It is not even clear how the lenders have evaluated the credit eligibility of borrowers. It creates a lot of confusion regarding whether it is spam or a genuine approach.

Like traditional lending, digital lending also considers two important aspects of the lending process; the customer’s willingness to pay and the ability to pay. While the first intention is evaluated through the customer’s previous credit history, the second intention is evaluated by the customer’s salary credited in the bank account, debit and credit history, investments, liabilities, and more. While applying for a loan, the digital lenders request access to contact details saved on customers’ phones. The lenders use this alternate data model to cross-verify borrowers’ credibility and positive intentions.

  • Lack of suitable assessment device – It is easy to avail of loans digitally as the processing is quick. But there is a lack of borrowers’ credit worthiness assessment that complicates the entire lending process. Often lenders provide top-up loans based on the timely repayment by the borrowers without a suitable assessment. This added loan sometimes may not flow well with the borrowers, and they may end up in high overdue.

The overdue reason could be the high-interest rates imposed within a short loan tenure. Several instances in the past highlighted that customers ended up being loan defaulters, and organizations had to contact them and force them to repay the loans. The collection process in digital lending happens digitally (mostly auto-debit). If customers miss one EMI, it will lead to a serious outcome, and lenders might look for alternative ways to recover the loans. Both borrowers and lenders face harassment.

  • Lack of grievance redressal – Digital lending lacks promptness in addressing customer complaints. In fact, the grievance redressal is not as quick as the loan disbursal process in digital lending. It also lacks transparency for customers, which their trust in digital lending. The digital lending ecosystem evolves multiple service layers offered by many fintech, making the customer interaction complicated and confusing and finally leading to failed redress. For most lending fintech, the only option for redressal is either through an integrated chatbot or WhatsApp chat sessions, which have certain limitations and do not always suggest adequate information. All these increase the intensity of redressal issues, and customers face problems.
  • Risk of compromised personal data – The unique selling feature of digital lending is how they gain access to customers’ personal data and use these alternate data for customer onboarding and credit appraisal processes. But it can be equally detrimental if the data points are sourced from external data agencies. Sometimes the borrowers sign two agreements in case the digital lending happens through a third-party service provider. In the above kind of agreement, the first signed agreement would be between the borrower and the lending app, where the lending app would be entitled to a different entity.  This structure allows the third party to gain access to customer data to collect all necessary information. These sourced data can be misused without the knowledge of the customers.

Why testing is an important digital lending platform?

Let us consider a scenario; you enter all your details, and suddenly the application stops responding with a notification message for you to close the application. You have to turn off the application, unaware of whether the application has recorded the details you have already entered. Or, you upload your documents and click your image, but the image does not get saved. The digital lending platform might have to contact the customer to inform about the missing information and ask them to upload all details again. Customers relate to the digital lending platform because of its seamless functionalities, easy navigation, superior performance, and security. If any of these is compromised and has errors, customers would not think twice about discontinuing using the application.

As per a report in Statista, “Digital lending is one of the fastest-growing fintech segments in India and grew exponentially from nine billion U.S. dollars in 2012 to nearly 110 billion dollars in 2019. It is expected that the digital lending market would reach a value of around 350 billion dollars by 2023”. We can imagine the growth of digital lending in the upcoming years with a 13.5% CAGR. The projected data give us an idea that the number of the digital lending platform will increase, which implies that it would need rigorous testing to ensure that the platform is top-notch without any technical errors. Each Fintech must also ensure that no organization loses their business to their competitors due to technical glitches of applications.

Let us investigate how efficient testing can improve the digital lending experience.

  1. UI/UX and integration – Customers seek platforms that are easy to use and navigate. Testing can evaluate a clean UI design and integration point to ensure that the customers enjoy a seamless experience of the lending platform.
  2. Performance – It is a massive turn off for customers if the application stops responding or if there is a performance error. Performance testing can ensure that the digital platform eliminates the possibilities of performance issues in the lending application.
  3. Accessibility and functionality – Customers relate to applications with easy accessibility and functionalities. They will not prefer using an application filled with features and functionalities. It confuses customers with the click-boxes and fields that do not allow them to navigate through the window command. Functionality testing helps detangle the application so that customers can easily access the applications and ensure that the platform performs at an acceptable standard.
  4. Security – Security is an important aspect of a digital lending platform. Customers share data with an expectation that the platform will maintain customer data confidentiality. The digital lending platform must ensure that the security of borrowers’ details is not compromised. Security testing can ensure that digital lenders maintain data security under the proper protocol.
  5. Regression – Changes, modifications, and addition to the digital platform are extremely frequent. Each change implemented in the application can harm the entire application functionality if not validated properly. Regression testing ensures that the new features are integrated adequately and correctly without disrupting the previous application features and functionalities.

Conclusion – Test automation is an effective solution to scrutinize the workflow of digital lending systems workflows. It validates the end-to-end process and saves time and effort for each implementation. Digital lending platforms have a high degree of inter-connectedness, which requires repeated testing to minimize manual efforts and achieve optimal coverage.

At Yethi, constantly upgrade and update your LOS and digital lending platforms to make them flexible and agile. The major challenge in testing these systems includes usability, performance, security, UI/UX, and Configuration. With Yethi’s robotic, 5th generation codeless test automation solution, Tenjin and deep domain expertise, the experts address the above challenges. Our team help banks and financial institutions drive their testing operation and ensure that their customers achieve their business goals within the stipulated timeline. Our intuitive solution – Tenjin, reduces 60-70% testing turnaround time.

Test Automation for Building Reliable Banking Systems

Test automation for reliable banking systems

Banking systems are far more developed with the latest technologies. Especially during the last decade, technological advancements have changed how we transact and interact with banks and financial institutions. Technology improvisation is not expected to end; with every passing day and year, it is now an essential aspect of our financial dealings.

By integrating banking transactions through mobile phones using UPI and NEFT payments, banking has moved another step towards digital advancement. While many third-party apps can connect to a bank account and make payments, some banking apps allow users to check the status of their cheques and card applications.

Digital transformation in banking is a matter of patience and caution. A mistake made in an online eight-ball game will not cause much damage, but software cannot be trusted with people’s money. Anything that goes wrong with transactions will directly be the bank’s fault, which can be detrimental for businesses.

Every software bundle that a financial institution releases must undergo a thorough testing process to ensure nothing goes wrong. In a growing business, software testing cannot wait for long days of testing or be prone to human errors. Therefore, banks and financial institutions are adopting codeless test automation. Test automation saves time, money, and effort, while codeless reduces human errors in the applications.

What is test automation and how can it help the banking sector?

Whenever organizations develop software, they do not directly release the initial version to the market. At least, strictly, not in the case of banking systems. The one place where you don’t want loopholes is in the software that connects to banking and financial archives.

The way financial institutions offer services has changed. With digitalization, financial services are more advanced. From how you avail services and access data to record transactions, everything must proceed with uniform speed while maintaining the quality of financial software and expenses. A financial sector is a place with humongous amounts of public data under a confidentiality contract, which means that if a bug in service causes loss of money, the bank can be defamed and sued.

Organizations must ensure that the applications offer outstanding customer experiences with real-time data. Real-time data must be safe and accessible to the customers to ensure complete customer satisfaction. This very reason creates a need for testing banking or financial software. Until codeless test automation came into the picture, the testing of such software was done by human eyes and brains, which were susceptible to many errors due to long test lines for running the whole testing program.

With maturity in machine learning, the linguistics of machines are now used to create a precise testing platform that allows faster, much more efficient testing of software and privatised control of the whole process.

How does Codeless test automation help financial institutions?

Codeless test automation is necessary for most core banking processes like loan origination. Loan origination and trading are some of the most affected areas of the industry. Such core banking operations require faster software development and a stable system to handle a plethora of tasks, all at once. In a world where a single rating on the Play Store matters, a few unsatisfied users might create a bad image with negative reviews. To understand why the financial service industry requires end-to-end codeless test automation, we need to know the requirements of financial software:

  • The application must be multi-utility and flexible to handle several multi-tier user requests at any given point in time.
  • The app must safely integrate with third-party apps on a large scale.
  • The app must deploy secure transactions with end-to-end data encryption.
  • The servers of the application must be secured enough to keep personal information hidden.
  • The application must be synced in real-time with the archives to make quick transactions.
  • The software must be stable enough to perform several transactions within a short time duration.
  • The app must record every detail from all transactions and store them securely on the user’s device or cloud.
  • The software must be able to troubleshoot queries raised by the customers.
  • The app must have a fail-safe system to protect the users from emergencies like device theft or data attacks.

Here are some of the core banking segments that require codeless test automation:

●       Trading

The world of Wall Street and many forexes rely on secure, real-time data and money transfers because people’s hard-earned money is at stake. In such a complex game of numbers and sales, a minor glitch in the system or algorithm would cause chaos for thousands. Codeless test automation makes sure that the software is tested in the most complex of conditions to make it fail-safe.

●       Digital banking

Banks have come a long way from transfer and withdrawal slips. Payments are being made on phones using QR codes, and business is being conducted on current digital accounts—that too with a bank with no branches. When an entire bank promises core banking from anywhere and everywhere, the whole banking framework depends on the software. With codeless tests, banking automation can turn branches and passbooks obsolete.

●       Loan origination

The entire process of loan origination, from the applicant to the lender to the credit score calculators and back to the applicant, is a long, complex operation. The credit market is the most fluctuating market and needs secure and accurate data for confirmation. Loan origination can benefit from proper assessment and credibility of the applicant, enhancing the user experience on both sides. With codeless test automation, the application becomes error-free and helps make accurate lending decisions for financial institutions.

Choosing the right framework

As a financial institution, the software you introduce cannot be open ware. A banking institution is mandated to hide its clients’ crucial and private data. With codeless test automation, the control of the software while it is connected to a network shall be in safe hands. You can choose what functions need to be automated and which ones are to be kept on hold. For testing such software, the testing framework needs to be hybrid or library-based, so it can be customised frequently with changing data-sharing norms.

Conclusion

Codeless test automation can help transform the banking sector by creating reliable banking systems that have become the need of the hour. Most of the banking processes can be streamlined to provide improved services and better customer satisfaction, leading to the overall growth of the sector.

At Yethi, we focus on improving the efficiency of the organization’s core software system. Being a niche QA service provider, we have helped and are helping several global banking/financial organizations increase the agility, consistency, and accuracy of their platform. With our efficient test automation solution.

Tenjin is an easy-to-integrate, codeless automation platform. This revolutionary solution has taken the test automation to next level with an accuracy rate of nearly 100%. It is designed to rapidly scan through the software and detect errors. This innovative platform works 3x times faster than any other automated testing system, while the simple plug-in and play design enable easy integration. Tenjin is developed with a focus on continuously helping banks and financial institutions across the globe to build a robust and resilient testing process.

Role of Test Automation in DevOps

Test Automation in DevOps

DevOps is a multidisciplinary approach that creates an advanced development environment by combining development, IT operations, modern practices, and tools. When test automation is carried out along the DevOps pipeline it aids in faster deployment of the software. DevOps supports continuous integration and continuous deployment (CI/CD), allowing the testing to be conducted earlier in the software development cycle. When testing is conducted earlier, it offers a much larger scope to improve the product quality by rectifying the errors/bugs in the earlier stage, which would otherwise amplify and cause severe issues if left unidentified earlier.

The success of the DevOps lifecycle depends on test automation which ensures that the developed software quality is top-notch. Continuous testing is a critical part of the DevOps cycle that lowers the operational and infrastructural risk and facilitates greater quality and improved speed, reduced cost, and increased accuracy. Hence, the success/failure of the end-product depends on developing it in a DevOps environment and implementing automation testing along the pipeline.

 Test Automation and DevOps

DevOps is the modern-day software development approach that can achieve the desired speed and agility by implementing test automation. Automation testing plays a pivotal role as it supports the dynamic CI/CD pipeline of the DevOps cycle. DevOps is a cultural shift that organizations are embracing for better and faster deployment, and test automation improves the quality with nearly 100% accuracy.

By implementing test automation, DevOps practice can benefit from the following:

  • Increases the process reliability
  • Test automation can detect the bugs earlier, hence, making the product deployment easier and quicker
  • The error rate is considerably reduced
  • Simplifies the process and promotes accurate and faster test case execution

Fig – DevOps Lifecycle

In the DevOps cycle, the test automation process has taken a shift-left approach, wherein testing is performed from the beginning of the software development cycle, reducing the length of delivery time while improving the quality of the release. This approach is purely focused on improving the quality to offer a great user experience, which will eventually improve the brand value and ROI.

How does the Automation Testing Process improve the previous cases?

The automation Testing process reduces the SDLC life cycles and follows the points mentioned below to improve the previous cases –

  • Improves speed
  • Offers fast feedback
  • Provide reliable results
  • Efficient result
  • Minimizes time and cost
  • Minimal human intervention

What role does Automation Testing play in DevOps?

Test Automation plays a crucial role in the following situations:

  • Incorporating test automation in DevOps, manual testing is minimized considerably as the automation processes take over. As the process is automated, the obvious human errors can be reduced and proven to be successful for repeated executions and regression tests.
  • It comparatively becomes easier to check an application after each step than to compare it at the end of the deployment. It makes it easier to correct each step than finding bugs after completing the software.
  • As advanced coding knowledge may be required for conducting testing at the API level, automation testing handles this task with ease as the process is automated and does not demand any coding knowledge. However, coding may be required only to set the process.
  • To correct the test cases in an estimated time limit and remove the errors, developers must change the code multiple times. The automation testing process offers an easy way to overcome these problems.

How to make test automation successful in DevOps

Here are a few points to consider yielding the best results from using test automation in DevOps:

Implementing testing simultaneous to the development

In the DevOps cycle operating on a continuous release approach, testing is carried out simultaneously to the development. By following this approach, issues can be fixed early and efficiently. This is an efficient way to reduce cost and improve time-to-market with improved quality.

Flexible test scripts

As the DevOps process consists of continuous integration, it is important to create flexible test scripts of higher quality to support the continuous integration process. The flexible scripts will support regression tests to ensure high accuracy and performance.

Choosing the right automation tool

It is important to choose the right test automation tool that will support the DevOps process efficiently. Make sure to use the tool that possesses all the capabilities that will suit your requirements.

Maintaining single test flow

It is recommended to test one thing at a time. Single flow testing will reduce the process complexity and makes it easier to find out the faults. Running multiple tests at a time can be a cumbersome process.

Building reusable test cases

Building reusable test cases will considerably reduce the time, cost, and hassle being taken to create a new test case. Organizations have reported that they have saved immense time and cost by creating reusable test cases.

Codeless test automation

Codeless test automation is the ideal choice for testing in a DevOps environment as it allows easy and faster product release across the complex CI/CD pipeline. Codeless test automation helps achieve the business objective by improving quality while reducing cost and risk.

Yethi’s test automation solution for banks and financial institutions

DevOps is the trend in the software development process banking and financial software processes are no different. To support the complex banking/finance software and ensure the developed software system is of high quality, Yethi offers a world-class test automation solution. Its test automation platform, Tenjin, is a 5th generation tool with robotic UI plug and play capabilities that can automatically learn and relearn to give higher testing accuracy.

Tenjin will help address the functional and non-functional issues in the complex banking/financial software system. With its half a million-test case repository, Tenjin can significantly help reduce time, effort, and money.

Test Automation Strategy to Achieve Product Development Goals

Introduction

The full potential of test automation lies in a well-formulated strategy. As the demand for feature-filled applications rises, independent software vendors and organizations focus more on delivering reliable and efficient products within strict product delivery deadlines.

However, as more and more companies are adopting agile and DevOps methodologies making application development a complicated process, manual testing can no longer be relied upon. When it comes to ensuring the quality and functionality of the software while speeding up its market launch, automated testing is the only viable option. Some of the key strategies adopted by firms to ensure best use of test automation are given below.

Steps to set your test automation strategy

  1. Ascertain your goals

The first step is to determine a successful enterprise test automation strategy and find out which test to automate. The best example of test cases are the ones that run often, are time-consuming, requires an extensive amount of data to perform a task, can be tested over multiple platforms, and have a high probability of test failures and risk.

The first strategy for successful test automation is methodically planning it out and defining the scope and goals of test automation.

2. Preparing a test approach

The test approach influences testing practice in organizations. With test automation and agile methodology, testing is becoming an integral part of the software development process. Once the team finalizes and decides to adopt a specific test approach and determines appropriate testing levels, roles and responsibilities are assigned to the respective team members.

Deciding on the right testing method will provide the maximum value when automated. Different testing levels requires various testing methods. Below are some of the testing methods that can help you to achieve maximum values.

  • Unit Testing

In agile methodology, unit testing is an important test automation strategy as it yields high ROI. The developers can write, execute, and maintain a small piece of code in form of either function or method, which are used during unit testing.

  • Smoke Testing

Smoke tests verify and provide instant feedback about the system builds. It confirms that all complicated functionalities are working without errors and defects. For an efficient smoke test, a few manageable test cases should be selected to quickly execute the tests.

  • Regression Testing

Whenever new features and functionalities are implemented in software, it introduces new errors in the build. Regression testing allows checking these features repetitively to detect defects. Regression testing can be automated to reduce the burden, time-to-market and cost.

  • Component Testing

Component testing tests the comprehensive business value and does not focus on the quality or quantity of the entity. Component testing can be automated to reduce time and expenses.    

  • End-to-End Testing

End-to-end tests can be complicated. Hence, the testers need to select the right tools, which are easy to use, maintain and scale to ensure high ROI.

  • Integration/API Testing

The software development relies on API and SDK, hence validating the comprehensive application performance is critical. Integration and API testing confirm the system’s performance and stability with external systems. Automating frequently run API tests is important as some of the changed codes may affect the API functionality.

  • Cross-browser Testing

Running app’s test manually over multiple browser / operating systems / devices can be a time-consuming task. Automating the cross-browser tests enables you to run these tests quickly. It is proven that cross-browser test automation has increased the test coverage, reducing the testing time and effort significantly.

3. Selecting test automation framework

Writing and running tests is based on detailed guidelines like coding standards, procedures, test-data reporting and more, etc, which is known as test automation framework. Here is a list of test automation framework,

  • Linear Scripting

Linear scripting is the most useful framework. With record and playback features, you can record the steps in sequence and play it whenever you need them.

  • Library Architecture

Library architecture identifies, divides, and group common tasks. The functions are saved in the library and used whenever the test scripts are required to use them.

  • Modular-Based Testing

In this type of framework, an application is divided into separate units and the testing is conducted in the unit base. Each part has respective test script, which is later combined as merged tests.

  • Data-driven Test

The errors found in linear & modular-based, data-driven test overcomes it. It allows one to store data and access it from the external file to test the same feature with different sets of data, whenever needed.

  • Keyword-driven Test

Keywords are stored externally and are used to represent or test the GUI of an application. The actions are tested following certain guidelines and are usually separated from the test logic.

  • Hybrid Testing

The hybrid testing facilitates application flexibility and provides accurate test results.

4. Selecting the right tool

As a part of a test automation strategy, it is important to select the right testing tool. Selecting the right automation tool is based on an understanding of the technology upon which an application is built and test requirements of the Application Under Test (AUT).

One of the main aspects of selecting the right automation tool is to address the testing demands of certain kinds of applications. The right automation testing tool must be compatible with the platform and easy to use.

As the number of platforms grows, the automation testing tool to validate application performance across the platform must be wisely selected. An ideal test automation tool is the one that supports cross-browser testing and has the ability for maximum use of the test scripts.

5. Create and run the tests

The next step is to write and execute the scripts. The following are the steps,

  • The test cases must be written in a way that enables the testers to use it in multiple projects
  • To remove the redundancy, it must be validated to see if a similar type of case has been written before
  • The test cases must be written in such a manner that anybody other than a test scripter would be able to execute it
  • Based on the feature and component, the user must prioritize the test cases
  • The high-priority test cases must be executed first

6. Maintaining test scripts

Scrutinizing testing parameters is important for maintaining test scripts. Regression test may take more time for the applications, which are rich in features, resulting in the importance of test automation to wane out.

Maintaining the test cases plays a crucial role; hence test cases must be optimized and categorized. It allows evaluation of test case subsets, and clearly defines the purpose of test automation. Process of test automation becomes easier with smaller test cases.

Importance of a successful test automation strategy to achieve product development goals

Importance of test automation strategy is to help you achieve product development goals. Finalizing test automation strategy helps in,

  1. improving test accuracy – Test automation improves accuracy by reducing human errors, which occurs in manual testing
  2. saving time and effort – Test automation reduces time and effort by delivering results faster
  3. offering test coverage – Test automation improves software quality by expanding the depth and scope of testing and ensuring a thorough examination and investigation of various software features
  4. increasing test case efficiency – Test automation improves test case efficiency by making slight improvements during the testing phase of software development cycles so that the product could be launched in the market on time
  5. Reducing maintenance cost – Test automation allows you to change and update testing methodology, reducing maintenance costs
  6. increasing the speed of the test execution – Test automation allows test experts to focus on more challenging, case-specific tests while executing redundant and lengthy test cases
  7. reducing manual intervention – Test automation can run with minimal manual intervention, which can be long, prone to errors and tedious
  8. analysing involved risks – Test automation analyses involved-risks delivering accurate results within the stipulated time

Conclusion

Having a successful testing strategy and framework can impact your business and organization in many ways. Test automation encompasses more comprehensive testing allowing you to accomplish complicated test automation tasks easily. A right automation strategy promotes the reused cases of critical components and improves employee productivity. The test automation strategies help in understanding business objectives and defining the product development goals.

Yethi’s well-managed Test Centre of Excellence can efficiently handle the test resources and infrastructure while ensuring the quality of applications. We help you meet your business objectives and product development goals with our test automation strategies.

Our proprietary 5th generation codeless test automation tool – Tenjin is an intuitive automated test suite. We have a test repository of 450k+ test cases, which help us to offer you high test coverage throughout all aspects of digital transformation and application testing like functional, UI/UX, performance, compatibility, security, geo-based and network testing. This smart tool blends with all test automation framework facilitating end-to-end testing like unit, regression smoke, integration, cross-browser and many more.

Importance of Data in Test Automation

Software development comprises of phases like gathering requirements, building, and testing the software followed by installation. In the development phase, the software may be exposed to all possible bugs and defects owing to human errors or technical glitches. Testing helps in detecting those errors and execute testing without any technical issues to ensure an outstanding customer experience.

A thorough software testing means checking all the components and elements of applications. The testing phase also includes all possible test case scenarios to extract accurate information and design the test cases considering the requirements. There can be a severe impact on the overall test process based on the type of data we select for test cases.

What is Test Data, and why is it necessary for testing?

To prepare test cases for software testing it is essential to select the right set of data. Test data is the data which are used to test the quality of the software systems. There are many ways to get the most appropriate test data for application testing. A skilled tester will be capable to source or produce test data to execute software testing to validate software performance and compare the desired results with the outcome.

Likewise, when we need the right set of data to evaluate quality of the software, we may also need data to test negative scenarios. Carefully choosing data will help in avoiding unexpected, unusual, and extreme results. If users enter the wrong information, the test case scenarios, which have been prepared out of most relevant data will continue to provide the most apt search result.

The production test data works best with a proper simulation of the real system during the testing phase. Ideally, both production data and synthetic data are used for testing, but in certain cases, production data is masked before using it for testing.

Why data is the key to test automation?

  • Test Data serves as the input, which is mandatory to test the application
  • Feeding the test data helps in validating the output if it is correct
  • Test Data selection helps in verifying different scenarios in testing
  • The test results are based on the inputs we feed in the system
  • Test Data is useful for the users to define the outcome
  • Test Data enable developers to track issues during the fix
  • Test Data confirms that applications provide expected result based on the input
  • Test Data allows you to be focused on systematic ways of feeding the data to the system
  • Test Data aids the tester to record the test case for future reference and data re-use

Types of test data and their importance

  • Valid Test Data:

Valid Test Data are supported by the application and helps in verifying the system functions and receiving an expected output whenever input is provided.

  • Invalid Test Data:

Invalid Test Data ensures that the application is working correctly. Including unsupported data format when these invalid values are provided for testing the application shows an error message to notify that the data is improper to function.

  • Boundary Test Data:

Combining the boundary value of an application, this type of data helps in removing defects that are connected while processing boundary values. However, these data are enough to handle applications. If the testers violate the process, then it may break the application.

  • Blank or Absent Data:

The files that do not contain any data and help in verifying the application response when no data is entered into the software is called blank or absent data.

Different ways that the test data are prepared:

  • Manually creating test data:

This method of test data generation is the simplest. It includes valid, invalid, null, standard production data, and data set for performance. It takes a longer time to generate test data manually with less productivity. A skilled testing team can create this test data without any additional resources. Lack of strong and in-depth technical knowledge, the testers would generate data with errors.

  • Using back-end data:

Back-end data generation helps in using back-end servers with a database and procure the data quickly. In this method, the need for having front-end data entry is removed. There is no need for technical expertise to create backdated entries. However, if the technology is not implemented, it might have an impact on the database and application.

  • Automated Test Data Generation:

Automated test data generation is most suitable to achieve excellent results with a high volume of data. The benefits of this kind of report generation are that a high volume of data is obtained at high-level speed and accuracy. The speed of delivering output is fast without any human intervention. 

  • Using third-party tools:

Using third-party tools makes it easy to create and extract data in the system. These tools have complete knowledge of the back-end applications and are built with a purpose to procure the data real-time with high accuracy. The test cases are built for future references that enable to execute test cases based on previous test case scenarios with accuracy and speed.

Challenges of test data sourcing

  • Accessing tools for achieving data sources can be an issue if the testing team does not provide permission to access the link. 
  • The lack of adequate and right tools can pose a challenge to source the test data.
  • The defects or bugs need to be identified at the earliest to run the testing for the software.
  • The testing phase may run for a longer time as most of the data are created during the execution phase.
  • Not all testers are skilled enough and have in-depth knowledge to create alternate test data solution for test data management.

Ways to control test data

Test data determines whether it is working as per expectations. Following are the ways to control test data: –

  1. Discover and understand nature of test data
  2. From multiple data sources extract a subset of production data
  3. Mask sensitive test data
  4. Compare the expected with actual result and automate the results
  5. Finally, refresh the test data

Conclusion:

Yethi’s team consists of experienced quality assurance professionals exclusively focused on the BFSI industry. We have in-depth knowledge of the domain and technology systems supporting it. We help many marquee organizations to achieve their business objectives within the stipulated timeframe, without compromising on quality.

Yethi’s flagship 5th generation codeless test automation tool – Tenjin is an intuitive automated test suite. We have a test repository of 450k+ test cases, which help us in providing cross-platform testing across multiple devices and networks with high test coverage throughout all aspects of digital transformation and application testing like functional, UI/UX, performance, compatibility, security, geo-based and network testing. This smart and intuitive tool can switch between API’s and the GUI, making it a perfect testing tool for regression testing in open banking applications.

Importance of Continuous Testing in Continuous Delivery and Integration

The quality of software can be determined when it adapts to changes and promptly responds without any delays. However, overtimes with extensive use the code may change, and manual testing needs to be conducted again to identify the impact of these changes on the functionalities of the system.

A software is manually tested at the software development stage but comes with several drawbacks as follows:

  1. Manual testing of regression packs delays the release of the software. It takes weeks and months to get feedback from the developers as the written code is tested. The entire process is relatively time-consuming and expensive.
  2. Even the most advanced and expert testers may not perform regression testing with accuracy. It might be hard to detect the impact of the set of changes in a complex software system through inspection.

All about Continuous Delivery

Alongside code writing, it is equally important to focus on quality during continuous delivery. Testers work closely with developers to help them create unit tests. They start by writing code to automate the small number of tests that cannot be covered by unit tests. Continuous delivery allows us to rapidly test product with our users and collect data on the possible outcome. Continuous delivery enables you to carry out experiments quickly in the on-going production stage.

With continuous delivery, there is no need to ensure quality of software at the end of the development cycle before its launch. The code goes straight to production allowing for quality check at the same time it is created. The testers closely work with the developers to ensure that the quality is maintained.

Automation propels testing and focuses on the quality of the applications, and so most of these applications are tested in the unit testing phase itself. The tested code is deployed at the production stage for continuous delivery as soon as it is checked into source code management and passes a deployment pipeline.

Why Continuous Testing is important?

Developing software and testing them are not two separate activities, but a part of the same equation. Hence, testing should be performed simultaneously along with developing the application. Automation like test automation, deployment automation, and environment automation allows you to execute these changes faster with minimum effort.

Application and systems need consistent updating of test documentation to keep it ready with the changes in the applications. Many different types of tests, both manual and automated, need to run continuously throughout the delivery process. Followed by continuous delivery and integration, continuous testing automation is included in the deployment pipeline. The deployment pipeline allows creating packages that can be implemented in any environment and runs unit tests, providing feedback to developers.

These test packages need to pass comprehensive automated tests that run against them. These packages are available for self-service other environments for activities such as exploratory testing, usability testing, and ultimately release after they pass all these automated tests. Automation testing is important for continuous delivery, which is followed by continuous deployment. Hence, it gives rise to the need for continuous testing to keep a track on changes.

In the deployment pipeline, the changes are implemented simultaneously with continuous integration during product release. If the common defects are not highlighted in the deployment pipeline, it could delay product release. However, some tests are improved and updated in the pipeline if defects are detected later. The focus here is to find the issues as early as possible to reduce the release time of the product.

How Continuous Testing can improve Continuous Delivery?

Implementation of continuous testing in continuous delivery can benefit your delivery pipeline. The following are the points that would explain how continuous testing can improve continuous delivery: –

  1. Executing API, UI, and Performance testing along with Regression testing will ensure the quality of the app in various customized cases. Continuous testing will allow the developers to perform a live test of the implementation, functionality, and behaviour of their code with testing tools.
  2. The DevOps team can implement parallel tests with automatic notifications after making the necessary configurations to the CI environment. Testers can notify developers whenever there is a failure in any build component. Testing of all changes can be done automatically using continuous integration.
  3. The QA team can verify and validate the product quality by running regression, load, and functional tests deployment. The automation testing will be continuously carried out if the test module configuration is correct. In case if there is a build failure in the system, it can be fixed by manual testing.  

There are some best practices for continuous testing in continuous delivery:

  1. Continuous testing enables you to test operating systems and devices before production. It saves money in the long run as instead of running a large volume of test cases, load tests implemented every day at specific target areas reveal smaller bugs and fix them immediately.
  2. Accurate results can be obtained conducting test simultaneously during the development phase as compared to running tests in a controlled lab environment.
  3. Detecting defects and fixing them will be much easier and can run at the same time if the entire test suite is divided into several smaller tasks.
  4. To have adequate knowledge and detect the issues or discrepancies in app architecture and test automation, the metrics must be properly used. Proper use of metrics can also help up to prevent the risk of failures and its impact.

Conclusion

Continuous deployment and continuous delivery require a well-structured and planned environment for continuous testing. In absence of which CI and CD effort would not be successful. At Yethi Consulting, we follow an agile test automation framework. Our scriptless test automation platform, Tenjin, is a plug-and-play banking aware solution. Its robotic capabilities enable them to learn and adapt to the application and its updates. Regardless of the complexity and number of updates, Tenjin facilitates continuous testing, minimizing the manual effort and speed up the test execution.

Discover the Test Data Management Techniques in Banking that empower Software Testing

The Growing Need for Test Data Management

Early in 2018 four major Banks in the US had clients up in arms when, for several hours, banking services were not accessible via their mobile banking apps. The interrupted services were attributed to a major spike in traffic due to it being payday. Notwithstanding, reputational damage had been done to the banks and, adding to their woes, a social media tirade on platforms like Twitter, where irate clients vented their frustrations and further lambasted the banks, ensued. The experience of these banks again highlighted the importance of software system testing in banking and financial services. However, software system testing is only as good as its test data management strategy, which should be adopted and implemented to:

  • Manage test and development processes to meet testing and application development requirements
  • Secure data and streamline cloning processes, delivering clones needed to meet upgrade and patch cycles as well as maintain data security
  • Identify appropriate replicable accounts and transactions from production to meet test criteria
  • Mitigate the threat of identity theft concerns among consumers and regulators
  • Improve turn-around-times during system upgrades through improved planning of data refreshes and overall data utilization.

The importance of test data management in testing

At its core, data management is the science of creating and maintaining the data sets generated by software system testing, driven by cause-effect relationships, producing predictable outcomes and responses. These data sets can be generated entirely by the tester, by simulating each stage of the customer or transaction journey, producing what is called synthetic data. Alternatively, data generated by actual transactions and previously recorded is called migrated data, providing authentic sets. Each of these forms of data generation has its value and challenges.

Synthetic data needs to be interoperable, able to account for diverse systems in varying environments without diluting the complexity of inter-relationships. Besides, the data needs to be refreshed and valid for multiple rounds of testing and if in an automated environment, should not need to be updated by manual intervention. Migrated data, in turn, is drawn from authentic transactions has limited reusability across different test-cycles, hamstrung further by data confidentiality obligations.

Mitigating the risks inherent in Test Data Management

Implementing a Test Data Management strategy requires that several risks and their potential impacts be considered. The complexity of the data, structured or unstructured, whether the databases are new or from legacy systems and how the data is stored. If kept in multiple environments, it may have the added challenge of access sensitivities and potential confidentiality breaches. Assessing the time available for data discovery, its generation and management is another factor that is paramount in ensuring representative samples are obtained. Besides, test data management requires different types of data for different types of testing, from performance through to user acceptance testing, so data needs to be organized correctly to fit within the required time and budgetary constraints. Another potential risk is the measure to which the organization operates in a distributed multi-supplier or outsourced environment, with multiple users accessing the data in multiple locations. Operating in such an environment also highlights the importance of data security and protection. As a standard, new security protocols will be required as well as staff training, highlighting the importance of protecting live production data as well as guarding test environments.

Empowered Software Testing through Test Data Management

Given the dynamic nature of the banking environment and the need to ensure optimized and efficient process continuity, any process that does not facilitate this expediency will have a negative impact on the entire system. Accordingly, if the process of choosing, interpreting and scrutinizing test results is time-consuming, arduous, and requiring specific knowledge of underlying applications, it will have a direct negative impact on the entire system. The time it takes for reporting and information sharing in an organization can also be a significant factor in the efficiency of the entire organization.

To meet these dual needs of time and efficiency, banks should implement the following test data management techniques, while taking care to mask sensitive information:

  1. Database cloning through the copying of production data
  2. Data sub-setting by substituting production data when appropriate, &
  3. Synthetic data generation, through the production of synthetic data based on a clear understanding of the underlying data model, which requires no de-identification

Yethi, a leader in software solutions and quality assurance in global banking and financial services has developed substantial expertise in creating end-to-end enterprise-wide test data management services which include data quality assessment, data masking, data subset, data archiving, data cleansing and data optimization. Yethi also assures that through rigorous control the thorough management of test data is ensured, beginning with quality assured consistent data. Data security and privacy are also safeguarded, while storage requirements and software costs are significantly reduced.