The client, a leading global bank headquartered in the US, offers a digital mortgage tool to improve the user experience for mortgage applications and mitigate digital risks.

The digital mortgage tool designed by the client is a loan origination platform that revolutionizes the mortgage generation process. It is integrated with an industry leading end-to-end mortgage processing platform. Infosys collaborated with the client for user acceptance testing (UAT) as well as functional and end-to-end testing of select platforms for the large-scale program. This was aimed at ensuring that configurations and customizations in the loan data flow pipeline met the client’s business goals. For faster decision-making, the Infosys team ensured the availability of fee information and data sub-fields in a filtered master sheet with detailed data synthesis.

Key challenges

  • The regression suite encompasses end-to-end testing of loan registered using the client’s tool which is then processed through the integrated end-to-end platform. This suite uses a combination of test data, borrower data, financial information, and subject property details as the basis for eight test scenarios. These scenarios were being manually tested, requiring significant effort and time.
  • Validating the fees for each loan is one of the most critical aspects of end-to-end manual testing. Based on the set-up criteria, each loan has a unique set of fees. Success of the UAT hinged upon confirmation that the correct or expected fee is charged to the loan application.
  • In sum, the key challenge was filtering the fees applicable to the loan under test from the master file. The team then needed to double-check the auto-populated fields and values. The client struggled with manual efforts because some loans had multiple fee requirements. This took considerable time and effort, delaying testing timelines.

Ready to experience?


The Solution

Implementing an automated data validation framework with detailed reporting capabilities

  • The automation solution designed was based on a framework to expedite the fee validation process during regression testing. This program was built to carry out validation between application data and pre-defined files provided by the client.
  • The solution proved to be highly robust, automated, and scalable. Gaps were quickly identified and resolved.
  • The new design allowed standalone validation for fee-specific or fee-based testing as part of the new configuration update and also accommodated ad hoc requests

Adoption of Automation to Expedite Crucial Multi-field Data Validation

The Infosys-designed framework highlighted the use of logic and fundamental languages. We built a reusable and adaptable solution to overcome the key challenge of fee testing during regression cycles.

Framework details

  • Tool – Selenium
  • Framework – Selenium and hybrid framework
  • Languages – Core Java
  • Input – MS Excel Spreadsheets
  • Output systems – Extent reporting and MS Excel Spreadsheet

The final output reports were attached to relevant test scripts in the application lifecycle management tool for client to see the reports



Increased accuracy and efficiency

Increased accuracy and efficiency
Automating the fee validation process resulted in the increase of both accuracy and efficiency of testing during regression. The automated solution enabled the client to avoid compliance issues related to fees.

Effort and time savings

Effort and time savings
There has been a 70% reduction in manual effort due to automated validation. This also helped reduce the validation time to about 25 minutes compared to the five hours it took manually.

Faster time to release

Faster time to release
No delays in completing regression within the stipulated timeframe. Major roadblocks or delays due to manual testing by the UAT team were reduced based on immediate feedback given to clients on specific issues.

Reduction in defect leakage

Reduction in defect leakage
Two out of three defects were identified during UAT prior to deployment. Defects were identified at the initial stages of regression thereby reducing the chance of leakage into higher environments.

Increased scalability and repeatability

Increased scalability and repeatability
Due to automation of the time-intensive section of regression suite, the team undertook multiple rounds of regression with variance in test data. This allowed the client to increase test coverage and prevent potential issues.