5 Test Data Management Challenges in BankingCigniti Technologies
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Banking is one of the few sectors that are critical to our everyday life. Testing of banking applications needs to be thorough with due importance given to data privacy and protection. Finding adequate and comprehensive test data is always a challenge and, in banking, it is more challenging due to the complex and sensitive nature of data.
Why is test data a challenge in banking?
- Compliance and regulatory requirement make mishandling of data punishable by law, inviting severe penalties and loss of trust
- Banking is becoming bigger, diverse and complex with many technological advances that have revolutionized the way we bank today
- Banks have complex IT infrastructure, often with legacy back-end
- Limited window of testing as new compliance requirements need to be implemented within a set deadline
- Increasing incidents of insider fraud have made banks wary of giving even limited access to production data
Test Data Management challenges in Banking
Data compliance requirements:
Banks are mandated by law (like the Gramm-Leach-Bliley Act, EU Data Protection Act etc.) and standards like PCI DSS (Payment Card Industry Data Security Standard) to protect and safeguard customer data. To make it more complex, these regulations vary from country to country and are frequently updated. Due to rising incidents of data breach, banks are forced to limit access to production data for cloning purposes. Testers need to rely on data from testing beds which may not be as expansive as production data.
Variety and complexity of data
: Banking, by nature, is a complex operation with huge variety in data and an intricate web of business rules woven around this data. It takes a good amount of experience to understand the nature and necessity of each data to be able to mine the right data for your test case.
Data is often stored in legacy back-end and scattered across different DBs. There may be upstream or downstream data dependencies between different systems like cards, payment processing, rewards and loyalty etc. which make it difficult to pull the required data. The problem is compounded by lack of sufficient documentation supporting the often decades-old legacy system.
Data for complex test cases may not be readily available in the correct format in the database. The tester might have to apply business rules and resort to data transformation to get the correct data to run the test without failing the data integrity rules.
Regression Testing :
Every release, big or small, needs to be preceded by adequate regression testing to ensure that introducing a new functionality has not broken an existing functionality. This is important in banking as any issues in production could personally affect the lives of customers. Finding test data for the entire regression test suite is difficult and a painstaking process.
A few things that banks can do
- Use test data management tools to ease the data identification process
- Adopt Data masking to mask production data for use in testing
- Use dedicated regression bed or adopt risk based regression testing
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