Ensuring quality and regulatory readiness in the implementation of a wealth management system

Key takeaways

• Critical integration defects were identified and resolved before production release, reducing regulatory and operational risk.
• A structured repository of test cases and automation tools established a reusable quality framework for future projects.
• Data integration between source systems, Data Mart warehouse, and wealth management platform was validated end-to-end.

Deutsche Bank Polska initiated the implementation of a new wealth management banking system integrated with a newly built Data Mart warehouse. The warehouse aggregated data from multiple source systems to meet reporting and regulatory requirements, including MiFID II obligations.

The programme introduced a multi-layer dependency model: transactional systems feeding the Data Mart, transformation logic within the warehouse, and export mechanisms providing input files to the wealth management application. Any inconsistency across these layers could lead to reporting errors, client portfolio misrepresentation, or regulatory exposure.

The bank required structured and independent testing support to ensure that both data integration and functional behaviour of the Wealth Manager system met internal standards and compliance expectations before production launch.

The challenge

The project combined several high-risk elements typical for banking transformation initiatives.

• Documentation originated from third-party vendors and required independent verification.
• Data flows spanned multiple source systems, a Data Mart warehouse, and downstream export interfaces.
• Regulatory compliance (MiFID II) increased the sensitivity of data accuracy and reporting correctness.
• The system had to be validated both at integration level (data correctness) and functional level (front-end user behaviour).
• Testing was conducted under a Waterfall framework, requiring clear documentation, traceability, and formal acceptance stages.

The key difficulty was ensuring end-to-end consistency: from raw transactional data to validated wealth management portfolios presented to users.

Solution overview

A dedicated team of test analysts and test automation engineers supported the implementation programme. The scope covered documentation analysis, preparation of structured test artefacts, development of automation tools, and execution of integration and functional testing.

The work addressed both the backend integration layer and the front-end Wealth Manager application.

The main areas of responsibility included:

• analysis of third-party documentation related to Data Mart structures and system interfaces,
• preparation of test cases and test scenarios covering data integration between source systems, the warehouse, and export files,
• development of SQL scripts and queries to validate transformation logic and data consistency,
• design and implementation of automation tools to validate input files generated by the Data Mart and investment funds,
• Selenium-based automation for front-end testing of the Wealth Manager system,
• execution of smoke, integration, and acceptance tests,
• management of defects, retesting, and validation of corrections.

Testing activities were documented using TestLink and Mantis, ensuring traceability and auditability in line with banking governance requirements.

How the work was executed

The engagement began with detailed analysis of the documentation delivered by external vendors. The goal was to identify potential ambiguities, inconsistencies, and areas requiring additional validation before implementation progressed further.

Test scenarios were designed to reflect real business cases, particularly in the area of portfolio data, investment fund inputs, and export file correctness. SQL-based verification allowed direct validation of warehouse logic and ensured that transformation rules produced expected results.

Automation tools were developed to validate input files provided to the Wealth Manager system. These tools compared expected and actual structures and values, reducing manual verification effort and increasing repeatability. Front-end testing was supported by Selenium, enabling regression testing of user flows and functional behaviour.

Testing covered smoke validation, integration testing across systems, and formal acceptance stages required by the Waterfall delivery model. Defects were tracked, prioritised, and retested systematically to ensure controlled progression toward production readiness.

Operational results

The testing programme delivered measurable stability and readiness before system go-live.

• Critical defects were identified and resolved prior to production deployment.
• A structured repository of test cases was created for reuse in future development and enhancement initiatives.
• A ready-to-use test automation framework was delivered and adopted across the organisation.
• Data integration between source systems, Data Mart, and Wealth Manager was validated end-to-end.

The project concluded with a recommendation for system implementation based on validated quality criteria.

Business value

The structured testing approach reduced the risk of data inconsistencies reaching production, particularly in areas subject to regulatory scrutiny. By validating transformation logic and file exchanges before launch, the bank mitigated the risk of reporting errors and operational disruptions.

Automation tools lowered future testing effort and provided a foundation for regression testing in subsequent releases. The established repository of test cases increased transparency and repeatability in quality assurance processes.

By embedding independent validation into the implementation programme, Deutsche Bank Polska strengthened control over system quality, regulatory alignment, and production readiness.

Through structured integration testing and automation, Deutsche Bank Polska ensured that its new wealth management platform met operational and regulatory expectations before entering production.