HDFC Bank raises testing stakes

Michiel Willems
August 12, 2026

HDFC Bank has replaced legacy wealth-management systems and manual processes with a unified, API-driven Finacle platform, extending a wider technology transformation that has already prompted the Indian lender to overhaul its software testing capabilities.

The bank has deployed the Finacle Wealth Management Solution across its domestic and offshore wealth operations, consolidating previously fragmented systems while automating processes spanning investment products, margin lending, portfolio management and regulatory compliance.

The new platform covers 12 asset classes, including mutual funds, fixed-income securities, private equity, alternative funds, structured products and insurance. It also supports held-away assets, allowing investments maintained outside the bank to be incorporated into a client’s overall portfolio.

For HDFC Bank’s quality engineering teams, the scale of the implementation created an unprecedented assurance challenge that involved data migration, financial calculations, regulatory rules and integrations with the wider banking ecosystem.

This included around 350 APIs support functions, including real-time settlement, high-volume transaction processing, automated corporate actions, compliance and product launches.

Every connection created dependencies involving data quality, permissions, processing sequences and error handling.

Testing had to therefore establish that information continues to move accurately between the wealth platform and connected systems, including when a service is unavailable, a data feed is delayed or transaction volumes suddenly increase.

2025 project

The deployment followed an earlier QA modernisation initiative involving Katalon and QualityKiosk, announced by HDFC Bank in March 2025.

That project was intended to address difficulties testing complex scenarios at scale, integrating testing frameworks with existing systems and reducing the extensive manual intervention required throughout the software testing cycle.

“At the core of this initiative was the development and deployment of an API-driven, cloud-native platform designed with a microservices architecture,” HDFC Bank said at the time.

The bank adopted an open-source automation framework capable of managing complex test cases at scale and integrating with its existing digital platforms.

“This allowed for integration with existing digital platforms, facilitating unified and streamlined test management and execution processes,” the bank explained.

Mumbai, one of the fastest growing QA sectors within the financial services space (source: ARA, Free Pexels) — *Mumbai, India’s financial hub and home to HDFC Bank*

“As a result, manual interventions dramatically decreased, significantly enhancing operational efficiency and allowing testing teams to concentrate on more complex, high-value tasks.”

HDFC Bank said the automation initiative enabled defects to be identified and resolved more quickly while improving the accuracy and reliability of customer-facing applications. It also accelerated software deployment timelines as the bank sought to introduce new digital services more rapidly.

Although HDFC Bank has not disclosed whether the same testing approach or suppliers were involved in the Finacle implementation, the earlier project provides insight into the bank’s broader shift towards API testing, automation and quality engineering.

Those capabilities will be increasingly important as the institution moves more operational processes away from manual workflows and onto interconnected platforms.

Data assurance

Data migration and reconciliation represented two of the most significant risks in the wealth transformation.

Moving to a consolidated platform requires HDFC Bank to ensure that portfolio positions, transaction histories, customer details and product records remain complete and accurate. The bank also had to reconcile data held on the new platform with source records and information maintained in connected systems.

In wealth management, relatively small discrepancies can affect client valuations, performance reports, fees or regulatory records. Errors may also be difficult to detect when information passes through several applications before reaching a client or relationship manager.

The Finacle platform automates net asset value updates, systematic investment plans, withdrawals and reconciliations. While this can improve efficiency, it also transfers responsibility for many operational controls from employees performing manual checks to software executing rules automatically.

“Our objective was a unified, digital-first platform that delivers agility, efficiency, and innovation.”
– Rakesh Singh

Testing had to consequently cover business rules, exception handling and audit trails, as well as the accuracy of the final result. Automated processes needed to respond correctly when data is incomplete, delayed or inconsistent rather than simply continuing with an incorrect transaction.

Margin lending adds another layer of testing complexity. The platform provides real-time collateral checks, automated workflows and risk controls intended to deliver faster approvals and more precise valuations.

These functions depend on the accuracy and availability of market data, collateral valuations, lending limits and eligibility rules. Test teams must establish how the system responds when prices move quickly, collateral values fall or external data feeds become unavailable.

Multi-currency portfolios present similar challenges involving exchange rates, conversion timing and rounding rules. Differences between markets and processing schedules can affect valuations, performance reporting and transaction settlement across the bank’s domestic and offshore operations.

Broader regression risk

Mumbai-based Rakesh Singh, group head of private banking, international banking, financial institutions and banking-as-a-service at HDFC Bank, said the bank’s objective was to modernise wealth management through “a unified, digital-first platform that delivers agility, efficiency, and innovation.”

“With the Finacle Wealth Management Solution, we have consolidated our domestic and offshore businesses, automated key operations across margin lending, bonds, and mutual funds, and empowered relationship managers with real-time insights,” Singh explained.

He added that the transformation would allow HDFC Bank to adapt more rapidly to regulatory changes, scale its operations and deliver differentiated services to clients.

That greater speed increases the importance of regression testing. A software or regulatory change introduced for one product, asset class or jurisdiction must not disrupt calculations and workflows elsewhere on the shared platform.

Regulatory requirements also need to be translated into precise and testable software rules. Those rules must then be validated across transaction processing, product eligibility, reporting and compliance workflows.

The presence of more than 350 APIs further expands the regression surface. Individual services may be changed and released independently, making contract testing and continuous validation important for detecting whether an update has altered the data or behaviour expected by another system.

Sajit Vijayakumar, chief executive officer of Infosys Finacle, said the implementation consolidated HDFC Bank’s domestic and international wealth operations on an advanced platform.

Finacle is focused on helping institutions transform wealth management through “composable front-to-back-office capabilities,” he added.

A composable architecture can allow HDFC Bank to introduce products and services without replacing the entire technology stack. However, it also means the reliability of the overall operation depends on multiple components continuing to work together as they are updated.

Neither HDFC Bank nor Infosys Finacle disclosed details of the testing strategy, migration process or performance benchmarks used during the implementation.

However, the scope described by the firms points to the need for extensive integration, migration, performance, security, resilience and regression testing.

Continuous production monitoring will also be necessary to identify problems that emerge only under live transaction volumes, market events or failures elsewhere in the banking ecosystem.

HDFC Bank’s earlier work with Katalon and QualityKiosk suggests that the bank had already recognised the limitations of manual testing as its software estate became increasingly API-driven and based on microservices.

At the time, the bank described its approach as a case study in the benefits of modern software testing and stressed the role of automation in delivering reliable digital banking services.

The Finacle deployment raises those stakes further. Testing is no longer concerned only with whether an individual application works as expected. It must provide assurance that valuations, transactions, compliance controls and customer data remain accurate across a highly interconnected wealth operation.

As HDFC Bank consolidates more products and processes onto shared digital infrastructure, software quality becomes inseparable from operational and financial risk.