Case Study | Banking & Financial Services
As one of the largest US-based banks, this organization manages over $200 billion in assets and is the financial partner of choice for venture-backed tech startups, having funded over 30,000 companies. With a 40-year commitment to the innovation economy and the stability of a 125-year-old financial institution, the bank plays a crucial role in fostering job creation and driving a more equitable, sustainable, and low-carbon economy.
Overcoming Legacy Barriers to Unlock Scalable Growth
To stay ahead in an increasingly digital landscape, the bank sought to modernize its online banking platform, which struggled with poor maintainability, limited scalability, outdated user interfaces, and suboptimal performance. Their goal was to transition from a legacy system to a digital banking experience—one that would be more secure, efficient, and user-friendly while accommodating evolving customer needs and competitive market dynamics.
Catering primarily to startups, venture capitalists, and innovation-driven businesses, the bank required a specialized financial management platform tailored to their unique needs. The new solution needed to meet strict compliance and regulatory requirements while delivering high availability, security, scalability, and maintainability.
With deep expertise in the BFSI sector and a proven track record of leading digital transformations for Fortune 500 financial institutions, Brillio emerged as the ideal transformation partner.
A Scalable, API-First Digital Banking Ecosystem
Rather than relying on a traditional data migration, Brillio designed a domain-driven, microservices-based architecture using an API-first approach. This enabled seamless service decoupling, regulatory compliance, and scalable infrastructure while allowing the bank to introduce new digital services quickly and efficiently.
To ensure a disruption-free transition, Pre-Migration APIs were used for data validation, while an Appian-driven approach facilitated user and data migration with minimal risk. A report generation utility was also developed, providing post-migration insights and ensuring the accuracy and integrity of migrated data.
The platform was seamlessly integrated with the bank’s existing systems, allowing it to support 1,500 concurrent users and enabling rapid onboarding, with 350 users and 350 accounts per client. This ensured the bank could scale operations while maintaining performance and compliance.
A modern, intuitive interface was introduced to optimize workflows, enable payment tracking, and enhance credit/debit card management with customizable alerts.
To support user adoption, an automated digital assistant was introduced, providing real-time assistance to migrated users. A series of co-innovation workshops were conducted to refine requirements, address gaps, and validate technical feasibility through proofs of concept. By optimizing migration processes, 30% more customers were migrated in parallel, significantly increasing operational capacity.
Driving Operational Performance with 85% Workflow Automation
Brillio’s solution enabled a seamless transition for over 35,000 commercial clients, significantly enhancing customer satisfaction and achieving an NPS of 80%. The improved platform led to increased market share and revenue growth by providing a more efficient, secure, and scalable banking experience.
By implementing 85% workflow automation, manual interventions were drastically reduced, improving overall operational efficiency. The API-first approach allowed for faster product iterations, reducing time to market and enabling the bank to quickly respond to emerging opportunities. Performance optimizations resulted in a 50% increase in concurrent user capacity, with page load times under 5 seconds and API response times below 1 second.
Security remained a top priority, with Brillio ensuring zero code vulnerabilities and full compliance with industry security standards. The transformation also enhanced scalability, allowing the system to handle 1.5 million transactions over 12 months with a 5X increase in data migration velocity per batch run.