Client Context
Leading Bank’s Non-Banking Financial Services (NBFS) division, focused on wealth management and financial planning, embarked on a digital transformation initiative to automate its Distribution Onboarding process. This end-to-end workflow spans multiple platforms—Salesforce, Avalon, and CAS—covering everything from client onboarding and financial planning to risk assessment and commission processing. A scalable automation framework was required to ensure reliability, accuracy, and repeatability across systems.
Challenges
Multi-platform integration across Salesforce, Avalon, and CAS with unique processing rules
Onboarding for 17 distinct client types, each requiring specific validation and business logic
Multiple screening systems (CASA, AMS, fraud risk, compliance) with varied conditions and outcomes
Avalon-based dynamic decisioning for FNA (individuals) and BNA (non-individuals) added path complexity
Complex post-Avalon validations in Salesforce: risk rating, CIF key generation, EDD approvals, Tier 2 checks
PRI generation and CAS integration required strict data and financial rule validation
Manual testing was inefficient and error-prone for the scale of onboarding workflows
Solution Delivered
A robust, end-to-end automation framework was built to validate all onboarding stages across platforms and client types. Key features included:
- Full automation of onboarding from Salesforce to Avalon to CAS
- Business rule validation across 17 client types for accurate flow and document handling
- Integration coverage for CASA, AMS, fraud risk, Avalon (FNA/BNA), and Salesforce (CIF, risk rating, EDD)
- Support for onboarding variants: New to Bank, New to Product, Existing Clients, File-based onboarding
- CI/CD pipeline integration for early defect detection and continuous validation
- Modular, reusable test components to scale across future use cases and minimize redundancy
Value Delivered
- 1000+ automated test cases executed across integrated onboarding systems
- Achieved 80% automation success rate with continuous pipeline optimization
- 90% regression coverage automated, reducing manual effort and enhancing consistency
- Improved defect detection for screening, FNA/BNA, risk, and commission processes
- Boosted release confidence with fewer production issues and faster deployments
Impact Highlights
- 200+ critical defects identified and resolved early in the development lifecycle
- 45% reduction in overall testing cycle time, increasing delivery speed
- Automation framework extended for new integrations and scalable future rollouts
- Fostered collaboration across QA, Dev, and DevOps through continuous testing practices
