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How EPS is transforming the Account Aggregation Ecosystem as a TSP
Cateina Technologies in collaboration with Electronic Payment Service (EPS), as a TSP (Technology Service Provider), transforms the Account Aggregator ecosystem with secure data sharing, bank statement analysis, underwriting risk assessment, real-time account monitoring, and automated data-fetching for EMI payments. The Account Aggregator (AA) framework, a pivotal initiative under India's digital financial ecosystem, enables secure and consent-based sharing of financial data across institutions. EPS, as a TSP, provided tailored solutions to Financial Information Users (FIUs) based on their specific use cases.
Tech used
Open Banking
Microservices
Zero Trust
Consent Management
India
Challenge
EPS, as a TSP, provided tailored solutions to Financial Information Users (FIUs) based on their specific use cases. These solutions include bank statement analysis, credit underwriting, real-time account monitoring, periodic data-fetch requests, and pre-EMI balance inquiries. By addressing these critical requirements, EPS enhanced decision-making, compliance, and financial efficiency for its clients.
The primary challenge was data complexity across institutions. Financial Information Providers (FIPs) provided financial data in various formats, making it challenging to integrate into a standardized framework for analysis and decision-making. The Underwriting Risk with Bank Statement Insights was also a lacking feature in the ecosystem. Lenders required in-depth bank statement analysis to assess borrowers’ financial stability. Manual processes often delayed risk evaluations and affected loan approval timelines, impacting business efficiency. There was also a need for continuous account monitoring. Real-time tracking of accounts for compliance and repayment readiness was essential. However, maintaining a scalable, automated solution to handle large transaction volumes across multiple clients added to the complexity.
The existing solutions also lacked automated and scheduled FI requests. Institutions needed timely and consistent data-fetching systems for routine checks such as balance inquiries, cash flow assessments, and compliance verifications. Manual and delayed processes often hindered operational efficiency. On the loan front the Pre-EMI Balance Validation was not vailable. Ensuring sufficient account balances before EMI payments was critical to reducing loan defaults. Manual checks lacked scalability and accuracy, leading to errors and inefficiencies.
FIUs had to maintain multiple sets of APIs tailored to the specific requirements of different banks. This created additional operational overhead, increased costs, and led to inconsistencies in data integration and processing. Diverse API Maintenance also posed challenges.
Solution
EPS implemented an automated analysis engine that extracted key metrics from bank statements, such as income patterns, expense trends, overdraft occurrences, and cash flow consistency. These insights were generated in real-time to support efficient and accurate underwriting decisions. It also standardised API integration. The unified API framework developed connected diverse FIPs and FIUs seamlessly. This ensured consistency in data sharing and enabled streamlined bank statement analysis across platforms, reducing the operational complexity for FIUs. The solution also simplified credit underwriting for lenders by automating the extraction and analysis of key financial data. This allowed for faster decision-making with reduced risk of manual errors.
A Real-Time Account Monitoring system was deployed to continuously monitor account transactions for FIUs. This improved compliance with regulatory standards, flagged anomalies, and helped reduce default risks. A system to automate periodic data-fetching for routine checks, including balance inquiries and cash flow assessmentwas also implemented. For pre-EMI payments, the system fetched and validated account balances a day before the due date, significantly reducing payment failures.
In AA Ecosystem data protection is a key requirement. To ensure compliance with data protection regulations, the solution included a mechanism to automatically purge data points after consent expiry. It protected user privacy and maintained adherence to regulatory requirements, such as those outlined by the RBI.The solution also leveraged a microservices-based architecture with cloud-native technologies. It also ensured scalability, fault tolerance, and robust performance, even during high transaction loads.
Result
EPS solution tremendosuly improved Loan Underwriting. The bank statement analysis engine accelerated underwriting processes by 60%, providing lenders with actionable insights in real-time. Pre-EMI balance checks resulted in a 35% improvement in payment success rates, reducing non-performing assets. it significantly increased EMI Payment Success
The solution was a win in terms of Cost and Time Efficiency.Automated periodic data-fetching and analysis reduced operational costs by 30% and manual processing time by 50%. It also helped in data driven decision making.With insights from bank statements, lenders could better evaluate borrower behavior, leading to more accurate risk profiling and decision-making.
It also Enhanced Compliance Monitoring.Continuous account monitoring increased regulatory compliance by 45%, with automated alerts preventing potential violations.
