Why a data segregation strategy for Fintechs is non-negotiable

India's fintech ecosystem has rapidly evolved into one of the world's most dynamic and innovative markets. India is home to over 10,000 fintech companies, making it the third-largest fintech ecosystem globally. With a high adoption rate of 87%, compared to the global average of 64%, fintech companies in India have significantly transformed the financial landscape.

In pursuit of growth, many fintech companies acquire multiple licenses, including Prepaid Payment Instrument (PPI), Payment Aggregator (PA), PA-Cross Border (PA-CB), UPI, NBFC, and Account Aggregator (AA) licenses to offer a wide range of financial services. This expansion can happen organically through business diversification or via mergers and acquisitions. 

Based on our analysis of the top 50 fintech companies in India, over 35% hold three or more licenses, reflecting the growing trend of fintechs expanding their service offerings. The analysis shows that 22% of these companies operate with a single license, 42% hold two licenses, 22% have three licenses, 10% possess four licenses, and 4% manage five licenses. This multi-license approach allows fintechs to cross-sell products, diversify revenue streams, and strengthen their market presence.

As a result of holding multiple licenses, they often face overlapping regulatory requirements in the areas of net worth maintenance, KYC, data security, risk management, third-party outsourcing, audits and reporting to the Reserve Bank of India (RBI). This creates a complex web of rules, making it challenging to manage data flows, maintain operational efficiency, and ensure complete regulatory alignment. In the rush to scale, fintech compliance can sometimes take a backseat, exposing companies to penalties, suspensions by the RBI, and, most critically, loss of consumer trust. Therefore, regulatory compliance must be a core business priority, not an afterthought.

One crucial aspect of regulatory compliance is data segregation strategy for Fintechs — the structured separation of data based on licenses, product lines, and regulatory requirements. The RBI has consistently emphasised the importance of unauthorised access to data and preventing data leaks, especially as fintechs handle vast amounts of sensitive customer information. Holding multiple licenses means companies must comply with various data-related regulations concerning collection, processing, storage, and deletion. A failure to segregate data properly heightens the risk of data breaches, attracts regulatory penalties, and damages consumer confidence. 

At the start of CY24, the Reserve Bank of India (RBI) took supervisory action against a leading fintech player for non-compliance with various regulatory provisions. The action aimed to safeguard consumer interests and maintain the system's financial stability.

It highlights the critical need for fintechs to embed compliance mechanisms, including data segregation, across all licensed operations to mitigate regulatory risks and uphold consumer trust.

Building a scalable data segregation framework

A well-defined data segregation strategy for Fintechs is more than just a compliance measure — it forms the backbone of sustainable growth. Fintechs can seamlessly integrate new licenses by implementing a scalable framework while maintaining data integrity. The key components of an effective data segregation model include:

• Regulatory mapping and relationships: Map data points to specific regulatory requirements. Fintechs must identify reporting obligations to the RBI for each license, ensuring smooth audits and regulatory submissions.
• Process and policy alignment: Evaluate internal processes and policies for each license, ensuring that data flows align with internal governance frameworks and external reporting mandates.
• Role-based access and controls: Implement granular access controls for teams handling compliance, risk, operations, and customer service. This prevents unauthorised data sharing between product lines while ensuring operational efficiency.
• Audit trails and real-time monitoring: Establish real-time data access, movement, and usage tracking. Transparent audit trails help strengthen internal oversight and enable fintechs to respond swiftly to regulatory inquiries.
• Standard Operating Procedures (SOPs): Fintechs should develop clear SOPs outlining data flows, storage practices, access controls, and cross-product data usage protocols to ensure regulatory compliance, prevent data co-mingling, and support internal accountability.
• Human resource mapping: Assign teams and individuals to specific licensed entities, maintaining clear roles and data access distinctions. For personnel working across multiple group entities, robust access controls should be in place to prevent unauthorised cross-entity data handling. Employees should also be trained on the importance of audit trails and compliance, ensuring that all actions related to sensitive data are properly logged.

Conclusion

In India's fast-growing fintech landscape, establishing a data segregation strategy has moved beyond just a regulatory requirement—it's now a critical business strategy. As companies expand their product portfolios and secure multiple licenses, a robust data segregation framework ensures operational efficiency, regulatory compliance, and data security. Beyond avoiding penalties, it reinforces customer trust by safeguarding sensitive information.

By adopting a structured and scalable approach to data segregation, underpinned by strong SOPs and audit trails, fintechs can navigate regulatory complexities, future-proof their operations, and position themselves for sustainable growth.