Early warning systems are powerful tools for financial institutions. This is especially true for institutions serving low-income borrowers, such as micro and small business owners who are more vulnerable to economic shocks that could impact their ability to repay. By detecting early signs of financial stress, early warning systems allow lenders to take preventive action, support borrowers in managing repayments, and ultimately reduce delinquencies while strengthening portfolio health.
Traditionally, lenders have relied on two main inputs to build these systems: repayment behavior and feedback from field staff. While useful, these indicators usually highlight risks only after financial stress has already affected repayment. A few financial service providers also use credit bureau data to guide collections, but this, too, often serves as post-event information rather than an early signal.
Today, account aggregators are transforming the way financial information is used in India by facilitating unified, consent-driven access to financial data. In just the first half of FY2025 alone, more than ₹74,500 crore was disbursed through the account aggregator framework, backed by over five million customer consents, highlighting how quickly the model is scaling. Accion is collaborating with local ecosystem partners to develop use cases for leveraging account aggregators, including the creation of early warning systems. With customer consent, lenders can regularly access and use bank statement data to identify borrower stress much earlier. By analyzing cash flow trends, overdraft usage, and irregular income patterns, lenders gain a real-time picture of borrower health, enabling them to move from reactive collections to proactive, risk-based strategies — a shift that will only deepen as account aggregator-enabled disbursals are projected to cross ₹2.5–3 lakh crore annually within the next few years.
Translating risk signals into collection strategies
An effective early warning system is not just about identifying red flags — it’s about linking insights to action. By segmenting customers based on their probability of default, lenders can tailor collection strategies to risk levels, improving both efficiency and outcomes.
With customer consent, bank statement data can be accessed consistently and serves as one of the strongest contributors to early warning systems. The following are sample indicators that can inform such systems:
A combined view of risk
To create a holistic risk profile, lenders can combine four key data sets:
The combined output can be represented in a risk score, making it easy to link risk levels to specific collection strategies.
This differential approach ensures resources are deployed where they matter most, minimizing unnecessary interventions while focusing effort on high-risk customers.
The transformative impact of smart early warning systems
When powered by bank statement data, early warning systems enable lenders to improve:
Using bank statements as a consistent source of information in early warning systems has its challenges. Since the approach is consent-based, customers may not always provide access to their primary or all bank accounts. However, by integrating bank statement data into early warning systems and developing straightforward consent processes for monitoring bank statements, lenders can access relevant information to transition collections from a reactive process to a proactive strategy. The result is not only healthier portfolios but also stronger trust and repayment discipline among customers — laying the foundation for more responsible lending and sustainable financial inclusion.
Accion Advisory combines decades of on-the-ground experience with insights into new technologies to help our partners become more sustainable and scalable. We work with a variety of organizations focused on serving the financial needs of low-income people and businesses in emerging markets. Learn more about how we work here.
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