This post was originally published on The Economic Times
The numbers are hard to argue with; as of early 2026, more than 2.61 billion financial accounts are enabled on India’s Account Aggregator (AA) framework, with over 180 million accounts successfully linked. In the first half of FY26 alone, AAs facilitated an estimated Rs 1.47 lakh crore in loan disbursals across 15 million loans. Monthly volumes are now running at approximately Rs 24,000 crore, nearly double the previous half-year period. According to Sahamati’s H1 FY26 Impact Report, the AA framework now touches roughly 1 in 10 personal loans disbursed in India by value, accounting for over 10% of retail and MSME (micro, small and medium enterprise) lending by volume.
The rapid scaling of AAs reveals a complex structural challenge. For decades, Indian lending was stifled by information scarcity and a reliance on collateral. Today, the problem has inverted. Lenders are inundated with granular transaction data providing a real-time picture of a borrower’s financial life. Yet, more data does not inherently improve credit outcomes. Without sophisticated analytical layers, an abundance of data leads to cognitive overload or algorithmic noise that masks underlying risks.
The mirage of data volume
For most
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