India's Data Ecosystem: Speed vs. Accountability

India's financial data ecosystem is operating at unprecedented speeds, with automated systems handling millions of data fetches each second. Technology providers are transforming raw data into credit judgments and risk assessments, a process that historically involved human underwriters. This shift means the role of human underwriters is evolving, focusing more on establishing standards and managing complex exceptions rather than direct data review.

Despite the efficiency, concerns are mounting over accountability when automated systems err. Reports indicate thousands of errors across aggregators, yet no agreed service standard governs them. This lack of clear oversight means customers may not receive optimal financial products. The system's reliance on deposit data also introduces bias, potentially excluding individuals without formal banking histories.

To address these gaps, a 23-factor framework has been proposed to evaluate data intelligence products. This framework aims to bring transparency and accountability to the automated financial assessment process. While automation handles routine verification and judgment, human oversight remains crucial for setting standards and addressing complex, non-standard cases in the BFSI sector.