Key Takeaways
With an exponential explosion of data sources—structured and unstructured, new and emerging—and multiple digital public pipelines to lean on, Indian lenders continue to find newer ways of assessing creditworthiness. That someone, with their digital footprint or otherwise, could be evaluated as being creditworthy, though, is something financial regulators rightfully worry about.
Last week, the Reserve Bank of India (RBI) gave voice to these concerns. Through a draft circular, the central bank brought credit risk models of regulated entities under supervisory review and mandating a raft of changes aimed at holding the boards of lending entities responsible for the models these companies use.
This move is critical given that in the next decade, the Indian market could rapidly evolve into one driven by digitally-led algo-credit models as newer datasets emerge as trustworthy and reliable.
Algorithmic credit models represent the future of lending due to their ability to process vast amounts of data quickly and accurately, enabling more efficient and informed credit decisions. These models leverage advanced machine learning techniques and diverse data sources, including non-traditional metrics such as social media behaviour and digital footprints, to assess creditworthiness with greater precision.
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