Can agentic AI make credit proactive, precise and more inclusive?
Lending has traditionally followed a sequential process: sense, analyse, decide and act. Each step depends heavily on human intervention, with analysts collecting information, interpreting signals, conducting checks and moving files through the next stage.
The emergence of agentic AI is beginning to challenge that model by connecting these steps into a more continuous workflow. AI agents can pull data, reconcile information, initiate checks, identify exceptions and recommend the next action. However, according to Sushantam Mohan, Chief Data Officer, Vivriti Capital, the transformation is unlikely to begin with autonomous credit decisions.
Instead, adoption will move from the bottom of the value chain upwards, starting with workflows where the information is verifiable, volumes are high and the tolerance for errors is relatively greater.
“The first genuinely agentic workflows will be the high-volume, verifiable, high-error-tolerance ones: document collection and chasing, KYC/KYB, bank statement and GST reconciliation, tracking conditions precedent and subsequent, security...
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