Underwriting moves beyond the point of origination
Intelligent agents can continuously evaluate cash flows, verify new information and identify emerging risk throughout the lending lifecycle.
Novel Patterns is helping lenders build AI-driven, explainable and continuously intelligent credit ecosystems — where trusted data, domain-specific AI and governed decision-making redefine the future of digital lending and investment management.
Financial services has spent years digitising access, data movement and workflows. The next phase is about what institutions do with that infrastructure: how evidence becomes judgement, how policy becomes executable and how decisions remain explainable after AI enters the process.
In this conversation, Ashwani Arora discusses why underwriting is shifting from a one-time event to a continuous process, why governance must be designed into AI rather than added after deployment, and where domain-specific financial intelligence fits into the next generation of lending and investment technology.
Intelligent agents can continuously evaluate cash flows, verify new information and identify emerging risk throughout the lending lifecycle.
Data, policy, reasoning and human accountability need to travel with every consequential AI recommendation.
India's financial rails already move information efficiently. The next opportunity is an intelligence layer that converts that information into governed decisions.
Trust should be continuously earned and continuously monitored, not inferred from a static three-digit score.The Big Interview · IBS Intelligence
Financial institutions already have access to more data, more digital infrastructure and more computing power than at any point in the past. The competitive question is increasingly about what happens after that information arrives.
In lending, that means turning evidence into explainable decisions throughout the lifecycle rather than treating underwriting as a single event. In investment management, it means applying intelligence to operational scale, personalisation, reconciliation, reporting and unified data.
Agentic AI expands what software can do between those steps, but the interview makes an equally important distinction: autonomy cannot mean abdication. Every consequential action still needs a governed boundary, a traceable rationale and a clear point of human accountability.
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