AI is Making Digital Lending Smarter: Rajat Deshpande on the Future of Credit

Finbox and the Future of Digital Lending: Rajat Deshpande on AI, Automation and Agentic Technology
AI is Making Digital Lending Smarter: Rajat Deshpande on the Future of Credit
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Artificial intelligence is steadily changing the way financial services operate, and digital lending is one of the areas seeing some of the biggest changes. From processing documents and analysing financial data to automating lending workflows, AI is becoming part of how lenders make decisions and serve customers.

In this episode of the Analytics Insight Podcast, host Priya Dialani speaks with Rajat Deshpande, Co-founder and CEO of Finbox, about how AI is shaping digital lending and the technology behind it.

Rajat explains how Finbox uses machine learning and alternative data to build credit profiles and support digital lending. He also discusses the company’s approach to AI-led workflows, agentic AI, loan origination, governance and human oversight, along with the possibilities AI could open up for embedded finance.

How is AI changing digital lending and BFSI?

AI is helping lenders handle tasks such as document processing, customer intake, credit workflows and customer interactions. Rajat explains how machine learning and alternative data can make lending processes faster while reducing the effort involved in handling applications.

Why are lenders adopting AI for lending workflows?

AI can help lenders coordinate several tasks, automate routine work and reduce processing time. Rajat points to the economics of smaller-ticket loans, where reducing manual work can make the lending process more practical and efficient for lenders.

What can agentic AI do in digital lending?

Agentic AI can bring together models, data, context and specific tasks within a workflow. In lending, this could allow activities such as document processing, validation and credit-related tasks to happen in parallel rather than being handled separately.

How does Finbox approach AI governance and human oversight?

Rajat discusses the importance of protecting sensitive data and maintaining controls as AI becomes more involved in lending. Finbox keeps certain important parameters from changing autonomously and uses human evaluations, sampling and AI observability.

What could AI mean for embedded finance?

AI could make financial services more conversational and accessible, including loan origination through WhatsApp, answering customer questions and helping users find relevant offers. Rajat also points to regulatory considerations around areas such as investment advice.

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