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Redefining Lending Through Agentic AI: Faster, Smarter, Personalized Financial Services

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TL;DR:

Agentic AI is revolutionizing lending in financial services by autonomously analyzing borrower behavior, optimizing loan portfolios, and dynamically managing risk. Unlike traditional AI, it acts and adapts in real time, enabling faster loan approvals, personalized repayment plans, and proactive fraud detection while maintaining human oversight for complex or high-value cases. Banks like JP Morgan and Danske Bank are already adopting Agentic AI to enhance efficiency, fairness, and compliance, redefining borrower experience and operational excellence.

Podcast Summary: Infosys BPM’s Deep Dive into Agentic AI with Megha Kochhar

Agentic AI is emerging as a transformative force in financial services, particularly in the lending sector. Unlike traditional AI, which operates within predefined rules to analyze data and support decisions, Agentic AI is autonomous—it acts, learns, and adapts in real-time. This capability allows financial institutions to optimize loan portfolios, manage risk dynamically, and create personalized solutions for borrowers.

From Credit Scoring to Dynamic Risk Management

Traditional AI models rely on historical data—credit scores, liabilities, income—to assess borrowers. Agentic AI enhances this by continuously updating models in real time. For instance:

→ It can adjust credit scores or loan terms when a borrower demonstrates improved financial behavior, such as consistent savings or reduced credit card usage.

→ It identifies emerging default risks in specific regions or industries and adapts lending policies accordingly.

→ It proactively flags at-risk loans and recommends restructuring plans to minimize losses.

These capabilities expand access to credit for qualified borrowers who might have been rejected under traditional models, while maintaining risk controls for lenders.

Adoption in the Banking Industry

Several banks are experimenting with or implementing Agentic AI solutions:

→ JP Morgan uses AI and machine learning for credit scoring, fraud detection, and customer service, enhancing decision-making for loan approvals.

→ Danske Bank improved its fraud detection capabilities by over 50% and reduced false positives by 60% through AI-driven systems.

Such applications indicate that Agentic AI adoption is steadily advancing across financial services.

Accelerating Loan Origination and Borrower Experience

Agentic AI can speed up loan approvals by pre-verifying documents using natural language processing (NLP) and interacting with borrowers to resolve missing information. By learning from past applications, the AI continually improves its accuracy and processing speed, enhancing the borrower experience while reducing operational delays.

Human Oversight Remains Critical

While Agentic AI increases efficiency, human oversight remains essential in:

→ Handling unique edge cases

→ Auditing for fairness and compliance

→ Managing complex corporate loans

→ Supporting high-value customers

This hybrid approach ensures that automation complements human expertise rather than replacing it entirely.

Personalization and Adaptive Lending

Agentic AI allows lenders to tailor financial products at a granular level. For seasonal businesses, it can adjust repayment schedules based on cash flow cycles. It can also monitor post-disbursement behavior, like early repayments or financial stress, and adapt loan terms proactively. This level of personalization strengthens lender-borrower relationships.

Ensuring Fairness and Compliance

Autonomous systems must be designed with fairness in mind:

→ Training data must be reviewed to eliminate bias, as demonstrated by Zest AI’s underwriting solutions.

→ Continuous monitoring and policy engines ensure decisions align with ethical and regulatory standards.

→ Regular audits simulate diverse regulatory scenarios to confirm fair and compliant decision-making.

These measures safeguard borrowers and reinforce trust in AI-driven lending.

Key Takeaways

→ Agentic AI moves beyond prediction: It acts autonomously, continuously adapting to borrower behavior and market conditions.

→ Credit scoring and risk management become dynamic: Real-time adjustments allow lenders to optimize portfolios and expand credit access responsibly.

→ Borrower experience improves: Faster approvals and personalized terms enhance satisfaction and loyalty.

→ Human oversight remains essential: AI complements, not replaces, human judgment in complex or high-value scenarios.

→ Ethics and compliance are built-in: Bias mitigation, monitoring, and regulatory policy engines maintain fairness and accountability.

Agentic AI is poised to redefine lending, offering banks the ability to operate more efficiently while delivering highly personalized services to borrowers. As adoption grows, it promises a more responsive, adaptive, and equitable financial ecosystem.

Citation

For deeper insights on Agentic AI in lending, refer to the Infosys BPM Podcast episode “Redefining Lending Through Agentic Intelligence” featuring Megha Kochhar, Industry Principal – Financial Services. Listen and explore the full discussion here: Infosys BPM Podcast

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