Case Study

Automating the PD Process

LendingIQ deployed an AI PD Questionnaire Agent and Voice AI-assisted workflow to cut follow-up rates in half and improve sourcing-to-underwriting handoff quality.

Client

One of India's leading NBFCs

Domain

Lending & Credit Operations

Function

AI Agents & Voice AI

Role

Consulting & Implementation

50%

Reduction in follow-up cases

30%→15%

Applications needing clarification

100%

Structured borrower responses

India's banking sector moves fast but the paperwork often does not. One of the country's largest banks faced recurring delays from incomplete borrower information and repeated clarification loops. LendingIQ was engaged to redesign the process using AI agents.

01

The Challenge: A Broken Loop Between Sales and Underwriting

The NBFC's loan sourcing relied on Relationship Managers (RMs) gathering borrower information in face-to-face conversations. In theory, this human touch is a strength. In practice, it had become the biggest bottleneck in the pipeline.

Every RM had their own way of capturing data. Critical risk signals were going unnoticed. Underwriters were spending significant time chasing down information that should have been collected upfront.

Inconsistent data capture

RMs captured borrower information in different formats, causing important risk signals to be missed.

Sales-underwriting back-and-forth

Nearly 30% of applications needed follow-up queries before underwriters could proceed.

Manual documentation overhead

Conversation notes were unstructured and mapping responses to application fields took significant manual effort.

Static questionnaires

One-size-fits-all PD forms did not adapt to borrower profiles, leaving key risk gaps.

"The goal was to replicate a mini-underwriter at the sales stage, catching gaps before they reach the credit desk."

02

The Solution: An AI Agent That Thinks Like an Underwriter

LendingIQ built an AI-powered PD Questionnaire Creation Agent which is designed to sit between RM and underwriter, ensuring critical questions are asked before files reach the credit desk.

The system analyzes application data, detects risk signals, and generates personalized PD questions for each borrower profile. It does not rely on static forms; it listens, adapts, and follows up.

Capability 1

Mini-underwriter intelligence

The agent analyzes borrower profiles, application details, and risk indicators to generate targeted PD questions by replicating underwriting logic at the point of sale.

Capability 2

Dynamic questionnaire generation

Instead of static forms, questions adapt to each customer profile. Up to two follow-up loops trigger automatically when responses need deeper exploration.

Capability 3

Voice recording + response mapping

A voice recorder system assists RMs during conversations by separating voices, tagging borrower responses, and mapping answers to the correct loan application fields.

Capability 4

Voice AI interview agent (architecture ready)

The platform architecture is prepared for a fully conversational Voice AI interview mode, with discovery and planning completed for the next phase.

03

Before & After: What Actually Changed

Before

  • ✕RMs captured data in inconsistent formats
  • ✕Static questionnaires missed critical signals
  • ✕About 30% of files required clarification follow-ups
  • ✕Underwriters received incomplete information
  • ✕RMs spent too much time on documentation

After

  • ✓Standardized borrower response capture
  • ✓Profile-specific AI questions with adaptive follow-ups
  • ✓Follow-up rates reduced to around 15%
  • ✓Underwriters received more complete, structured files
  • ✓RMs focused more on borrower engagement

04

Results That Speak to the Credit Desk

The impact was immediate and measurable. Within the deployment window, the NBFC saw a fundamental shift in how efficiently loan applications moved from sourcing to decision.

01

Follow-up cases cut from ~30% to ~15%, accelerating approval timelines.

02

Borrower information became consistently structured across RM teams.

03

Credit desks received cleaner, decision-ready application inputs.

04

Sales teams regained time for relationship-building over paperwork.