Driving Enterprise AI Adoption for an Indian NBFC with an Outcome-first AI Roadmap

Industry: Financial Services | MSME Lending
Client: An RBI-regulated NBFC focused on MSME lending across India

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Client Overview

A large lending business operating across customer acquisition, underwriting, disbursal, and collections in semi-urban and rural markets.

Challenge

The lending funnel had severe drop-offs, with 1,000 leads yielding only 25 disbursals
Manual data capture, low FTR, and dependency on credit managers were increasing TAT and rework.
Collections remained field-heavy, with limited prioritization, weak intent visibility, and high RO workload.
Sequencing AI investments across the lending lifecycle fast enough to improve KPIs without disrupting live operations.

Solution

Identified 5 high-priority AI initiatives across lead engagement, document intelligence, voice agents, credit assessment, and collections
An impact vs effort prioritization matrix and mapped each initiative to KPI outcomes such as conversion, FTR, TAT, CE%, and PAR30
Completed primary and secondary market scans across 20+ vendors, competitors, and practitioners to define build / buy / customize paths
Designed a quick-win roadmap plus AI Lab operating model to take experiments into production

Impact

Defined a path to improve lead conversion from 2.5% to 7%
Established roadmap interventions to improve FTR at source from 50% to 80%+ and pre-disbursal FTR from 70% to 90%+
Built a roadmap to reduce application-to-disbursal TAT from 10 days to 6 days while improving collections efficiency.

Strategic Significance

Strategic Significance:

Showcases Indexnine’s ability to convert process-heavy BFSI operations into KPI-linked AI roadmaps with clear quick wins, strategic bets, build-vs-buy decisions, and an operating model for sustained execution

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