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CASE STUDIES · AI & CREDIT INTELLIGENCE
IFLOW CASE STUDY

Grow Faster
Lend Smarter

How an NBFC scaled its lending without compromising credit quality

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782AI SCORE
78%
Faster turnaround time
75%
Better credit quality
38%
Lower acquisition cost
60%
More processing capacity
THE CHALLENGE

When Growth Hits a Bottleneck

Like many lending businesses, this NBFC faced a fundamental tension: the ambition to grow faster, and the operational constraints that made scaling difficult without compromising credit quality.

01

Slow turnaround

Days-long credit assessment cycles limiting competitive positioning.

02

Manual assessment

Human-dependent processes creating inconsistency and bottlenecks at scale.

03

Credit quality under pressure

Growth ambitions compromising portfolio health and risk management.

04

Costlier growth

Rising customer acquisition costs eroding lending margins and profitability.

"How do you grow faster without compromising credit quality?"

THE SOLUTION

Smarter Scores. Sharper Decisions.

BORROWER DATAIFLOW AI SCORESCREDIT DECISIONOUTCOME
  • One unified view of the borrower
  • Consistent, model-driven decisions
  • Deeper risk insights from multiple data sources
  • Faster assessment at scale
  • Real-time portfolio health monitoring
Alt DataBureauBank StmtGST
AI

Multiple borrower data points unified through iFLOW AI Scores for consistent, faster decisions

BEFORE VS AFTER

The Transformation

METRIC
BEFORE AI SCORES
WITH AI SCORES
SPEED
Days of manual review per application
•78% faster turnaround through AI-driven assessment
SCALE
Processing capacity limited by team size
•60% more applications processed without adding headcount
CREDIT QUALITY
Inconsistent decisions depending on analyst experience
•75% improvement in credit quality through consistent model-driven scoring
COST
High acquisition cost due to manual effort and rework
•38% reduction in customer acquisition cost
PORTFOLIO HEALTH
Reactive risk management, identified after defaults occurred
•Proactive portfolio monitoring with early warning signals

READY TO TRANSFORM?

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