A thin-file lender drives profitability by improving credit risk model accuracy by 20 GINI points

8% credit increased
5% credit decreased

Country

United Arab Emirates

Company Size

500 – 1,000 Employees

Products

Credit Cards

Type

Fintech, Retail Lending

The Challenge

A digital lender in the Middle East was struggling to reverse high rejection rates and high first month default rates. Credit Bureau information was limited for their target segment of blue-collar workers, resulting in low accuracy credit risk models, which took 6 months to develop and deploy.

The Results

Increase in GINI accuracy

+20 pts

Processing time per application

< 1 week

Increase in approval rates

+8%

Reduction in loss rates

-5%

High Return of Investment
Within 2 months of using creditX, our customer gained an ROI of 17X and increased profitability resulting from the combination of more loans disbursed and lower loss rates.
Higher Operating Efficiency
The end-to-end process of developing and deploying credit models used to take 6 months and involved a team of 8 persons. It is now managed by 2 persons and takes less than a week to complete, allowing the team to focus on other value-adding projects.

The Solution

Ensemble ML algorithms for higher predictive accuracy
Full automated solution seamlessly connected to Lender’s data warehouse and LOS system
Ability to create credit models for thin-file customers using historical data
Implementation completed in 12 weeks

Results after 3 months

<1 week

to develop and deploy new credit models

8%

Increase in Approvals which reversed rejection rates

“A game-changer”

finbots.ai’s solution, creditX, is a game changer in credit modelling that supports our Bank’s digital transformation journey.

– Ti Eng Hui, CEO, Baiduri Bank

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Let us show you how finbots creditX can help your lending business with a no-obligation call and demo.

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Let us show you how fnbots creditX can help your lending business with a no-obligation call and demo

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