SUCCESS STORY
How Deem reversed rejection rates with high accuracy with creditX
Increasing Credit Card Approvals with Higher Accuracy
A digital fintech in the Middle East provisioning credit cards.
Client: Deem
Company Size: 500 Employees
Country: Middle East
Type: Digital Fintech
Results after 3 months
<1 week
to develop and deploy new credit models
8%
Increase in Approvals which reversed rejection rates
The Challenge
A digital fintech in the Middle East provisioning credit cards was struggling to reverse rejection rates and was suffering from high first month default rates. Credit Bureau information was limited for their target segment of blue-collar workers leading to low accuracy of their credit models
The Solution — creditX
- Ensemble ML application models
- Bias reduction techniques implemented
- Incorporated both existing customer data and bureau data where available
- Deployment completed in less than 4 weeks
How creditX enabled Deem to increase revenue
20pnts
Increase in GINI Accuracy and enabled more lending
<1 week
to develop and deploy new credit models
8%
Increase in Approvals which reversed rejection rates
5%
Drop in gross credit losses
Increase in Overall revenue
Deem was able to lend more confidently which increased revenue. This eliminated frustration and time weighing risk Deem was able to lend more confidently which increased revenue.
Reduced Operating cost
Deem was able to to develop and deploy new credit models. Deem was able to to develop and deploy new credit models. Deem was able to to develop and deploy new credit models
“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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FINTECT
How Deem reversed rejection rates with high accuracy with creditX
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How Deem reversed rejection rates with high accuracy with creditX
RISK
How Deem reversed rejection rates with high accuracy with creditX
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