Optimized Collection Efforts
Improve Collections
and Optimize Efforts
The Challenge
About the Company
- One of India’s largest NBFC Companies offering loans
- Offering flexible Loan products with innovative repayment plans
- 25,000+ customers
- USD 55+ cr loan disbursed
- ~ 20 lending partners
The Solution
iTuring.ai’s iTuring can be used to develop predictive models that identify customer default early in their lending journey. It can accurately forecast delinquency movement for the whole portfolio, across all customers and all buckets. The outputs of the default prediction models and their explanations around customer behavior can help define strategies to improve overall collection efforts and as a result improve portfolio.
The FinTech company we engaged with on Collection optimization was experiencing a default rate of ~12%. We used iTuring be build predictive models that predicted customer movements from one delinquency bucket to the next for pre-delinquency, early stage, late stage and recovery. iTuring developed accurate models which predicted default in the immediate next month with an accuracy of ~86%, enabling business to effectively manage portfolio monthly. This enabled the company to identify 9 customer segments based on probability of default and value at risk and develop collection strategies around the same.
By focusing efforts on 72% of likely defaulters that were identified in the top 30% customers the company would improve collections by 116%.
Highlights
- 116% increase in collections by targeting the right customers with the same amount of collection effort
- 9 customer segments based on likelihood of default and value at risk identified
- 72% of likely defaulters identified in the top 30% customers
- 86% model predictive accuracy
- Models trained on 12 months cohort data across several data tables
- Model validated on next 6 months cohorts and maintained consistency and accuracy over time
Impact
Collections
Time to Deployment
Accuracy
Why iTuring.ai
Not only does iTuring provide highly accurate predictions of which customers are likely to default, it also enables you to identify key customer segments for optimized collection strategies. This allows collections team to focus on the customers based on their likelihood of default, value at risk and probability of repayment, thereby improving overall debt collection.
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