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Feuji Enabled an Auto Loan Company With a Data Analytics Machine Learning Model to Predict Defaulters


USD saved each year

The ML system yielded an estimated annual saving of over USD 600,000


Revenue increase

ML accurately predicted potential loan defaulters, thereby increasing revenue


Effort reduction

The time, effort, and resources needed to pursue loan defaulters saw a significant reduction

The US-based auto loan company generated revenues exceeding USD 140 million. Nevertheless, they faced challenges with a department tasked with contacting loan defaulters, even resorting to in-person visits for collections. Success in these efforts was rare.

The client is a $20 billion IT giant with operations across the world providing mission-critical IT services. With operations in 70 countries globally, the client drives innovation in the IT world. The client has over 130,000 employees across the world and is a Fortune 500 global IT services leader.


Understanding the challenge, we collaborated with internal teams to identify patterns among loan defaulters. Employing advanced machine learning systems and conducting thorough data analytics, we developed a model to predict customers' likelihood of default.


  • Complexity in identifying defaulting loans: The key challenge was the difficulty in identifying loans at risk of default. 

  • Uncertainty in identifying default-prone customers: Identifying customers prone to loan default presented a challenging task. 

  • Escalating operations with increasing defaulters: The growing number of defaulters led to an escalation in operational demands. 

  • Revenue drain in pursuing defaulters: Substantial revenue was invested in pursuing defaulters through various means. 


Through machine learning, we achieved the following:

  • Developed a model capable of predicting potential loan defaulters 

  • Implemented an ML system that provided weekly predictions and fine-tuned itself over time 

  • Assessed data, including loan history, payment history, emails, and calls 

Download the case study to know more about the benefits we delivered, and how we executed this project





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