600K
USD saved each year
The ML system yielded an estimated annual saving of over USD 600,000
8.6%
Revenue increase
ML accurately predicted potential loan defaulters, thereby increasing revenue
22%
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.
PROJECT SUMMARY
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.
CHALLENGES
SOLUTION
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Incident Response
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