600K
USD saved each year
The estimated positive impact each year the ML system we created was over USD 600,000
8.6%
Revenue increase
The ML was able to accurately predict possible loan defaulters, thereby increasing revenue
22%
Effort reduction
The effort, time and money required to pursue loan defaulters dramatically reduced
The auto loan company based out of the US possessed revenues exceeding USD 140 Million. However, they had to work with a department that tried to call up loan defaulters and even having to visit them to get them to pay up. Seldom did they succeed
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
Having understood the challenge, we worked with the internal teams to see if they could identify a pattern among loan defaulters. Using advanced machine learning systems, and performing vigorous data, analytics and insights, we built a model that could predict customers who are likely to default
CHALLENGES
The key challenge in this case was the complexity to get the defaulting loan
The client could not identify which customers are likely to default on loans
With increasing defaulter, there had to be increasing operations
Revenue was poured into pursuing defaulters through various means
SOLUTION
Through machine learning, we were able to
Build a model that was able to predict possible loan defaulters
The ML system made weekly predictions and fine-tuned itself
Data we assessed included 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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