Credit Risk Scoring

Predict loan repayment and default rates on new inbound customers.

Finance
Marketing
Operations
100,000

rows of data

5 days

time to value

79.2%

prediction accuracy

7%

decreased defaults

Background

Obviously AI can be used to estimate default probability, loss severity, and for loss forecasting, using past client behavior data. These predictions improve pricing for risk, credit approval, and portfolio management. Obviously AI also automatically updates, making credit scoring more precise as models learn the nuances of discrete populations.


A micro lending company in India wanted to predict which customers are most likely to pay back micro-loans on time and what is the best amount to offer to them. They used to do this by hand keeping a track of each individual person but certainly had trouble doing it at scale. An internal data science team was out of reach, so they turned to Obviously AI.

The Solution

With Obviously AI, the company instantly connected their historical data consisting of inputs like demographics, employment data, who they banked with, and overall, a historical data of loans given to these customers in the past and if they paid them back on time, delayed or defaulted.


In just minutes, they had fully trained an AI model that can proactively predict loan defaults and provide preemptive strategy by demographics, time, product engagement, etc. These predictions were then fed directly into their CRM systems in real time!

The Results

Obviously AI was able to identify 83% new customers that are likely to default and increased their internal efficiency building models by 10x, enabling the business team to build AI predictions without onboarding Ph.D. AI engineers.

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