Banking Credit Application Intelligence

It is widely recognized that credit application scoring is a popular use case of AI in the banking sector. Risk managers can accurately evaluate default risks by utilizing numerous detailed factors and AI algorithms, such as deep learning. Compared to traditional methods like rule-based scorecards and statistical scoring models, AI has demonstrated its potential for higher accuracy in predicting default probabilities.

< AI Model vs Business Decisions >

However, credit scoring constitutes only a small portion of the overall loan risk management process. Many decision-making areas remain, such as cut-offs, credit limits, interest rates, and profitability-based fine-tuning, that are not covered by AI models. Furthermore, as the business environment evolves, all decision areas need to be adjusted in a timely manner. Unforeseen events like pandemics, climate change, and wars underscore the necessity for a responsive and resilient decision-making process.

AI alone cannot manage these complex decision-making processes and unexpected circumstances, as it relies on data derived from past experiences. Here are four challenges most frequently addressed by lenders:

1) Cut-off Strategies: Difficulty in setting optimal thresholds for approval and rejection decisions.

2) Adjustment of Approval Strategies: Identifying unforeseen risks and responding promptly.

3) Balancing Profitability and Risk: Fine-tuning strategies to realize potential profitability.

4) Reviewing Existing Rules: Evaluating and improving rules accumulated over a long period

DEIN Station’s Credit Application Intelligence enables lenders to establish their own credit evaluation process, which allows for broader and deeper analysis, simulation, optimization, monitoring, and updating of decisions. By combining AI and human intelligence, Credit Application Intelligence helps lenders identify and address unexpected circumstances, incorporating these events into their business operations. This solution not only accurately balances profitability and risk but also enhances timely responsiveness to unforeseen events.

Business KPIs 

∙ Total Loan Amount

∙ Approval Ratio 

∙ Profit 

∙ Default Rate 

∙ Default Amount

Challenges 

∙ Enhancing the profitability of the loan business 

∙ Assessing default or delinquency risks using application data 

∙ Simulating approval strategies including cut-offs, interest rates and credit limits 

∙ Monitoring and adjusting the approval strategies in a timely manner

Decision subjects 

∙ Cut-offs

∙ Interest Rates

∙ Loan Approval/Rejection by micro segment

∙ Credit Limits