Economics · Banking and Technology
A neo-digital bank in India rejects Ms. Sneha's loan application based on an AI-driven scoring model that penalizes her for using fantasy sports apps, having 'low balance' alerts (due to immediate sweeping of salary into high-yield investments), and visiting luxury stores without high spending. However, her traditional credit bureau (CIBIL) score is solid at 720. Based on prudent risk management and current regulatory expectations regarding fair lending and algorithmic transparency, what is the most appropriate approach for the bank?
- 1Delete the AI model entirely as it is causing too many complaints and go back to using only physical document verification.
- 2Implement a 'Human-in-the-Loop' review for such discrepancy cases, allowing the customer to provide proof of investments to counter the 'Low Balance' signals, and refine the AI's feature weights to distinguish between casual fantasy sports and high-risk gambling.✓
- 3Stick to the rejection because the AI model identified 'behavioral' risks that traditional bureau data (which is backward-looking) cannot capture, even if those behaviors have a logical explanation.
- 4Override the AI score and grant the loan because Sneha's CIBIL score is 720 and traditional bureau data should always take precedence over experimental AI data.
Correct answer
Implement a 'Human-in-the-Loop' review for such discrepancy cases, allowing the customer to provide proof of investments to counter the 'Low Balance' signals, and refine the AI's feature weights to distinguish between casual fantasy sports and high-risk gambling.
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