Authors: Shuochen Bi, Wenqing Bao

Published on: April 28, 2024

Impact Score: 7.8

Arxiv code: Arxiv:2404.18183

Summary

• What is new: Innovative application of AI for credit risk management in banks, integrating deep learning and big data for accurate credit evaluations and real-time risk monitoring.
• Why this is important: The need for improved credit risk management in banks to ensure stability and safety of asset quality.
• What the research proposes: Implementing AI technology, particularly deep learning and big data analysis, to enhance the accuracy and comprehensiveness of credit risk assessments and decision-making.
• Results: AI-enabled systems provide precise evaluation of borrowers’ credit status, identify potential risks earlier, and support banks with timely and effective decision-making tools.

Technical Details

Technological frameworks used: Deep learning, big data analytics

Models used: Not specified

Data used: Borrowers’ credit data, transaction histories, financial statements

Potential Impact

Commercial banking sector, credit risk assessment services, financial technology firms

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