| Fraud Detection in Financial Institutions: From classical approaches to AI/ML-based approaches |
| کد مقاله : 1040-FEMATH7 |
| نویسندگان |
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Hassan Omidi Firouzi * JP Morgan Chase & Co., Houston, Texas, USA |
| چکیده مقاله |
| Fraudsters have been challenging financial institutions (FIs) in various forms and through different channels. With the rise of new emerging technologies, they constantly changing their behaviors which makes it very complicated for FIs to warn, predict and detect these behaviors. For a fair amount of time FIs have leveraged binary rule-based approaches to detect and monitor suspicious behaviors; however, these techniques are not the optimal solution in the area of the emerging technologies and FIs need to hone their skills to combat fraudulent attempts. In this talk, we'll shed some light on the advanced methodologies and technologies FIs are exploring to fight against fraudsters. The opportunities and challenges of these techniques will be discussed. |
| کلیدواژه ها |
| Fraud Detection, Artificial Intelligence (AI), Banking, Class Imbalance, Risk Management |
| وضعیت: پذیرفته شده برای ارائه شفاهی |