Page 44 - CCFA Journal - Seventh Issue

机器学习 Machine Learning 加中金融

Talents with relevant skill sets are in high demand in fraud and AML analytics. First, working with ML models entails solid quantitative
skills (statistics, ML, data mining ) and programming skills (e.g., Python, SAS, SQL). Second, creativity and critical thinking are essential
for handling real-world complexities (e.g., working with incomplete data or poor data quality during model development). Third,
because multiple business teams contribute to fraud and AML daily operations, excellent communication skills are needed for smooth
and efficient collaboration among various stakeholders. Finally, deep business understanding is invaluable to the development and
management of models, interpretation of model results, and design of business strategies. A combination of several aforementioned
skills, if not all, may bring one competitive advantage in the job market. Do you want to join this adventure?

具有相关技能的人才在欺诈和反洗钱分析方面的需求量很大。首先，使用机器学习模型需要扎实的量化技能（统计、机器
学习、数据挖掘）和编程技能（例如 Python、SAS、SQL）。其次，创造力和批判性思维对于处理现实世界问题的复杂性至
关重要（例如，在模型开发过程中需要使用不完整的数据或较差质量的数据）。第三，由于多个业务团队共同为欺诈和反
洗钱日常运营做出贡献，因此需要出色的沟通技巧才能在各个利益相关者之间进行顺畅高效的协作。最后，深入的业务理
解对于模型的开发和管理、模型结果的解释以及业务战略的设计都是非常宝贵的。上述几种技能的组合或者全部几项技能
可能会在就业市场上带来竞争优势。你想加入这场探险吗？

免责声明

本文所表达的意见是作者本人的意见。它们并不意味着反映了作者的雇主意见或观点。本文章的中文翻译是由 CCFA 义工
Gracie Huang 提供的。
References

[1] K. P. Murphy, Machine Learning: a Probabilistic Perspective, Cambridge, Massachusetts: MIT Press, 2012.

[2] B. Baesens, V. Van Vlasselaer and W. Verbeke, Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques:
A Guide to Data Science for Fraud Detection, Hoboken, New Jersey: Wiley, 2015.

[3] K. Sullivan, Anti-Money Laundering in a Nutshell: Awareness and Compliance for Financial Personnel and Business Managers,
Berkeley, California: Apress, 2015.

[4] The Insight Partners, "Fraud Detection and Prevention Market Forecast to 2028," The Insight Partners, December 2021.
[Online]. Available: https://www.theinsightpartners.com/reports/fraud-detection-and-prevention-market/. [Accessed 9 April 2022].

[5] Global Market Insights, Inc, "Anti-Money Laundering Market to hit $5 BN by 2027," GlobeNewswire, September 2021.
[Online]. Available: https://www.globenewswire.com/news-release/2021/09/07/2292387/0/en/Anti-Money-Laundering-Market-to-
hit-5-BN-by-2027-Global-Market-Insights-Inc.html. [Accessed 9 April 2022].
[6] Card Not Present, "Fraud is Major Driver of AI Adoption in Business," Reed Exhibitions, 6 February 2020. [Online]. Available:
https://news.cardnotpresent.com/news/fraud-is-major-driver-of-ai-adoption-in-business. [Accessed 9 April 2022].

[7] KPMG and SAS, "Acceleration through adversity: The state of AI and machine learning adoption in anti-money laundering
compliance," June 2021. [Online]. Available: https://www.sas.com/content/dam/SAS/documents/briefs/third-party/en/acceleration-
through-adversity-112221.pdf. [Accessed 9 April 2022].

[8] T. Brewster, "Fraudsters Cloned Company Director’s Voice In $35 Million Bank Heist, Police Find," Forbes, 14 October 2021.
[Online]. Available: https://www.forbes.com/sites/thomasbrewster/2021/10/14/huge-bank-fraud-uses-deep-fake-voice-tech-to-
steal-millions/?sh=1276fccb7559. [Accessed 9 April 2022].

CCFA JOURNAL OF FINANCE May 2022
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