Data and Machine Learning in Financial Fraud Prevention

Presented by

Kayla Hartman, Data Analyst, Alloy

About this talk

According to Capgemini’s World Payments Report 2017, global digital payments are expected to rise to roughly 726 billion transactions in 2020. The growth of digital financial services offers innumerable opportunities, expanding access to financial services products and allowing for essentially instantaneous feedback loops. With these opportunities, however, also come risks, including fraud. The threat of fraud requires financial services organizations to act proactively to minimize losses due to fraud. Analysis of data surrounding their customers and transactions is an essential effort to ensure the benefits of the digital payments space continue to outweigh the risks. In this webinar, Kayla Hartman will discuss the various ways data is used in fraud prevention. As a Data Analyst at Alloy, a fintech company that provides identity verification APIs for clients’ KYC (know your customer) and AML (anti-money laundering), she has firsthand experience in enhancing fraud prevention efforts through data analysis. She will dive into the ways the use of data is currently advantageous to fraud prevention, as well as the challenges that are presented in this quickly changing space.

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