Srihari Govindarajan, Senior Director of Finance Transformation at PayPal, discusses how PayPal approaches fraud and policy abuse using generative AI. The episode explores the end-to-end process of a transaction in eCommerce, challenges of international fraud prevention, and the practical impact of leveraging generative AI. It also emphasizes the significance of data quality, governance, bias, fairness, trust, and transparency in AI initiatives.
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Quick takeaways
PayPal uses a bespoke version of GPT called fraud GPT to preemptively detect and mitigate potential fraud in multiple touch points of transactions.
Leaders must prioritize data quality and governance to ensure the success, trustworthiness, and fairness of AI initiatives in fighting fraud challenges.
Deep dives
Challenges of Finance Leadership Since COVID
The shift to digital due to the COVID pandemic has brought new challenges for finance leaders, including fraud and policy abuse. With multiple touch points in transactions, such as banks, payment processors, and user information, finance leaders need to ensure data security and a secure transaction process. They also need to handle bias and fairness when applying AI in transactions, especially with the increase in online purchases and different regulations internationally.
Preemptive Fraud Detection and Risk Toolkits
PayPal focuses on preemptively fighting fraud by using risk toolkits, including the use of a bespoke version of GPT called fraud GPT. This toolkit helps detect and mitigate potential fraud in multiple touch points, such as FX transactions and online purchases across different currencies. By applying risk layers to the data, PayPal can identify and prevent potential fraud, ensuring a secure environment for both merchants and consumers.
The Power of Data, AI, and Governance in Fraud Prevention
To address fraud challenges, leaders should leverage AI and data analytics, particularly in the form of generative AI. However, data quality and governance play a crucial role in the success of AI initiatives. Poor data governance can lead to breaches, regulatory non-compliance, and biased outcomes. Leaders need to ensure data quality, handle bias and fairness, and prioritize trust and transparency in their AI initiatives. Investing in data quality and governance reduces costs and improves the effectiveness and trustworthiness of AI models.
Today’s guest is Srihari Govindarajan, Senior Director of Finance Transformation at PayPal. Srihari joins Emerj CEO and Head of Research Daniel Faggella on today’s show to talk about how PayPal approaches fraud and policy abuse – including how they leverage a bespoke version of ChatGPT they refer to as “fraudGTP.” Throughout the episode, the pair scrutinize the concrete value of LLMs and other forms of generative AI in finserv workflows, specifically in mitigating fraud. This episode is sponsored by Riskified. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.
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