Day 1 of Money20/20: Generative AI dominated conversations early in the conference, which is unsurprising given that it is the hottest payment trend of the year.
Here’s what we heard on stage and one-on-one with industry leaders about the future of genAI and how payments providers should respond.
Are we at the dawn of a utopian or dystopian revolution?
- Generative AI can bring a lot of good to the world, IPG Sheila Colclasure, Head of Digital Responsibility, said during a session on preparing for a revolution in AI and emerging technologies. In financial services, for example, it can de-risk the banking sector by reporting credit more accurately.
- Across all sectors, this can boost productivity, competition and economic growth. More utopian visions of AI also involve solving problems such as disease, climate change and poverty.
- But there is also a dark side to genAI. Technology can discriminate, hallucinate, and make biased decisions. Copyright and intellectual property rights are also not resolved.
- This technology could usher in a “post-truth” world, Colclasure warned. Deepfakes created by GenAI proliferate and become almost undetectable. This can make it difficult to trust anything beyond person-to-person interactions.
There is, of course, a broad middle ground between the improbable extremes of utopia and dystopia. But to find a healthy approach to AI, early action from governments, businesses and other leaders will be vital.
How can financial institutions prepare?
- Companies need to set the tone at the top, according to Andrew Reiskind, chief data officer at MasterCard. Leaders must put safeguards in place that align with their corporate responsibility programs.
- Once these are in place, different parts of the organization can learn how to operationalize genAI – this needs to be a multi-stakeholder effort.
And after? AI needs human expertise and oversight, Heidi Hunter, chief product officer at GBG Americasargued in another panel.
Some present genAI as a magic key capable of solving all challenges, but the reality is far from the same. Technology itself needs advancement and it must eliminate bias and discriminatory practices. Right now, Hunter said, genAI is only as good as what you put into it.
Mastercard’s AI approach: Insider Intelligence caught up with Mastercard’s Reiskind after his panel to get more insight into Mastercard’s AI strategy.
Democratization of AI: Mastercard has used AI for more than 10 years, Reiskind said.
- It uses AI to fight fraud and extrapolate insights from data.
- Mastercard also uses genAI to create fake data to test anti-fraud solutions.
- But what has changed over the past year, according to Reiskind, is the democratization of AI capabilities. Everyone has access to it. And skills like coding become less essential because AI can do it.
Now, extracting insights from AI data is the real skill humans need. And using AI is an efficiency play that can help businesses focus on creating better products.
Top use cases for genAI in payments: Fraud prevention is the most valuable genAI use case for Mastercard, Reiskind said. It can complement existing anti-fraud tools to more quickly identify suspicious behavior and flag potentially fraudulent transactions for further investigation.
Other payment players will say that personalization is the primary use case, Reiskind noted, particularly in the commerce experience. It can create product recommendations, promotions and payment options tailored to customer preferences and behaviors. This can improve customer satisfaction and loyalty, thereby increasing conversion rates.
