Money20/20: Key Takeaways

Money20/20 Las Vegas, the premier global fintech and payments conference, recently concluded with 35,000 financial leaders and industry experts gathering to explore the future of money, share insights on fraud prevention, and shape the next wave of financial innovation. 

This year’s event spotlighted hot topics like open banking, collaboration in combating financial crime, personalized fraud detection, and the transformative role of AI in customer service. 

If you missed the action, don’t worry. Here are the key Money20/20 takeaways you need to know to stay ahead of the year ahead.

US Open Banking: A Hot Topic, but What’s the Path Forward?

The financial services and payment industry has experienced a great deal of buzz around open banking in recent years. And especially recently, with the Consumer Financial Protection Bureau (CFPB) releasing its final rule on October 22, 2024, implementing section 1033 of the Dodd-Frank Act. The idea of easily sharing financial data to improve customer experiences when buying items on a mobile app or opening a new bank account or loan is an appealing prospect.  

However, open banking faces some significant hurdles in the US. Privacy and security are top concerns. Sharing sensitive customer information poses a delicate matter, and you cannot downplay the regulatory and reputational risks.

So, while there’s a clear desire to give consumers broader access to their financial data, banks (and consumers) are understandably cautious about taking the plunge. Meanwhile, changes in financial data rights could significantly impact open banking, adding another layer of complexity.

Financial Industry Collaboration: Cautious Interest

It’s not just open banking facing hesitation. There’s also a growing interest in a collaborative approach to fighting fraud—however, once again, the industry appears to be eying this strategy very carefully. 

One of the critical questions to address is how to manage competing priorities. Case in point, issuers and acquirers have distinct viewpoints on data sharing. Issuers are more keen to prioritize customer privacy to protect their cardholders and, therefore, are careful about exposing sensitive data. Acquirers, on the other hand, see value in broader data sharing to identify and combat fraud trends in order to protect their merchants.

While issuers focus on protecting customer data, acquirers argue that controlled data sharing could enhance security for all. However, the risk of data breaches and misuse remains a significant concern, particularly for issuers.

The idea of shared blacklists and fraud data pools is intriguing, but it’s a delicate balance. While it could provide valuable insights, privacy regulations, and potential liability risks pose significant challenges.

This uncertainty over how to responsibly collaborate can hinder progress. Smaller, newer players like digital banks and FinTech companies are eager to leverage shared intelligence. However, their lack of historical data and limited resources make navigating the complex landscape of fraud prevention difficult.

As the industry continues to grapple with these issues, it’s clear that finding the right balance between collaboration and privacy is essential. By fostering trust, addressing regulatory concerns, and developing forward-driven solutions, we can work towards a future where collaboration empowers us to combat fraud more effectively.

A Tailored Approach to Fraud Detection

If one thing is clear from Money20/20, it’s this: a one-size-fits-all approach to fraud prevention is no longer sufficient. It all depends on the type of business you’re considering. 

For example, retail fraud often deals with individual consumer behavior. Considerations such as spending limits, typical transaction times, and purchase history can be valuable clues.

Commercial fraud, on the other hand, is a more complicated matter. Corporate credit cards, for example, can exhibit wildly different spending patterns. One user might make a few high-value transactions a year, while another might use the card daily for smaller purchases.

To stay ahead of fraudsters, companies need to adapt their detection strategies. Profiling based on behavior allows us to tailor fraud models for each customer type. This personalized approach can significantly improve accuracy and response times.

Understanding the unique attributes of different types of fraud is essential to building more effective defenses.

AI: Your Customer Service Secret Weapon

Imagine a world where fraud detection doesn’t disrupt your customers’ experience. That’s the goal of many financial institutions. By leveraging real-time, AI-powered decisioning, they can reduce the number of false positives, striking a balance between security and customer satisfaction.

How does AI pull this off? By considering the context of each transaction. For example, if a customer is traveling to a new location, AI can factor geolocation metrics into the fraud assessment. This means fewer false alarms and smoother experiences for your customers.

By combining historical data with real-time transaction monitoring, AI systems can create unique, individual profiles for each customer and identify truly suspicious behavior. This allows legitimate customers to access their accounts without any unnecessary hurdles.

If there’s one thing Money20/20 Las Vegas demonstrated, it’s that the future of financial services lies at the intersection of innovation, collaboration, and adaptability. Navigating the collaboration path won’t be easy, but it will require balancing technological innovations with customer trust and regulatory compliance. 

Financial institutions can tackle today’s challenges and turn them into opportunities. They can do this by using tailored fraud prevention methods and AI strategically to enhance customer experiences. 

• Article: 10 Fraud Prevention Tips for Businesses
• Resource: How North American Banks Can Measure, Classify, and Prevent Scams
• Solution Sheet: Account Opening Fraud
• Solution Guide: Prevent and Detect Payments Fraud with Feedzai