How Synchrony Financial Is Upgrading Its AML Strategy

Money laundering has always troubled financial institutions, but today’s digital banking system creates additional complexities as fraudsters around the world take advantage of financial technologies to launder approximately $2 trillion annually. Banks are scrambling to match cybercriminals’ pace, and some are adapting quicker than others.

Five Dutch banks recently formed a group to protect their systems against money launderers, but only after three of them shook off fines and anti-money laundering (AML) strategy investigations. Member ING Bank was fined 775 million euros ($852 million USD) in 2018 for failing to prevent criminals from siphoning millions of euros through it over a six-year period, for example.

Financial institutions (FIs) worldwide are innovating their AML strategies to protect against similar events, but the process requires more than simply adding security to their online platforms. Legitimate customers have expectations that banks must meet, meaning FIs must walk fine lines between providing speed and AML security, according to Michael Bopp, executive vice president and chief customer engagement officer for Synchrony Financial.

Bopp recently spoke with PYMNTS about how AML expectations are changing and how Synchrony has developed customer engagement and cybersecurity protocols to address all aspects of money laundering.

“Consumers want speed and personalization, but they don’t want to sacrifice security,” he said. “Because the online environment continues to evolve at a fast pace, our AML strategies need to be fluid to keep up with the increased functionality and continual evolution of technology our customers expect and deserve.”

AML Strategies and Innovation Quirks

Strong relationships with regulators have always been key to developing anti-crime strategies, especially as security needs evolve. Synchrony has configured its information security controls to align with Financial Services Sector Cybersecurity Profile framework developed by the National Institute of Standards and Technology (NIST), Bopp said. Such profiles ensure FIs comply with current regulations and AML standards.

Matching regulations is only part of the AML puzzle, as modern FIs must protect many channels from cybercriminals, even though balancing security needs with prickly customers’ personalization demands is not a new problem for banks. Mobile, online and phone channels all have distinct fraud challenges and customer needs, after all.

“We believe that consumer choice is paramount, and that extends to information security,” Bopp said. “We offer the ability to log into online and mobile banking services using face ID and fingerprint ID. Of course, if people prefer typing passwords, they can do that instead.”

Banks also need to match fraudsters’ technologies if they want to defend their platforms. Artificial intelligence (AI) and machine learning (ML) are popular tools for both, used by FIs to determine how legitimate consumers behave and by bad actors to mimic those behaviors. Bopp said this competition makes gaining a more intuitive grasp of customers’ behaviors critical to banks’ AML strategies.

“If we have a better understanding of how our customers use our cards for their everyday needs, then we can direct our AML strategies and activities accordingly,” he explained.

Such technologies become more sophisticated every year, and FIs must carefully adapt to prevent launderers from slipping into their platforms.

This is also why banks need to shift how they think about utilizing AI and data, Bopp added. FIs must tap into their vast amounts of data to protect customers and innovate AML efforts, but they should carefully approach such innovation to best serve their customers.

“There [are] a tremendous [number] of AI and ML tools, but it’s the combination of these technologies that becomes powerful,” Bopp said.

Changing AML with AI and ML

Synchrony continues to innovate its AML approach, experimenting with ML technology to provide greater speed to customers and using AI to offer stronger personalization.

“Enabling ML solutions containing fraud detection features to work in tandem with our credit solutions helps protect our more than 80 million active customers,” Bopp stated. “We’re scaling ML models to identify fraud patterns to combat and prevent coordinated fraud networks at twice the speed.”

Banks will need to make sure they can continue this speedy innovation as cybercriminals develop more sophisticated technologies. Preventing money laundering will be an ongoing battle for FIs that will always require further innovations, and banks must be certain they are prioritizing customers as they fight cybercrime.