With financial institutions (FIs) fortifying their defenses and evolving their strategies against digital payment fraud, criminals are turning to a new weak spot: the customers themselves.
Gone are the days of clunky phishing emails riddled with typos. Today’s fraudsters are using advanced social engineering scams to target consumers directly, leveraging fear, urgency and even fake customer service lines to dupe unsuspecting victims into handing over sensitive information.
The latest PYMNTS Intelligence in “The State of Fraud and Financial Crime in the U.S.” reveals that social engineering fraud has increased by 56% in the past year. While FIs have made strides in curbing traditional digital payment fraud, the escalating sophistication of scams highlights critical gaps in their defenses.
Unlike traditional digital payment fraud — which saw a significant decline in its share of dollar losses, dropping by 57% in 2024 — social engineering scams exploit human psychology rather than technological loopholes. Fraudsters now rely on “customer-centric” tactics, leveraging trust to bypass the robust security systems FIs have built around digital payments.
This shift underscores the need for FIs to continuously adapt their fraud prevention strategies and prioritize customer education to mitigate the growing threat of social engineering scams.
Read more: Financial Scams Drive 122% Increase in Fraud Losses by US Banks
The decline in digital payment fraud is a testament to the effectiveness of advanced security measures, such as transaction alerts and device fingerprinting. Yet, combating social engineering scams requires a different approach.
A PYMNTS Intelligence report, “The Impact of Financial Scams on Consumers’ Finances and Banking Habits,” a collaboration with Featurespace, revealed that financial scams are widespread, affecting 3 in 10 U.S. consumers in the past five years. Scams damage consumer trust in FIs. Over half of victims consider switching FIs, and 30% actually do.
The sad reality is that the true incidence of scams is likely higher than what’s being reported, due to embarrassment and perceived futility of reporting. Sixty-five percent of victims blame themselves for falling victim to fraud.
But against that backdrop, the same PYMNTS Intelligence data shows that victims prioritize advanced fraud detection and monitoring technologies as the most important safeguards financial institutions can implement. Behavioral analytics — an emerging technology that analyzes patterns in user behavior to detect anomalies — has proven particularly adept at identifying scams that exploit human targets.
“[End-users] often don’t have a lot of time to look at a particular message. It becomes harder to understand of it’s a ‘real’ message or one that’s trying to deceive us,” David Excell, founder of Featurespace, told PYMNTS, highlighting the role that technology can play in preventing fraud before the bad actor can stick their foot in the front door.
However, a striking 83% of FIs cite budgetary constraints as a barrier to implementing new anti-fraud technologies or enhancing existing ones. While the cost of innovation remains a challenge, FIs must weigh these expenses against the financial and reputational risks of inaction.
Read more: Why the Customer Experience Should Drive Fraud Prevention Strategies
Forget the stereotype of elderly victims falling prey to smooth-talking fraudsters. Today, it’s the digital-savvy millennials and Gen Z consumers who are more likely to take the hit, per PYMNTS Intelligence. These generations, often perceived as tech-literate, are still frequent targets for scams like identity theft, fake eCommerce schemes and investment fraud, which can deliver devastating financial blows.
Scammers do more than deceive their targets. These criminals contribute to undermining trust and confidence in FIs, online transactions and the financial system as a whole.
Financial institutions sit at the front lines of this battle and have an opportunity — if not an obligation — to take a stand. From advanced fraud detection technologies to streamlined reporting processes, FIs can empower consumers with tools to detect, report and recover from scams.
The fight against fraud is a dynamic and high-stakes battle. As fraudsters continue to refine their strategies, FIs must demonstrate equal agility by embracing innovation and prioritizing customer protection. Institutions that fail to adapt risk not only financial losses but also erosion of customer trust — a critical component of their long-term success.
Agentic artificial intelligence (AI) promises to improve operational efficiencies and the customer experience offered by enterprises.
The advanced technology is finding applications in loan underwriting and fraud detection, and now it’s moving across borders.
TerraPay Co-Founder and Chief Operating Officer Ram Sundaram told PYMNTS as part of the “What’s Next in Payments” series focused on exploring AI’s use in banking and by FinTechs that automated decision making and streamlined processes will continue to transform global money movement, especially as faster payments gain ground in cross-border transactions. That’s the inexorable trend, but as Sundaram put it, there’s still room, and a necessity, to have some human interaction in the mix.
In terms of global fund flows, TerraPay’s single connection ties more than 3.7 billion mobile wallets together across 200 sending and 144 receiving countries, touching 7.5 billion bank accounts. As one might imagine, coordinating and enabling the transactions is complex.
“Obviously, in the best-case scenario, everything goes smoothly, but when things are not going smoothly, that’s when the customer queries come in,” Sundaram said.
It’s no easy task to find out straight away where a transaction is, as analysts and representatives at the company have to look at logs and query partner systems.
“A lot of that work is done manually,” said Sundaram, who added that the agents “know the corridors and the markets that they are working in, but it still takes some time.”
TerraPay is using AI models with machine learning to bolster customer support and automate tasks as financial institutions (TerraPay’s client base) send payments in real time, and those payments are processed into local markets’ beneficiary banks.
“We still don’t trust [AI models] to let them respond to the customer straight away, but we can do the analysis, and then that gets reviewed by an agent who decides if [information] is accurate or not and then sends it off,” Sundaram said.
The same principles are guiding AI models and company practices to improve technical and security operations, analyzing and categorizing anomalous transactions and automating integrations with partner firms.
“Compliance is an issue where there is a lot of review needed of the alerts, and we are using [AI models] to speed up those processes,” Sundaram said.
Asked by PYMNTS about how agentic AI can be harnessed, he said: “In financial services, you can’t take chances on technology like this, which has the freedom to go wrong. You have to be careful about making sure that it’s 100% reliable before we can let things run entirely by automation.”
Agentic AI also remains pricey. For example, OpenAI is charging $20,000 a month for its specialized agents. However, Sundaram said the industry will become commoditized quickly, which will lower prices, and some open-source offerings are capable.
“There’s a fire hose of news about breakthroughs and new ideas and new ways of doing things that are coming out on a daily basis,” he said.
Data underpins it all, and Sundaram told PYMNTS that no matter what the application, the information fed into the models must be clean. Most organizations have a range of data sitting in different intra-company silos, and those silos need to come down.
In addition, the data must be structured so that it is accessible and can be synthesized by the models. Many firms may have more than 1,000 software-as-a-service (SaaS) resources to which they are subscribed but are not accurately tracked or monitored.
“Every database is separated, each one sitting somewhere else,” he said.
The days of stitching together those separate SaaS offerings to run an enterprise are ending, he said, and we’re headed to a future when data is collected in one place.
AI models and agentic AI “are extensions of what we’ve always valued at TerraPay, which means building the most efficient infrastructure possible in order to make sure that transactions are processed safely, quickly and affordably,” Sundaram told PYMNTS. “We see AI and [AI models] as powerful tools that help us scale all this very quickly while making sure we build more and more efficiency into the system.”
