When Netflix released Love Con Revenge, it quickly sparked conversation about the mechanics of modern scams. The series chronicles how ordinary people are manipulated into extraordinary situations: daily selfies, fake diplomas, fabricated investment opportunities, and promises of love that never existed.
To the fraud and risk community, this isn’t entertainment. It’s a case study in behavioral red flags.
On a recent episode of Good Question, Inscribe’s podcast about the future of fraud, AI, and trust, I spoke with Angela Diaz (Senior Principal of Operational Risk Management at Discover) and Michael Coomer (Director of Fraud Management at BHG Financial) about AI scams. What struck me was how closely their real-world experiences mirrored the patterns revealed in Love Con Revenge.
For banks and lenders, the documentary surfaces familiar challenges in a new light:
As Angela reminded us, the biggest danger is assuming AI scams require a brand-new playbook. “We can’t skip over our foundations,” she said. “We still need strong controls, layered models, and constant monitoring. AI should strengthen those, not replace them.”
Michael echoed the urgency, citing how quickly scam-related losses are climbing in the lending world: “Inaction is worse than friction.” For banks and lenders, that means reconsidering how they classify fraud, how quickly they act on behavioral changes, and how they balance customer experience with proactive intervention.
Love Con Revenge may be a cultural phenomenon, but for financial institutions it’s also a wake-up call. Behind every love story gone wrong is not just a “fraud vector” — it’s a person who has been manipulated, often at their most vulnerable. For fraud and risk leaders, the opportunity is not only to detect suspicious activity but to intervene in ways that protect people, preserve trust, and prevent life-altering losses.
Scammers may use AI to scale manipulation, but fraud fighters can use AI to scale protection. With stronger controls, sharper data analysis, and empathetic outreach, banks and lenders can turn insights from stories like Love Con Revenge into action — proving that technology and humanity together are more powerful than any scam.
For banks and lenders, romance scams don’t arrive in the form of fake love letters or doctored diplomas. They surface in data: subtle but telling behavioral shifts.
Angela Diaz of Discover explained it this way: “We can’t stop a customer from falling in love with a scammer. But we can prepare for what that looks like once it reaches us.” That means monitoring for unusual activity patterns such as:
These aren’t anomalies a human investigator can always catch in the moment, especially when teams are stretched thin. That’s where AI comes in. By ingesting years of transaction history and comparing millions of signals at once, AI can raise red flags earlier and with greater accuracy.
But Diaz also offered a warning: relying solely on AI tools without shoring up internal defenses is dangerous. Foundational controls (rules, alerts, models, and investigator training) remain the backbone of risk management. Only when those are strong does layering in AI or third-party solutions create meaningful protection. Otherwise, you risk plugging holes without fixing the foundation.
For institutions, the lesson is clear: treat romance scams not as fringe cases but as predictable behavioral disruptions. Build systems that look for those shifts, and empower investigators with both data and context to act fast.
At its core, Love Con Revenge isn’t just about deceit — it’s about manipulation at scale. Fraudsters exploit psychology as much as technology, and that’s where both consumers and institutions can learn.
As Michael put it: “Inaction is worse than friction.” Banks may fear slowing down a legitimate customer, but doing nothing carries high costs financially, reputationally, and personally.
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Brianna Valleskey is the Head of Marketing at Inscribe AI. A former journalist and longtime B2B marketing leader, Brianna is the creator and host of Good Question, where she brings together experts at the intersection of fraud, fintech, and AI. She’s passionate about making technical topics accessible and inspiring the next generation of risk leaders, and was named 2022 Experimental Marketer of the Year and one of the 2023 Top 50 Woman in Content. Prior to Inscribe, she served in marketing and leadership roles at Sendoso, Benzinga, and LevelEleven.
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