Love Con Revenge: What fraud leaders can learn from Netflix’s romance scam docuseries

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:

• The disguise of legitimacy. Fraudsters aren’t only sending poorly Photoshopped documents anymore; they’re producing diplomas, credentials, and financial records convincing enough to fool untrained eyes or even investigators under pressure.
• Behavioral anomalies. What looks like romance in a living room translates into unusual wires, transfers, and account activity inside a core banking system. These signals are subtle but detectable (if institutions know what to look for).
• Scams outside the perimeter. Many tactics unfold long before a customer interacts with their bank or fintech. By the time money moves, it can appear authorized. That’s why institutions must focus less on preventing the relationship and more on recognizing when that relationship starts driving financial risk.

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.

Signs of pig butchering and romance fraud to watch out for

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:

• A customer who’s had an account for years suddenly wiring money for the very first time.
• Transfers that start small but climb steadily in value each week.
• A flurry of daily transactions that seem routine on the surface, but deviate sharply from past behavior.

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.

Lessons fraud leaders can take From Love Con Revenge

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.

• For consumers: Awareness is a form of armor. Documentaries like this show how scammers prey on deeply human needs (love, companionship, trust) and how easily red flags can be ignored when emotions run high. Normalizing this conversation reduces stigma and empowers people to pause, verify, and protect themselves before sending money or personal details.
• For banks and lenders: The job is bigger than just blocking suspicious transactions. As Michael, institutions must be willing to challenge old assumptions, like treating first-party fraudsters as “customers.” Empathy doesn’t mean letting scams slide; it means building systems that recognize victims, detect early warning signs, and intervene before losses spiral. Classifying scams as fraud, tracking them rigorously, and using AI to catch subtle changes in behavior isn’t optional anymore; it’s the baseline.
• For everyone: Fraud is not just financial. It’s human. Behind every fake bank statement or wire transfer is someone being manipulated, sometimes on both ends, from victims losing money to trafficked workers forced into scam operations abroad. Human-centered solutions, built on empathy and accountability, are the only way forward.

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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