Good Question

Is AI-generated document fraud actually increasing, or does it just feel that way? The data says yes: a 4X jump in just 11 months. In this episode of Good Question, Inscribe co-founder and CEO Ronan Burke sits down with Jessica from Inscribe's Risk Operations team to unpack what's driving the surge and how fraud teams can catch it.They cover:
What AI-generated bank statements and payslips actually look like, and the formatting tells that give them away
Why bank statements remain the top target for AI-generated fraud
The difference between AI-generated documents and AI-edited real documents, and why edited documents are harder to catch
How tools like FraudGPT remove the guardrails found in mainstream AI models
Whether AI-generated fraud can be detected using AI, with a real example from Inscribe's risk team
What lending teams should be doing right now to prepare for this threat
Jessica also explains why the barrier to committing fraud has dropped so low that even previously trustworthy customers may be tempted to try it, and what that means for underwriting and onboarding teams going forward.Inscribe helps banks, credit unions, lenders, and fintechs detect fraudulent documents and verify applicant information at scale. Learn more at inscribe.ai.

Miguel Navarro (KeyBank) and Angela Diaz (Senior Risk Manager, external fraud oversight) on where fraud teams are actually falling behind on AI, and what it costs them.

They cover:
Why reading about AI isn't the same as using it, and where to start
How deepfake scams work outside the bank's visibility — and why that makes them so hard to catch
The difference between managing risk and avoiding it
Why collaboration is the most underrated fraud strategy in financial services
How to build an AI governance framework that lets your institution move with confidence

Today is the worst AI will ever be. The teams that treat that as a reason to wait are going to have a hard time catching up.

Fraud Fight Club is an independent fraud prevention community. This episode is sponsored by Inscribe, the AI platform banks and fintechs use to detect document fraud and verify income at scale. Learn more at inscribe.ai.

Frank McKenna and Marc Evans come at fraud from opposite ends -- data and the street -- and land in the same place.
Description (both platforms):Frank McKenna is Chief Fraud Strategist at Point Predictive and author of the Frank on Fraud blog. Marc Evans is a detective, Certified Fraud Examiner, and founder of Fraud Hero, with 14 years in law enforcement. They approach fraud from completely different vantage points -- Frank from the data side, Marc from the street level -- and keep arriving at the same conclusion: the human element is what holds it all together.
Recorded live at Fraud Fight Club Round 3, this conversation covers the first-party fraud misclassification problem (Frank's estimate: up to 70% of early payment defaults in auto lending contain fraud that never gets called fraud), what generative AI actually means for fraud teams, and why Marc keeps coming back to the same point: fraud is not just a tech problem. It's a human problem.
Frank's hot take: AI will create more fraud analyst jobs, not fewer. More coverage, more complexity, more demand. Marc's angle is complementary: technology evolves on both sides, but knowledge and education are durable in a way that any specific tool is not.
Topics covered:
Will AI replace fraud analysts?
First-party fraud and early payment default misclassification
Generative AI and the future of fraud operations
Real-time intelligence sharing between lenders and law enforcement
What makes a fraud determination hold up in court

Freddy Massimi is a Fraud Analytics Analyst at Live Oak Bank, a certified human trafficking investigator, and a fraud professional who has spent his career following financial patterns to their human consequences.

In this conversation from Fraud Fight Club Round 3, Freddy traces his path from third-shift debit card fraud at BB&T to elder abuse investigations, human trafficking certification, and now AI-powered document fraud detection. He talks about what the link between financial crime and human exploitation actually looks like in the data — and why fraud teams that understand that connection are better equipped across the board.

He also shares a case that changed how he thinks about the job: a pig butchering victim who told him she was planning to end her life. "Trust your gut. Treat every customer like your grandparent."
On the technology side: Freddy uses Inscribe at Live Oak Bank to detect AI-generated documents. He's seen the forgery market firsthand — pay stubs available for $10, IDs that pass visual inspection, documents generated by AI tools that leave almost no trace for human reviewers.

Topics covered:
AI-generated document fraud and detection
Pig butchering scams and investment fraud
Human trafficking and financial crime
Elder abuse and fraud victim support
Fraud analytics at community banks

Tracy Hall lost over $300,000 to a romance scammer. For the first two years, shame kept her silent — the same shame that keeps most victims from coming forward.
She's now an author, speaker, and fraud victim advocate. She co-authored a language guide with the Australian government to change how fraud is reported in the media. One of the nine principles: never say a victim "lost" money. Money was stolen.
At Fraud Fight Club Round 3, Tracy talks about why the language around fraud matters, what it takes to rebuild after financial and emotional devastation, and why she keeps showing up for people who don't yet have their own strength.
Topics covered:
Romance fraud and pig butchering scams
Fraud victim advocacy and support
Media language and how we talk about scams
Shame, silence, and survivor recovery
Women in fraud prevention and awareness