--- title: Cross Industry Fraud Intelligence and 314(b) Modernization - Ask Us Anything with Frank McKenna source_page: https://www.sardine.ai/media/fraud-forward/episodes/cross-industry-fraud-intelligence canonical: https://www.sardine.ai/media/fraud-forward/episodes/cross-industry-fraud-intelligence format: text/markdown date: 2025-08-06T00:00:00.000Z description: Cross country fraud losses rise while teams stay flat. Delayed coordination and siloed risk data slow response times and increase exposure across institutions… --- **Quick links:** [Human page](https://www.sardine.ai/media/fraud-forward/episodes/cross-industry-fraud-intelligence) · [Home](https://www.sardine.ai) · [Customers](https://www.sardine.ai/customers) · [Blog](https://www.sardine.ai/blog) · [Demo](https://www.sardine.ai/demo) --- # Cross Industry Fraud Intelligence and 314(b) Modernization - Ask Us Anything with Frank McKenna **Published:** 2025-08-06T00:00:00.000Z Cross country fraud losses rise while teams stay flat. Delayed coordination and siloed risk data slow response times and increase exposure across institutions… What’s up fraud fighters, and welcome to Fraud Forward! Fraud Forward is powered by Sardine. Alright, let’s get into it, because cross industry fraud intelligence is not optional anymore. Financial crime is moving across institutions, payment rails, telecom providers, and digital platforms in real time, and yet most teams are still trying to respond with siloed risk data and delayed coordination. And this is the part that makes me want to flip a table. 314(b) fraud information sharing was built for a slower era. It still matters, 100 percent, but it was not designed for coordinated rings that can test, pivot, and move funds in minutes. So in this live Ask Us Anything session, I’m joined by Frank McKenna, and we’re breaking down what fraud leaders are dealing with right now. Not a high-level policy debate. A practical, operator-focused conversation about financial crime information sharing, real time fraud information sharing, and what fraud prevention modernization actually looks like when your team size stays flat and the threat velocity keeps accelerating. Why this matters for fraud fighters Fraud does not happen in isolation, and neither should our defenses. Here’s the structural problem: Teams are seeing isolated fragments instead of coordinated schemes because ecosystem wide fraud visibility is limited Siloed fraud intelligence slows investigations, and by the time signals connect, the money is gone Cross industry fraud collaboration breaks down operationally because workflows are inconsistent and participation is uneven Without entity level fraud insights, you are monitoring accounts, not networks Shared risk intelligence is the control that keeps up with velocity, but it is not being treated like a core control everywhere And while we’re dealing with that, synthetic identity fraud detection is getting more expensive to unwind after onboarding, and deepfake identity threats are accelerating. If your model depends on single-institution monitoring and point-in-time checks, criminals will exploit the blind spots. What you’ll hear in this episode Where 314(b) fraud information sharing is falling short in practice and what modernization could look like Why real time fraud information sharing is critical before funds move, not after losses post How cross industry fraud intelligence improves ecosystem wide fraud visibility and reduces investigative duplication What synthetic identity fraud detection looks like operationally and why remediation is so costly after accounts are opened How deepfake identity threats are undermining traditional verification and why layered monitoring matters How internal fraud monitoring and culture determine whether risk signals get escalated or quietly rationalized Where AI assisted fraud investigations can help teams move faster without sacrificing judgment You should listen to this episode if you Lead fraud, AML, or BSA programs inside a bank or credit union and need stronger financial crime information sharing Are struggling with siloed fraud intelligence and want practical insight on cross industry fraud collaboration Are evaluating fraud prevention modernization and want to understand what actually changes outcomes Are dealing with synthetic identity fraud detection cases, deepfake identity threats, or internal fraud monitoring challenges Are early in your career and want guidance on building investigative judgment and credibility inside risk organizations If you liked this episode, follow Fraud Forward on Spotify, Apple Podcasts, YouTube, or your preferred platform for more operator-first conversations on fraud and institutional risk. Episode notes and key takeaways ### Cross industry fraud intelligence and 314(b) fraud information sharing Fraud no longer operates within institutional boundaries. Criminal networks test controls across multiple banks, fintechs, telecom providers, and digital platforms before institutions can even connect the signals. Frank helps me break down where 314(b) fraud information sharing is falling short in practice: 314(b) participation is often uneven, inconsistent, or too slow to match threat velocity Institutions frequently learn about shared exposure only after losses have already occurred Operational workflows do not always support real time fraud information sharing The gap between fraud velocity and regulatory modernization keeps widening The core point is simple. Without stronger cross industry fraud intelligence, teams investigate isolated fragments instead of coordinated schemes. What needs to be true for modernization to work: Signals move closer to real time, before funds move Institutions build repeatable processes for what gets shared, when, and how Shared risk intelligence becomes a foundational control, not a “nice to have” Entity level fraud insights get prioritized so teams can see networks, not just accounts ### Synthetic identity fraud detection and deepfake identity threats Let me just assure you, synthetic identity fraud detection is one of the most operationally expensive problems in the building. Fraudsters blend fabricated identities with legitimate credentials, and once an account is open, remediation gets ugly: More time, more manual work, more exceptions Harder customer friction decisions Longer investigations and downstream losses And now deepfake identity threats are making it worse by weakening traditional verification controls. Key themes from this section: Point-in-time identity checks are not enough when the threat evolves after onboarding Layered monitoring has to combine identity, behavior, entity context, and transaction patterns Institutions that rely only on static verification risk missing long-term entity risk signals AI assisted fraud investigations can help, but only if teams keep strong investigative judgment ### Internal fraud monitoring and fraud culture inside financial institutions Fraud prevention is not only models and tooling. Culture determines whether suspicious behavior is escalated, ignored, or quietly rationalized. 100 percent. This section covers how internal fraud monitoring can be built without eroding trust: Safe escalation pathways so employees can surface concerns without backlash Recognition for staff who speak up and catch suspicious behavior early Clear governance so insider access risk is treated seriously Investigative skepticism that protects integrity without poisoning morale We also talk directly to early-career fraud professionals about: Building investigative judgment through disciplined casework habits Navigating internal politics while maintaining compliance integrity Earning credibility by documenting well, escalating appropriately, and staying consistent ### AI, deepfakes, and institutional preparedness AI is not theoretical anymore. It is reshaping both attack patterns and investigative workflows. And here’s the reality for smaller institutions. You may not be able to outspend large banks on tooling, but you can absolutely improve outcomes through coordination: Prioritize cross industry fraud collaboration to offset resource constraints Improve internal information flow so signals do not die in inboxes Invest in shared risk intelligence and ecosystem wide fraud visibility Tighten operational workflows so real time fraud information sharing is possible Fraud is accelerating across institutional boundaries. Teams that invest in cross industry fraud intelligence, operational coordination, and cultural alignment will be better positioned to respond. The evolution of Banking on Fraudology The mission stays the same: Elevate fraud prevention education. Strengthen banking community leadership. Support real operators inside community banks and credit unions. Build durable fraud community building frameworks. Advance fraud prevention thought leadership that is grounded, not hyped. The future of banking fraud prevention depends on community. The future of credit union fraud prevention depends on collaboration. The future of fraud industry evolution depends on shared intelligence and values alignment. We are leveling up. And we are doing it together. Stay vigilant, stay informed, and keep moving fraud forward.