The Next Evolution of Fraud Defense: Unlocking Collective Fraud Intelligence with Sonar AI

What is up fraud fighters, and welcome to Fraud Forward!

Today we’re talking about something that is becoming absolutely essential for fraud prevention teams.

Fraud intelligence.

Because fraud no longer happens inside a single institution.

Fraudsters move across fintechs, banks, payment rails, and digital ecosystems incredibly quickly. They test controls at one institution, pivot to another, and exploit the gaps in between.

And the reality is this.

If every institution is relying only on its own transaction data, we are always going to be one step behind.

That’s why collective fraud intelligence is becoming such an important capability across the industry.

In this episode I sat down with Ravi Loganathan, Co-founder and President of Sonar AI and Head of Banking and Policy at Sardine.

Ravi has spent more than two decades working across banking, payments, and consortium networks, and he brings a really unique perspective to how fraud intelligence sharing can strengthen financial crime prevention.

What I really appreciated about this conversation is that we didn’t just talk about theory.

We talked about how fraud intelligence actually works in practice, how institutions can share signals responsibly, and how shared fraud defense can help detect threats before funds move.

What you’ll hear in this episode

• Why fraud intelligence for banks and credit unions is becoming essential
• How fraud signal sharing can expose recipient risk before a payment is authorized
• The role of consortium based fraud prevention in closing ecosystem gaps
• How fraud intelligence under FinCEN 314(b) enables compliant collaboration
• Why AI driven fraud detection becomes stronger when institutions share intelligence

You should listen to this episode if

• You lead fraud prevention, BSA, AML, or payments risk programs
• Your institution is facing authorized push payment fraud exposure
• You are evaluating fraud intelligence platforms or consortium participation
• You want stronger cross institution fraud detection
• You are looking for compliant approaches to fraud intelligence sharing

If you liked this episode, be sure to subscribe and review the podcast on iTunes, Spotify, YouTube, or wherever you listen to podcasts.

Episode notes & key takeaways

Before we double click on the notes, I just want to say that my marketing team told me I need to structure these notes a certain way in order for people to find my podcast. The below is a bit of that 😀

Collective fraud intelligence is becoming essential

One thing Ravi and I talked about right away is how fraudsters take advantage of institutional isolation.
Fraud attacks rarely stay inside one bank, one fintech, or one payment rail.

Fraudsters test a tactic at one institution, pivot to another, and repeat that process across the ecosystem.

Without collective fraud intelligence, each institution only sees a fragment of the attack lifecycle.

Fraud intelligence networks help close that gap by enabling shared fraud defense.

When institutions share fraud signals responsibly, the entire ecosystem gains earlier visibility into emerging threats.

How fraud intelligence works in practice

During our conversation, Ravi walked through how a fraud intelligence platform actually operates in real environments.

Before authorizing a payment or approving a new account, an institution can query a fraud intelligence network about the entity involved.

That might be a recipient account, email address, device, or identity signal.

The response could include block list indicators, risk scoring signals, or simplified risk levels that augment internal decisioning.

Participating institutions contribute feedback into the network, which strengthens the fraud intelligence ecosystem over time.

The more signals shared across institutions, the stronger the detection capability becomes for everyone.

Regulatory foundations enable secure collaboration

One of the most important questions fraud teams ask about fraud intelligence sharing is compliance.

And Ravi spent some time explaining how regulatory frameworks already support responsible collaboration.

Fraud intelligence under FinCEN 314(b) allows financial institutions to form associations and share fraud related information in a compliant way.

Additional signal sharing may also be supported under the Gramm Leach Bliley Act depending on the structure of the collaboration.

What that means is institutions do not have to choose between fraud intelligence sharing and compliance.

The regulatory foundation already exists to enable secure collaboration.

Empowering community banks and credit unions

Another point Ravi made that really resonated with me is how important accessibility is for fraud intelligence.

Fraud intelligence for credit unions and community banks has to work within real operational constraints.

Not every institution has a massive engineering team.

Batch inquiry capabilities and batch signal contributions allow smaller institutions to participate in fraud intelligence networks without complex API integrations.

Partnerships with core providers can also embed fraud intelligence into existing workflows, making participation more practical for institutions of all sizes.

Shared fraud defense only works if the ecosystem is broad enough to be effective.

The future of fraud intelligence

Looking ahead, fraud intelligence is evolving beyond individual transaction monitoring.

Ravi and I talked about how innovations like entity risk intelligence and expanded financial crime intelligence services are creating broader ecosystem visibility.

Capabilities such as entity footprint analysis, credential monitoring, and digital ecosystem signals allow institutions to understand risk at the entity level rather than just the transaction level.

That shift from transaction based defense to ecosystem level awareness is one of the most important developments happening in fraud prevention today.

Because the more context institutions have about the entities they interact with, the earlier they can detect fraud risk.