Fraud doesn’t start with the transaction. It starts with the trajectory.
SPEmet helps organizations build, govern and defend against AI-enabled fraud by focusing on the signals that appear before financial loss.
Behavior
Trust
Trajectories
Intelligence
Build. Govern. Defend.
We work at the intersection of artificial intelligence, fraud, risk and human behavior — helping organizations stay ahead of emerging threats in an increasingly complex world.
Authorized doesn’t always mean unmanipulated.
In an AI-enabled world, identity can be real, authentication can be correct and intent can still be manipulated. We focus on the behavioral signals, relationships and trajectories that precede fraudulent activity.
Built from inside the problem.
Raquel Schwarcz founded SPEmet after more than two decades working across investigations, fraud, payments and technology risk, including leading global risk and fraud-prevention programs at Amazon.
Meet the Founder
Organizations operating in high-trust, high-risk environments.
Financial
Services
Payments &
Fintech
Marketplaces &
Platforms
Enterprise &
High-Growth
Government &
Non-Profit
Ready to move fraud detection upstream?
Let’s talk about how SPEmet can help your organization build intelligently, govern responsibly and defend against what’s next.
Book a ConversationTechnology, advisory and research built around one question: how early can we know?
Explore the systems, advisory work and research behind SPEmet’s approach to fraud, AI risk and trust intelligence.
EmberTrace
Detect developing manipulation trajectories before financial action becomes the first reliable signal.
Explore EmberTrace →Fraud & Risk Advisory
Senior-level fraud, AI risk and control strategy for organizations facing growth, friction or control uncertainty.
Explore Advisory →Project EMBER
Research into behavioral progression, manipulated intent, synthetic presence, trust provenance and AI-enabled influence.
Explore the Research →Detecting Fraud Before the Transaction
A practical framework for identifying behavioral progression, manipulation patterns and adversarial activity before financial loss occurs.
View the Framework →A DIFFERENT APPROACH