Catches what static rules miss.
A finance-specific build on Data Reliability, tuned for synthetic identities, deepfake onboarding, and agent-driven scams — behavioral, cross-channel anomaly detection for a world where fraud is now as automated as the defenses against it.
Detects patterns static rules miss — synthetic identity signals, deepfake onboarding artifacts, coordinated account behavior.
Connects signals across onboarding, transactions, and device data rather than checking each channel in isolation.
Extends Data Reliability's already-working anomaly detection rather than starting from nothing.
Planned design — this pipeline does not exist yet.
Points the existing anomaly engine at finance-specific data — onboarding events, device fingerprints, transaction sequences.
Layers behavioral and cross-channel checks tuned for synthetic identity and deepfake onboarding on top of Data Reliability's statistical checks.
Produces a composite risk score and routes high-risk cases for manual review rather than auto-blocking on a single signal.
The reasoning approach this concept is designed around.
The combination shown here is illustrative — actual weights, thresholds, and scoring logic are unspecified until this is designed.
Unlike most concepts on this roadmap, FraudSentinel's parent engine — Data Reliability's anomaly detection — is working code today, not a future dependency.
Fraud has automated; static rule lists lag behind. The design bet is on behavioral and cross-channel patterns instead.
Produces a risk score for human review rather than auto-blocking, since false positives have real customer cost.
Explicitly designed around synthetic identities and deepfake onboarding, not just transaction-pattern fraud.
Nothing below is built. This describes the intended design and its dependencies.
One mock transaction shown for illustration — real weighting, thresholds, and scoring logic are unspecified.
Extends an anomaly detection engine that already works today, not a hypothetical one.
Onboarding, device, and transaction signals correlated together, not siloed.
Synthetic identity and deepfake onboarding named explicitly, not an afterthought.