The "Instant" Fraud & AML Sentinel
The agent mission
Stop a coordinated fraud ring in real time. Correlate card payments, ACH/wires, account logins, device fingerprints, and customer communications to identify the ring leader and block losses before funds irreversibly leave the network. The agent must act in seconds—while producing an auditor-ready explanation of every action taken.
The Challenge
Split Evidence
Fraud signals are fragmented across transaction rails (cards, RTP, ACH, wires), identity systems (KYC/CRM), security telemetry (logins, devices, IPs), and communications (chat, email, call transcripts). The hardest part is joining these sources fast enough to be useful—without losing traceability.
Graph Speed vs. Compliance
Modern fraud is relational: mule accounts, shared devices, synthetic identities, and coordinated timing. Graph analytics can surface this, but many pipelines are batch-based and produce stale results. Meanwhile, regulators and risk teams require explainability—why a customer was blocked, and which evidence justified it.
Unstructured Blind Spots
Critical indicators often hide in PDFs and free text: onboarding documents, dispute narratives, SAR notes, support chats, and email threads. Keyword search misses paraphrases and code words, and manual review is too slow.
High-Volume, Low-Latency Reality
Payment networks operate at massive event rates with tight SLAs. If correlation requires moving data into separate systems (ETL, lakehouse, feature store, graph DB), teams trade speed for complexity—and gaps appear exactly where attackers exploit them.
How Volumez Agentic Data Platform solves this
Unified, Governed Signal Plane
Matrix brings transactions, identity/KYC artifacts, login/device telemetry, and communications into one governed data plane that preserves raw records, normalization steps, and a full chain-of-custody for risk and audit teams.
Real-Time Entity Resolution + Ring Graphs
Matrix builds and updates relationship graphs in-place—shared device, shared address, common beneficiary, co-timed behavior—so agents can traverse multi-hop connections instantly and rank the most likely ring nodes as events arrive.
Semantic Retrieval for 'Dark' Risk Data
Matrix turns PDFs, chat logs, call transcripts, and case notes into queryable artifacts (extracted text, entities, vectors) so agents can retrieve concept-level matches (e.g., similar narratives, recurring phrasing, forged doc patterns) with citations back to the source.
Explainable Decisions at Machine Speed
Matrix keeps every model input and join path linked to the originating evidence. The agent can output an action (block, step-up auth, hold funds) plus an explanation trail that maps directly to source events and artifacts—meeting both latency targets and compliance requirements.
Take agentic to a whole new level.
Infrastructure Ready for Anything Agents Demand to Deliver ROI.
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