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Neo4j GraphAware Financial Crime Intelligence Debuts for Full-Cycle Detection, Investigation & Prevention
Graph intelligence leader delivers new graph-native financial services solution supported by a knowledge layer for trustworthy AI, enabling deeper and quicker financial crime investigations
SAN MATEO, Calif., September 16, 2026–(BUSINESS WIRE)–Neo4jⓇ, the world’s leading graph intelligence platform, today announced Neo4j GraphAware Financial Crime Intelligence, a detection and investigation solution built on a reusable knowledge layer for enterprise AI, specifically to help banks and insurers prevent financial crime. The news marks the first milestone for Neo4j since closing its acquisition of GraphAware in August 2026.
Financial crime: a $442bn global problem
Fraud is a world-leading crime, second only to burglary, with the OECD stating that $442bn was lost to consumer fraud globally in 2025. It is also a deeply networked and distributed crime, as seen with Interpol reporting over 5,800 arrests across 97 countries and territories from a single global fraud bust in July 2026. However, the responsibility is increasingly placed on financial institutions to be accountable and proactively prevent crime. With regulatory pressure bringing new and expensive fines and AI increasing the volume and creativity of fraudulent activity, a change is underway in how banks and insurance companies handle fraud, anti-money laundering (AML), and compliance.
Neo4j: fraud detection partner
GraphAware Financial Crime Intelligence from Neo4j is a graph-native detection and investigation solution built on a reusable knowledge layer for modern financial crime operations. It enables analysts and investigators to connect data silos, build deep context, and identify patterns through multi-hop reasoning, a core strength of graph databases. This leads to timely decisions based on high-quality detection, investigation, and prevention tooling.
Michael Down, Global Head of Financial Solutions at Neo4j, said, “Every fraud involves a network, every network has a pattern, and those patterns are hiding in your data. Financial crime is a deeply interconnected problem, but one that is better addressed by a modular graph intelligence platform, which, unlike others, natively stores relationships to effortlessly hop between multiple datapoints, detecting suspicious behaviors.”
A knowledge layer for every financial investigation
Neo4j already enables fraud detection or compliance solutions for many financial services organizations globally, including top 20 leaders such as BNP Paribas, UBS, and Zurich. The company also works with many fintechs and challenger banks on additional AI-powered solutions, such as Klarna, Prospa, and Arhasi. With the new GraphAware Financial Crime Intelligence solution, Neo4j now offers the full financial crime investigation cycle on a single graph-native stack, all within a comprehensive, adaptable, and continuously enriched environment, and underpinned by a knowledge layer for trustworthy AI. This includes:
