Neo4j is the Graph Database of Choice for World’s Top Financial Services Organizations

Deployed by 20 of the World’s Top 25 Financial Services Firms, Neo4j Sees a Surge in Demand for its Powerful Graph Technology

SAN MATEO, Calif. – October 22, 2019 – Neo4j, the leader in graph databases, reported a surge in demand for its powerful graph technology among the global financial services community. 

As firms step up their fight against fraud, bolster anti money laundering (AML) investigation and comply with strict transparency requirements, Neo4j has been the graph database of choice for 20 of the world’s 25 top financial services firms. Made famous thanks to its role in uncovering the Panama and Paradise Papers tax avoidance scandals, Neo4j is on the shortlist for many organizations looking to identify and eliminate financial fraud.

Caption: Neo4j worked with the ICIJ on the Panama Papers leak resulting in a Pulitzer Prize-winning investigation into global tax evasion. Shown is the Neo4j graph data model used for the investigation.

Fortune 500 organizations are adopting graph capabilities to scrutinize financial data for the earliest signs of financial misconduct or fraud in real time. Organizations in the financial services industry know they’re in a rapidly escalating arms race trying to defend against bad actors leveraging new technologies – a struggle that requires new and more sophisticated fraud detection and prevention approaches.

Firms’ ability to pinpoint financial crime from huge data volumes using Neo4j are impressive. When transactions run into tens of thousands of occurrences per day, traditional, manual approaches to anomaly checking aren’t sustainable.

Graph technology is able to “connect the dots” across even the most complex and opaque data trails to reveal the subtlest connections and inter-relationships. This capability proved instrumental in recouping some $1.2 billion in fines and back taxes linked to the Panama Papers affair.

Caption: An anti-money laundering graph data model in Neo4j that clearly demonstrates how entities are related.

The global fraud detection and prevention market was valued at $17.5 billion in 2017 and is expected to grow to $120 billion by 2026, according to Stratistics MRC. As a testament to the velocity of innovation in fraud, over the last decade more than 48,000 patents for fraud and anomaly detection solutions have been issued in the U.S. alone.

Dun & Bradstreet (D&B), the world’s leading business information provider, was among the first to spot the potential to apply graph technology to fraud detection, when it launched a new company ownership tracking service back in 2016. The service allows clients to investigate all historic company ownership records linked to individuals, and it adheres to new international transparency regulations designed to counter tax evasion and money laundering. 

Dun & Bradstreet’s Senior Compliance Manager, Paul Westcott, explained how the company uses Neo4j.

“Being able to quickly understand relationships between data gives us the ability to rapidly interpret corporate structures and any dilution of ownership of a business,” said Westcott. “Neo4j’s networks of nodes and connections mean the data to do this can be surfaced for an individual in milliseconds – a very quick return of information, making graph the ideal fit for our needs.”

Neo4j’s Vice President of Products, Philip Rathle, explains how augmenting traditional data management approaches with graph databases allows financial institutions to leverage connections inherent to their data.

“Graph databases offer powerful new methods of uncovering fraud rings, money laundering, and other sophisticated scams by surfacing patterns in data that are invisible via traditional methods,” said Rathle. “The same pattern-based approach enables financial institutions to understand and better assist their customers, who grapple with multiple accounts, identifiers, and lines of business. Graph-driven innovations at banks today result in initiatives and products that better serve customers, increase share of wallet, promote capital preservation and enhance regulatory compliance effectiveness.”

AIG, Citigroup, Credit Agricole, China Zheshang Bank (CZ Bank), ING, Société Générale, Thomson Reuters and UBS are among Neo4j’s numerous financial services clients, applying Neo4j’s graph technology across a wide range of risk management use cases. Meanwhile in the insurance sector, Neo4j’s customers include Aviva, AG Insurance Belgium, Die Bayerische and Zurich Insurance Group.

Graph’s critical role in making sense of complex data relationships has been demonstrated in a broad range of business settings. Gartner considers graph to be a top 10 data and analytics technology trend for 2019. Combined with artificial intelligence and machine learning, graph technology has tremendous potential to uncover fraud with record speed and efficiency.

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Neo4j is the leading graph database platform that drives innovation and competitive advantage at Airbus, Comcast, eBay, NASA, UBS, Walmart and more. Thousands of community deployments and more than 300 customers harness connected data with Neo4j to reveal how people, processes, locations and systems are interrelated. Using this relationships-first approach, applications built using Neo4j tackle connected data challenges including artificial intelligence, fraud detection, real-time recommendations and master data. Find out more at



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