Neo4j Addresses Key Challenges in Finance
In today’s regulatory environment, financial services firms are beginning to experience the impact of graph databases across a number of functions ranging from fighting financial crimes, preventing and responding to cyber threats and ensuring compliance.
Meanwhile, as the continuous digitization of processes requires financial services firms to evolve their customer engagement strategies to meet rising customer expectations, graph databases are helping financial services firms gain competitive advantage from digitization to drive new sales, reduce costs and build closer relationships with customers.
This white paper, “Addressing Key Challenges in Financial Services with Neo4j,” illustrates how financial services organizations are using graph databases, specifically Neo4j, to effectively solve these problems.
Fast Track
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Neo4j powers the Insurance Industry with High Performance at Die Bayerische
The German insurer uses Neo4j to create a high-performance sales system with 24/7 instant access to contract information.
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How Lending Club uses Neo4j to manage over 130 microservices
Lending Club relies on Neo4j to in its mission to shake up the financial services industry.
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Fraud Detection: Discovering Connections with Graph Databases
Learn how powerfully and effectively graph databases uncover first-party bank fraud, insurance fraud, ecommerce fraud and other fraud scenarios.
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Neo4j Financial Services Customers
ICIJ and the Paradise Papers
Using a search engine built on Neo4j, the Paradise Papers uncovers how individuals and organizations use shell companies in tax havens and offshore jurisdictions to avoid taxes.
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Customer Spotlight: Wobi
Insurance price comparison site Wobi uses Neo4j to create a detailed financial picture of each customer, including savings, pensions, insurance policies, accounts and family background.
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Customer Spotlight: Cerved
Find out how a Neo4j-powered solution allowed Cerved to simplify processes and cut maintenance and development costs when it came to multi-level relationship searches.
Read more“The transition to Neo4j technology has at least doubled the level of service for identification of the actual owner of businesses, from an average calculation time of 12 seconds to 67 milliseconds (-99 %) in cases that require tracking of up to 15 ownership links. This allowed us to extend its use and improve the precision of the algorithm at the same time.”
—Stefano Gatti, Innovation & Data Sources Manager, Cerved
Financial Services Case Studies
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Real-Time Data Lineage at UBS — Wren Chan and Sidharth Goyal, UBS
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Microservice and Module Management with Neo4j — John Lavin, Vanguard
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Preventing Fraud with Neo4j - 5 min Exec Overview
