fraud detection Archives - Neo4j Graph Database

Graph Technology for Enterprise Master Data Management (MDM)

By Rachel Howard | July 14, 2017

Editor’s Note: This presentation was given by Aaron Wallace at GraphConnect San Francisco in October 2016. Presentation Summary Modern enterprises need to have a full, 360-view of their customers drive their bottom line. This requires the integration of data from… Learn More →

Keywords: customer information management • data quality • fraud detection • graphconnect • Knowledge Graph • Master Data Management • MDM • metadata management • Pitney Bowes • single customer view

Financial Services & Neo4j: Anti-Money Laundering

By Bryce Merkl Sasaki | June 26, 2017

Reducing the risk of money laundering presents a similar challenge to that of fraud detection when it comes to today’s financial services landscape. Firms need to know where funds come from and where they are headed, but criminals use indirection… Learn More →

Keywords: AML • anti-money laundering • cypher • Data Visualization • financial services • fraud detection • graph technology • money transfer • smurfing • sql

Financial Services & Neo4j: Fraud Detection

By Bryce Merkl Sasaki | June 19, 2017

Identifying and stopping fraudulent activity is harder than ever for financial services organizations. Standard anti-fraud technologies — such as a deviation from normal purchasing patterns — use discrete data. This is useful for catching individual criminals acting alone, but discrete… Learn More →

Keywords: Connected Data • cypher • Data Visualization • financial services • Fortune 500 • fraud detection • fraud ring • graph technology • Microsoft SQL Server • relational database

Fraud Prevention with Neo4j: A 5-Minute Overview

By Bryce Merkl Sasaki | April 21, 2017

Fraud is becoming increasingly difficult to discover and prevent as fraudsters are increasingly employing complex techniques and advanced technologies to perpetrate fraud. Who Are Today’s Fraudsters? Today, fraudsters are organized in groups, possess synthetic or manufactured identities – which in… Learn More →

Keywords: credit card fraud • data science • ecommerce fraud • financial services • fraud detection • fraud pattern • fraud prevention • Fraud Rings • Insurance Fraud • pattern analysis

The 5-Minute Interview: Chuck Kane, Director of Global Solutions at Pitney Bowes

By Rachel Howard | March 17, 2017

“Moving from relational to graph, it takes time to learn to step back from your data and ask, ‘What more can I do?’” said Chuck Kane, Director of Global Solutions at Pitney Bowes. The company partnered with Neo4j to provide… Learn More →

Keywords: 5-minute interview • AML • Connected Data • Data Relationships • fraud detection • graph database • neo4j • pattern analysis • Pitney Bowes • relational database

The 5-Minute Interview: Andrés Natanael Soria, Senior Software Architect at Cablevisión

By Rachel Howard | March 10, 2017

“Due to native graph storage, the Neo4j queries run really quickly, which is amazing,” said Andrés Natanael Soria, Senior Software Engineer at Cablevisión Fibertel. The company uses a broadband network to provide cable television and internet services to customers throughout… Learn More →

Keywords: 5-minute interview • apache kafka • data model • docker • fraud detection • impact analysis • native graph storage • network failure detection • Recommendation Engine • sql

Couchbase & JDBC Integrations for Neo4j 3.x

By Bryce Merkl Sasaki | November 22, 2016

Editor’s Note: This presentation was given by Lorenzo Speranzoni at GraphConnect Europe in April 2016. Here’s a quick review of what he covered: Converting JSON documents into nodes Couchbase integration architecture How the JDBC driver makes use of the Bolt… Learn More →

Keywords: bolt • Couchbase • fraud detection • graph database • graphconnect • jdbc • json • neo4j 3.0 • Recommendation Engine • Spotify

Detect & Investigate Financial Crime Patterns with Linkurious

By Bryce Merkl Sasaki | October 7, 2016

Linkurious is a Bronze sponsor of GraphConnect San Francisco. Meet their team on October 13-14th at the Hyatt Regency SF. Using Graphs to Fight Financial Crime Financial crime can take many forms: money laundering, terrorism funding, corruption, tax evasion, insurance… Learn More →

Keywords: AML • anti-money laundering • cypher • financial crime • fraud detection • Geospatial • Insurance Fraud • Linkurious • tax evasion • terrorism funding

The 5-Minute Interview: Mar Cabra, Editor at the ICIJ

By Bryce Merkl Sasaki | June 24, 2016

For this week’s 5-Minute Interview, I sat down with Mar Cabra, the Data & Research Unit Editor at the International Consortium of Investigative Journalists (ICIJ). I caught up with Mar at GraphConnect Europe after her standing-room-only keynote: “How the ICIJ… Learn More →

Keywords: 5-minute interview • data analysis • ETL tool • fraud detection • graph visualization • graphconnect • icij • Linkurious • Mossack Fonseca • Panama Papers

The 5-Minute Interview: Jean Villedieu, Co-Founder of Linkurious

By Bryce Merkl Sasaki | June 10, 2016

For this week’s 5-Minute Interview, I chatted with Jean Villedieu, a co-founder of Linkurious. I sat down with Jean at GraphConnect Europe last April. Here’s what we discussed: Q: For people who might not be familiar with it, what is… Learn More →

Keywords: 5-minute interview • anti-fraud • cybersecurity • fraud detection • graph visualization • graphconnect • knowledge management • Linkurious • Network Management • Panama Papers

Stop Fraud Rings in Their Tracks with Graph Databases [Infographic]

By Bryce Merkl Sasaki | May 16, 2016

Fraud rings are big business. First-party bank fraud costs banks (and their customers) over $16 billion each year in the United States, and insurance fraud costs nearly $80 billion annually. And fraud rings organized around ecommerce fraud rack up nearly… Learn More →

Keywords: bank fraud • ecommerce fraud • fraud analytics • fraud detection • Fraud Rings • Graph Databases • infographic • Insurance Fraud • neo4j • organized fraud

(Un)common Use Cases for Graph Databases

By Bryce Merkl Sasaki | April 18, 2016

At GraphAware, we live and breathe Neo4j. For three years, we have been helping customers around the world embrace this amazing technology as a solution to many interesting problems. Mainstream applications of graphs, such as real-time recommendations, fraud detection, impact… Learn More →

Keywords: cypher • fraud detection • graph database • GraphAware • graphconnect • investment portfolio • law enforcement • neo4j • real-time recommendation • rules engine

Graphs Are Everywhere and Their Possibilities Are Endless

By Bryce Merkl Sasaki | April 13, 2016

Graphs are everywhere, and with the ability of a graph database to solve multiple business problems, pre-empt potential situations and – most importantly – save companies huge amounts of money in the meantime, why shouldn’t you use Neo4j? Graphs in… Learn More →

Keywords: Connected Data • eSynergy solutions • first-party fraud • fraud detection • graph • logistics • Master Data Management • neo4j training • synthetic identity • triadic closure

From the Neo4j Community: February 2016

By Bryce Merkl Sasaki | March 8, 2016

In the Neo4j community last month, love was in the air. That love expressed itself as more nodes than ever in our community content. From articles and podcasts to GraphGists and other projects, our global graph of community members keeps… Learn More →

Keywords: cypher • data pipeline • elasticsearch • fraud detection • graph database • graph visualization • Master Data Management • metadata management • Neo4j Community • real-time recommendations

Why Enterprises Are Abandoning RDBMS (and Adopting Graphs)

By Bryce Merkl Sasaki | March 3, 2016

Relational databases (RDBMS) were conceived to digitize paper forms and automate well-structured business processes, and they are still extremely relevant today. But, many companies are choosing to explore other database options to solve some of their biggest challenges. Why? The… Learn More →

Keywords: Data Relationships • fraud detection • graph database • graphs • Master Data Management • Network Monitoring • rdbms • Recommendation Engine • Relational Databases • webinar

Neo4j + Cassandra: Transferring Data from a Column Store to a Property Graph

By Bryce Merkl Sasaki | February 8, 2016

We’ve previously talked about the concept of polyglot persistence and why it can make sense to use multiple database technologies together. Today, we will examine a possible use case for using Neo4j (a graph database) and Cassandra (a column store)… Learn More →

Keywords: Cassandra • column store • data import • data mapping • data model • fraud detection • neo4j • polyglot persistence • property graph • write throughput

How Graph Databases Stop E-commerce Fraud in Real Time

By Bryce Merkl Sasaki | January 25, 2016

As our lives become increasingly digital, a growing number of financial transactions are conducted online. Fraudsters have been quick to adapt to this trend, and to devise clever ways to defraud online payment systems. While this type of activity can… Learn More →

Keywords: credit card number • e-Commerce Fraud • fraud detection • fraud patterns • fraud ring • fraud scenario • graph database • ip address • online payment systems • synthetic identities

Catching Insurance Fraud Using Graph Database Technology

By Bryce Merkl Sasaki | January 18, 2016

The impact of fraud on the insurance industry is estimated to be $80 billion annually in the US, a number that has been growing in recent years. From 2010 to 2012, questionable claims in the U.S. jumped 27 percent, to… Learn More →

Keywords: fraud detection • fraud ring • graph database • Insurance Fraud • Network Analysis • relational database • social network analysis • soft tissue injuries • whiplash

Improving First-Party Bank Fraud Detection with Graph Databases

By Bryce Merkl Sasaki | January 11, 2016

First-party bank fraud involves fraudsters who apply for credit cards, loans, overdrafts and unsecured banking credit lines, with no intention of paying them back. It is a serious problem for banking institutions. U.S. banks lose tens of billions of dollars… Learn More →

Keywords: bank fraud • cypher • first-party fraud • fraud detection • fraud prevention • fraud ring • graph database • graph traversal • link analysis • relational database

Why Modern Fraud Detection Needs Graph Database Technology

By Bryce Merkl Sasaki | January 4, 2016

Banks and insurance companies lose billions of dollars every year to fraud. Traditional methods of fraud detection play an important role in minimizing these losses. However increasingly sophisticated fraudsters have developed a variety of ways to elude discovery – both… Learn More →

Keywords: bank fraud • Connected Data • data analysis • e-Commerce Fraud • fraud detection • fraud prevention • fraud ring • graph database • Insurance Fraud • real-time fraud detection

How Gamesys Harnessed Neo4j for Competitive Advantage

By Bryce Merkl Sasaki | December 7, 2015

Gamesys is the largest cash and social gaming operator in UK and Europe, created the world’s first cash gaming application on Facebook. With games like Jackpotjoy, Instant Slots and Here Be Monsters, the company features online bingo, slots and casino… Learn More →

Keywords: competitive advantage • data model • data relationship • fraud detection • Gamesys • graph database • neo4j • online bingo • online gaming • social network

The Sustainable Competitive Advantage of Connected Data

By Bryce Merkl Sasaki | November 30, 2015

As data sizes and customer expectations accelerate at lightning speed, how can your business achieve sustainable competitive advantage? By unlocking the value of data relationships – in both new and reimagined applications – your enterprise can easily improve performance, simplify… Learn More →

Keywords: Connected Data • Data Relationships • fraud detection • graph database • Internet of Things • Master Data Management • nosql • Recommendation Engine • relational database • sustainable competitive advantage

The 5-Minute Interview: Hamish Boland-Rudder, Online Editor of the ICIJ

By Bryce Merkl Sasaki | November 27, 2015

For this week’s 5-minute interview, I sat down with Hamish Boland-Rudder, the Online Editor for the International Consortium of Investigative Journalists (ICIJ). Hamish and I got to chat at GraphConnect San Francisco. Q: Can you tell me about how you… Learn More →

Keywords: 5-minute interview • excel • fraud detection • graph database • graph visualization • icij • Linkurious • offshore finance • relational database • sql database

The Competitive Advantage of Graph Databases in the Enterprise

By Bryce Merkl Sasaki | November 16, 2015

“Big data” grows bigger every year, but today’s enterprise leaders don’t only need to manage larger volumes of data – they critically need to generate insight from their existing data. So how should CIOs and CTOs generate those insights? To… Learn More →

Keywords: Big Data • CIO • competitive advantage • cto • data model • fraud detection • graph database • rdbms • Recommendation Engine • relational database

Graph Databases in the Enterprise: Fraud Detection

By Bryce Merkl Sasaki | September 21, 2015

Banks and insurance companies lose billions of dollars every year to fraud. Traditional methods of fraud detection fail to minimize these losses since they perform discrete analyses that are susceptible to false positives (and false negatives). Knowing this, increasingly sophisticated… Learn More →

Keywords: banks • e-Commerce Fraud • fraud detection • fraud ring • Graph Databases • insurance company • link analysis • online payment systems • synthetic identities • use case

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Tag Archives: fraud detection