Taking the First Step: How to Lead a Local Neo4j GraphDB Meetup
By Jocelyn Hoppa
August 2, 2018|
Reading time: 4 minutes
I discovered Neo4j and became instantly captivated. Finding something that made data make sense, was fun, approachable, and easier to learn, I read articles and white papers, watched videos online… but it wasn’t enough. I needed to connect, with people,… Read more →
Keywords: Big Data • Connected Data • data science • fraud detection • graph algorithms • Graph Databases • graphitude • neo4j meetup • nodes • relationships
Graph Databases for Beginners: Data Modeling Pitfalls to Avoid
By Bryce Merkl Sasaki
July 31, 2018|
Reading time: 6 minutes
With the advent of graph database technology, data modeling has become accessible to masses. Mapping business needs into a well-defined structure for data storage and organization has made a sortie du temple (of sorts) from the realm of the well-educated… Read more →
Keywords: Connected Data • cybersecurity • data model • data modeling • fraud detection • graph data model • graph data modeling • graph database • graph model • graph technology
This Week in Neo4j – Moving Adobe Behance from Cassandra to Neo4j, New Go Driver, Emil on The New Stack Makers Podcast
By Mark Needham
July 21, 2018|
Reading time: 6 minutes
Welcome to this week in Neo4j where we round up what’s been happening in the world of graph databases in the last 7 days. This week David Fox explains how his team at Adobe moved from a 48 instance Cassandra… Read more →
Keywords: Adobe • APOC • emil eifrem • fraud detection • google cloud platform • Google Kubernetes Engine • python • RDF • twin4j • yFiles
Graph Technology for Enterprise Master Data Management (MDM)
By Rachel Howard
July 14, 2017|
Reading time: 8 minutes
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… Read 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|
Reading time: 3 minutes
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… Read 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|
Reading time: 5 minutes
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… Read 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|
Reading time: 4 minutes
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… Read 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|
Reading time: 3 minutes
“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… Read 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|
Reading time: 2 minutes
“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… Read 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|
Reading time: 3 minutes
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… Read 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|
Reading time: 5 minutes
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… Read 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|
Reading time: 7 minutes
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… Read 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|
Reading time: 3 minutes
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… Read 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|
Reading time: 1 minute
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… Read 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|
Reading time: 4 minutes
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… Read 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|
Reading time: 3 minutes
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… Read 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|
Reading time: 3 minutes
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… Read 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|
Reading time: 2 minutes
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… Read 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|
Reading time: 5 minutes
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)… Read 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|
Reading time: 3 minutes
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… Read 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|
Reading time: 4 minutes
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… Read 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|
Reading time: 6 minutes
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… Read 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|
Reading time: 3 minutes
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… Read 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|
Reading time: 4 minutes
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… Read 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|
Reading time: 3 minutes
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… Read more →
Keywords: Connected Data • Data Relationships • fraud detection • graph database • Internet of Things • Master Data Management • nosql • Recommendation Engine • relational database • sustainable competitive advantage
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