Real-Time Fraud Prevention with OrientDB
Banks and insurance companies lose millions of dollars in fraud every year. As online data grows, fraudsters have become increasingly capable of performing elaborate scams, identity theft, fraud rings and many other elusive ways to defraud customers and enterprises. Their methods are sophisticated and often times, their tactics go unnoticed until it is too late.
Using relational databases to detect fraudulent claims can prove especially difficult. Table and columns are not suitable for forming complex relations between datasets. Joining tables can prove time consuming as well as taxing on system performance, which makes them difficult to use when attempting to detect crimes in real time. Contrary to relational databases, graph databases are relational in nature and are inherently capable of forming links between pieces of information, which can be easily traversed to detect suspicious activity.
Whereas relational databases rely on primary keys to join disconnected pieces of information, graphs work by forming a web of interconnected data and allows customer details, transactions and relations to be formed quickly, are easily observable and always available. In fact, a simple visual representation of a graph is enough to detect links between individuals and pieces of information. Graph databases are perfectly suited to store information and relations in a manner that lends itself to uncovering strange data patterns. However, normal graph DBs still make use of document databases in order to store transaction data. With regards to fraud detection, integrating multiple systems is not optimal when hoping to store secure data that must be travelled quickly.
How Does Bank Fraud Happen?
Successful first party fraud is carried out by exploiting information that takes time to verify, that can be shared with other people, or that is simply overlooked due to the inability (or complexity) to properly link it to its source. By using real information such as telephone numbers and real addresses, scammers may appear to be regular clients, though these pieces of information can be used to create multiple identities.
How Can OrientDB Protect the Banking, Insurance and Online Retail industry?
By treating every edge and vertex as a JSON document, OrientDB allows properties to be assigned within relationships (links) themselves and does away with document stores all together. Its graph capabilities enable parts of or entire trees and graphs of records to be analyzed in just a few milliseconds. When it comes to quickly reading client data to find suspicious activity, multiple systems are simply not an as effective.
OrientDB Guarantees Ecommerce Safety
System reliability is also of utmost importance for companies dealing with millions of transactions while safekeeping sensitive personal information. Server node crashes can lead to lost data as well as leave systems vulnerable. OrientDB uses WAL (Write Ahead Logging) to restore database content after a crash. Any pending transactions are automatically rolled back. Immediately, the server cluster redistributes the load across the available nodes and all the clients connected to the node in failure are automatically switched to an available server node with no fail-over to the application level.
A Simple Choice
OrientDB is a 2nd Generation Open Source distributed graph-document database where every vertex and edge is a JSON Document. It supports schema-less, schema-full and schema-mixed modes, has a strong security profiling system based on user and roles and supports SQL amongst the query languages. It is incredibly fast, storing 220,000 records per second on common hardware and allows one to traverse parts of or entire trees and graphs of records in a few milliseconds. Its multi-model approach lends itself to easily and efficiently link database types to maximize performance.
Ranked 2nd most popular graph DB by DB engines, 6th document store and 7th key value store, it’s within the top 10 in all 3 model categories and steadily climbing the charts. Combining various models into one engine makes it a powerful, easy to use tool that doesn’t limit its users to adopt a single DB model.
OrientDB comes in two editions. The Community Edition is open source and free for any use (Apache 2 license). For those companies looking for Professional Support, Consultancy and additional advanced enterprise features, OrientDB Enterprise Edition is available upon request. Fortune 500 companies, government entities and startups all use this technology to build large-scale innovative applications. Clients include the United Nations, Ericsson, Sky, CenturyLink and Sonatype. OrientDB is the winner of the 2015 Infoworld Bossie award and has been covered by multiple media outlets.
Replacing your DBMS, once it no longer meets requirements, can be a huge cost in time and resources. Is your database powerful, scalable and flexible enough to grow with you? OrientDB also reduces the need to support multiple products to achieve your goals. See for yourself, give it a try! If you would like to receive more information about OrientDB and its capabilities, send us a message at firstname.lastname@example.org.
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OrientDB is the world’s leading distributed graph database and the 2nd in the general graph category. By combining the power of graphs with document, key/value, object-oriented, geospatial and reactive models into one core native engine, OrientDB extended the basic graph database concept into a Multi-Model open source DBMS.
It allows schema-less, schema-full and schema-mixed modes, supports SQL and TinkerPop/Gremlin standards and its strong security has been developed together with global banks who use it to power thousands of transactions per second. Fortune 500 companies, government entities and startups all use OrientDB to build large-scale innovative applications including: Accenture, Barclays, Cisco, Comcast, Dell, United Nations, Verisign, Pitney Bowes, Sky, Diaku, CenturyLink and Sonatype.
OrientDB won the prestigious 2015 Infoworld Bossie award and has been covered by multiple media outlets.