In the enterprise, educated decisions need to be made swiftly. A delayed decision could mean lost opportunity and/or profit. With the rise of Big Data, new tools are needed.
Data-intensive computing represents a new computing paradigm to address Big Data processing requirements using high-performance architectures supporting scalable parallel processing to allow government, commercial organizations, and research environments to process massive amounts of data and implement new applications previously thought to be impractical or unfeasible.
The fundamental challenges of data-intensive computing are managing and processing exponentially growing data volumes, significantly reducing associated data analysis cycles to support practical, timely applications, and developing new algorithms which can scale to search and process massive amounts of data.
The open source HPCC (High-Performance Computing Cluster) platform offers a seamless ecosystem for Big Data processing requirements that empowers developers and other professionals to manage it all end to end.
CASE STUDY 1: Detecting Collusion in Big Data for Health Care and Insurance The health care and insurance industry suffers from collusion at all levels – providers, attorneys, claimants, runners, etc. – specifically to run up claim costs. Traditional fraud detection methods such as “Link Analysis” are labor intensive and are reactive instead of predictive and proactive. To better detect fraud rings and collusion, two and three degree “external” relationships need to be revealed. This case study will demonstrate how to find non-obvious relationships for fraud and business opportunities.
CASE STUDY 2: Detect Fraud in Big Data for Financial Services. The Mortgage Fraud case study using 600 million deeds records and 3 billion people relationships, will be presented as one example of how LexisNexis actively leverages the platform to tackle real world challenges that traditionally would be impossible to attempt. The presenter will cover the following key areas:
• Extract, Transform and Load (ETL), a big data mashup involving 600 million deeds records, 3 billion person to person associations and mathematical graph magic (not a map-and-reduce process). • Rapid data delivery queries. • Dashboards with integrated visualizations.
Bill Fox Senior Director, Health Care LexisNexis Risk Solutions
Jo Prichard Consulting Software Engineer LexisNexis Risk Solutions/HPCC Systems
About HPCC Systems™ HPCC Systems™ from LexisNexis® Risk Solutions offers a proven, data-intensive supercomputing platform designed for the enterprise to process and deliver Big Data analytical problems. As an alternative to Hadoop and mainframes, HPCC Systems offers a consistent data-centric programming language, two processing platforms and a single architecture for efficient processing. Customers, such as financial institutions, insurance carriers, insurance companies, law enforcement agencies, federal government and other enterprise-class organizations leverage the HPCC Systems technology through LexisNexis® products and services. For more information, visit http://hpccsystems.com.
Big Data Examples at LexisNexis Risk Solutions • 50 billion records. • Over 10,000 public, non public and contributor data sources, made up of structure, semi-structured and unstructed data. • Several million records added daily. • 7.5 billion unique name and address combinations • 250 million unique identities [Over 1.1 billion unique business contacts.
Bill Fox, JD, MA, is Senior Director of Healthcare at LexisNexis Risk Solutions. Prior to LexisNexis, Mr. Fox was Vice President of Program Integrity at MAXIMUS Federal. He was a Partner at the law firm of Post and Schell, and was Deputy Chief of Economic and Cyber Crime at the Philadelphia District Attorney’s office and a Special Assistant U.S. Attorney in Philadelphia. Mr. Fox is a Senior Fellow at the Jefferson School of Population Health, on the Strategic Planning Comittee of the NHCAA, and leads HIMSS Enterprise Fruad Control taskforce. He is a frequent speaker on topics of healthcare fraud, compliance and quality. He has also served as a tactical strength and conditioning consultant to the U.S. Navy SEALs.
LexisNexis Risk Healthcare Solutions develops and implements innovative data driven technology solutions across the healthcare continuum with a focus on identity management/HIE, predictive analytics, fraud, waste and abuse detection and prevention, and disease management.
Data Scientist at LexisNexis Risk Solutions. I have responsibilities to the HPCC Systems platform technology and spearhead large scale graph analytics projects working with big data, for various industries to help customers target fraud, collusion and other red flag indicates.
Prior to LexisNexis, Mr. Prichard worked for Topspeed Software R&D in London.
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