Fabricated scripts, doctor hopping and aberrant prescribing and filling patterns are just a few of the schemes we will unravel during this webinar to better understand the toll they are having on your members and your business. Join LexisNexis^® to explore methodologies that expand your investigative scope to identify critical target groups who impact your plan and its daily operations.

Topics covered include:

• The role and use of data to identify these surface scheme types.
• Key critical measures that can bring these schemes to the surface within your universe of claims faster.
• Workflow development process that includes preventative actions, educational touchpoints, provider monitoring, and member outreach.

Faculty

Richard K. Grape, Jr., MPA, MCMP-II
Director of Market Planning, LexisNexis

Tom Figurski, MBA, CFE, CPC
Sr. Consultant, Payer Solutions
LexisNexis Risk Solutions

Identity Fraud in the age of the Dark Web
Sponsored by Experian
November 8, 2018
2:00 pm ET

The pace of data breaches continues to rise.  It has been noted that an individual’s identity is available on the dark web for roughly $1,200. 

With personally identifiable information (PII) available to fraudsters, identity management methods must evolve. 

Several key methods have proven effective in using advanced analytics in fighting identity fraud horizontally across industries and across fraud attack vectors.  Medical ID theft and government entitlement ID theft have just begun to receive the focus found in the financial services industry.

Experian’s Identity Management expert, Eric Thompson will discuss industry trends, the impact of the dark web, and strategies to help uncover fraudulent identities in a portfolio as well as preventing the fraudulent identity from entering the portfolio.

During the webinar, gain greater insight into:

• ID verification
  • Risk based methodology
  • Layered approach using alternative data sources
  • Reducing the reliance on PII in the process

• Device assessment
  • Look at the identity holistically, considering the person and the device

• Tailored and custom fraud detection models
  • Improved model performance with heterogeneous data
  • Machine learning improving model performance

• Portfolio monitoring
  • ID assessment after verification

Faculty
TBA