Medical fraud, waste, and abuse cost insurers at least $80 billion each year. Medical expenses associated with bodily injury claims are one of the leading drivers of allocated loss adjustment expenses (ALAE). Does your SIU team have the information they need to fight medical billing fraud?
Provider Scoring provides a range of ROI metrics to support your success in the first year, champion your achievements, and ensure continued long-term benefits.
SIU investigators get qualified leads backed by specific issues so they can devise investigative plans, launch factual examinations, and develop questions for interviews, examinations under oath, and depositions.
Provider Scoring analyzes massive amounts of providers to spotlight outlier trends and patterns of practice, including high exposures and emerging schemes, so SIU analysts can identify which providers to focus on in their book of business.
With leads vetted simply and quickly, teams will know which providers to investigate and why, and SIU managers can articulate ROI with several tangible success metrics.
Achieve return on investment in the first year and beyond with several different metrics:
Medical Provider Scoring doesn’t stop with your data. It analyzes data from the Aggregated Medical Database—the largest P&C billing data repository.
Provider Scoring uses more than 100 advanced analytic models, casting a wider net to find more fraud, waste, and abuse (FWA).
Get insights on which providers may be submitting questionable bills and specific reasons the providers triggered potential FWA issues.
See projected patient counts and estimated dollar amounts billed by highlighted providers for each triggered reason, as well as benchmarking of the provider’s total billings among their specialty peers.
Provider Scoring is part of a full suite of claims solutions that provide compliance, claims development, and deeper fraud analysis and tools.
Fast-track claims while improving fraud detection with access to data from more than 1.8 billion claims.
Get hundreds of supplemental data reports to enhance claim analysis and investigations.
These models deliver enhanced claim scores and reason codes to detect potential fraud and support investigations.
This automated process applies a series of algorithms to every customer-submitted loss photo to expose anomalies.
Discover the hidden relationships and connections among claimants, providers, and businesses.