Insurance Fraud Detection

Fraud & Risk

Prevent, detect and manage fraud across the enterprise, making smarter decisions, increasing return on capital and driving business performance

Insurance Fraud Detection

Insurance fraud affects not only the financial health of the insurers, but also of innocent people seeking effective insurance coverage. Fraudulent claims are a serious financial burden on insurers and result in higher overall insurance costs. Here are a few examples of the way data analysis can be applied to fight fraud in the insurance industry:

  • Medical Billing Fraud
    • Identify excessive billing — same diagnosis, same procedure
    • Identify excessive number of procedures, per day or place of service/day
    • Identify mutiple billing of same procedure, same date of service
    • Highlight ?upcoding? of procedures. Statistically outlying numbers
    • Locate age inappropriate treatments  too young/old for treatment
    • Identify duplicate charges on patient bills
    • Find doctor and patient with same address
  • Claims Fraud
    • Identify duplicate cliams
    • Review submission of multiple/inflated claims
    • Find fraudulent family members: i.e., five dependent children born within a two year period.
    • Highlight incorrect gender specific treatments
    • Flag mutually exclusive procedures: e.g. if appendix removed on 01/10/14, then it would be impossible to have appendicitis on 01/02/15.
    • Highlight failure to disclose pre-existing condition (where applicable)
  • Life Insurance Fraud
    • Determine patterns of overpayment of premiums
    • Review transaction payments comprising more than one type of payment instrument
    • Report multiple accounts to collect funds or payment to beneficiaries
    • Report purchase of multiple products in a short period of time
    • Review beneficiaries with multiple policies
    • Isolate transactions for follow-up where employees are beneficiaries
    • Determine agents/brokers with statistically high numbers of claim payouts
    • Calculate benefit payments paid for lapsed policies
    • Find policy loans that are greater than face value
    • Report unauthorized policy changes
    • Identify missing, duplicate, void or out-of-sequence check numbers

Cutting-Edge Fraud & Risk Analytics Expertise

Experfy provides the world's most prestigious talent on-demand

Works at Ernst & Young
Senior Enterprise Intelligence - Advanced Analytics
Worked at ING
Quantitative Risk Analyst
Worked at Enova Financial
Advanced Analytics Manager

Request a Free Consultation

Tell us about your business problem and we help you define it further.

The Harvard Innovation Lab

Made in Boston @

The Harvard Innovation Lab