Fraudulent Claims
by Tableau
Description
This Tableau Accelerator allows you to:
- Assess & Reduce your exposure to Fraudulent Claims
- Identify top offenders
- Deep-dive at Broker level of detail
- Drill-back at “Claim #” level of detail, directly in your Claim Application and take immediate actions
Answer key business questions
- How are we exposed to Fraudulent Claims?
- Which Product Groups are affected the most by Fraudulent Claims?
- Which Brokers have exposed us most to Fraudulent Claims?
Monitor and improve KPIs
Claims
- Number of Claims: Total number of claims opened over the period
- Number of Suspected Fraud Claims: Total number of suspected fraudulent claims over the period
- Suspected Fraud Claims %: Share of claims which are suspected to be fraudulent (expressed in %)
- Average Policy Limit: Average of highest amounts the insurer will pay for claims covered by insurance policies over the period (expressed in currency)
Claims Amount
- Total Suspected Fraud Amount: Total amount paid for suspected fraudulent claims (expressed in currency)
- Suspected Fraud Amount %: Share of paid amount which is suspected to be fraudulent (expressed in %)
- Total Claims Amount: Total amount of compensation paid over the period (expressed in currency)
Required attributes
- Event Date (date): Date on which the event causing the damage or loss occurred
- Claim Number (string): Claim Unique Identifier
- Product Group (string): Group of the insurance product (Professional, Property, Technology, Vehicle, ...)
- Broker (string): Broker identified for this insurance policy, if any
- Policy Holder (string): Owner of the insurance policy
- Suspected Fraud Flag (string): Determines whether a claim is suspicious. Expected values: “Y”, “N”; “Y” means that the claim is suspicious.
- Policy Limit (numeric): The highest amount the insurer will pay for a claim that an insurance policy covers
- Paid Claim Amount (numeric): Total paid amount by the insurance provider for the claim
Features
Supports data mapping