For Insurance Companies
Detect more fraudulent activity than ever before.
Insert advanced analytics into the process, in addition to rules engines.
Process all claims data (not just a sample) through rules and analytical models in real time or in batch.
Use customized anomaly detection methods to detect previously unknown schemes.
Spot linked entities and crime rings, which can help stem larger losses.
Overcome poor data quality issues associated with imperfect matching and highly linked entities.
Prevent fraud losses before settlement.
Stop fraud before claims are paid using online real- time scoring or daily batch scoring.
Detect loss padding in similar claims using anomaly detection and loss comparisons.
Identify repeat offenders and more accurately score incoming claims by searching databases of known fraudsters and capturing all fraud outcomes, referrals and suspects within the system for reuse.
Uncover insider or collusive fraud by integrating staff data and audit records that show who handled which claims.
Apply risk- and value-based scoring models to prioritize output before presenting to investigators.
Insert analytical models into your process workflow, enabling real-time access to information.
Lower loss-adjustment expenses.
Greatly reduce false positives using a sophisticated fraud scoring engine.
Improve investigator efficiency with advanced case management tools.
Increase investigator ROI per investigator by prioritizing higher value networks and conducting more
efficient and accurate investigations.
Capture all claims settlement amounts within the system for reuse with similar claims in the future.
Gain a consolidated view of fraud risk.
- Identify cross-brand/product fraud by seeing customer claims and policies for all lines of business.
- Continuously improve models and adapt the system as needed to address changes in fraud trends.
- Understand new claim threats and prevent substantial losses early using social network diagrams and
- sophisticated data mining capabilities.
- Improve your competitive position.
- Generate fewer false positives, which leads to greater customer satisfaction for legitimate customers.
- Drive fraudsters to target other insurers with less diligent and effective fraud detection methods.
- Satisfy regulatory and rating agency requirements through enhanced fraud management.
Fraud data management
- Consolidates historical data from internal and external sources for fraud analysis and investigation.
- Includes data quality tools that can reduce or eliminate data inconsistencies or redundancies.
- Supports integration with third-party fraud applications.
Rule and analytic model management
- Enables you to logically manage rules, models and alerts for investigators.
- Allows you to create and manage business rules, analytical models and known fraudster lists.
- Lets you maintain simple or complex routing and suppression rules.
Detection and alert generation
- Scores claims in real time with an online scoring engine that combines business rules, anomaly etection and advanced analytic techniques.
- Calculates the propensity for fraud at first notice of loss, then rescores claims at each settlement stage as new claims data is captured.
- Goes beyond claims fraud detection by deploying at policy inception to prevent fraudsters from taking out policies in the first place.
- Assembles alerts from multiple monitoring systems, associates them with common claimants and gives investigators a more complete perspective on the risk of specific claimants.
- Calculates risk scores based on specific characteristics of the activity, and includes transparent reason codes.
- Prioritizes alerts and automatically assigns them to appropriate team members based on user-set rules and requirements.