Property and Casualty Insurance

In the competitive environment of P&C insurance, it is more important than ever to reduce costs; to focus acquisition, retention and expansion tactics on high-value customers; and to deliver the right level of service to suit each particular claim. With STATISTICA Decisioning Platform®, predictive analytics and reporting solutions for P&C Insurance applications enable insurers to utilize data about claims, policies, customers, and third party data sources so they can improve underwriting decisions, detect fraud, identify opportunities for subrogation, update reserve estimates, assign the right service level to claims, and segment customers across all product lines (e.g., auto, worker’s compensation, home, commercial property, disability, and any other specialized product lines).

StatSoft has developed the Predictive Claims Flow®, incorporating predictive modeling at each stage of the lifecycle of a claim. From the first notice of loss through to closure, claim data is constantly changing. As new information about a claim becomes available, the Predictive Claims Flow automatically scores the probability of fraud, updates the predicted reserve estimate, and predicts claim complexity to determine whether the claim should be assigned to a more senior adjuster. It also identifies opportunities for subrogation and determines the right level of servicing of the claim. At each stage, alerts and updates are provided with minimal human intervention from adjusters, SIU managers and claim personnel, or any other key stakeholders in the overall claims adjudication process.

predictive claims score control

STATISTICA Solution

Insurance Fraud Whitepaper Thumb

Insurance Fraud
White Paper

  • Cutting-edge Predictive Analytics: STATISTICA provides a wide variety of basic to sophisticated algorithms to build models which provide the most lift and highest accuracy for fraud detection, prediction of expected outcomes and more.
  • Innovative Data Pre-processing Tools: STATISTICA provides a very comprehensive list of data management and data visualization tools.
  • Integrated Workflow: STATISTICA Decisioning platform provides a streamlined workflow for powerful, rules-based, predictive analytics where business rules and industry regulations are used in conjunction with advanced analytics to build the best models
  • Real-time Predictions and Integration with Claims Management Systems: The STATISTICA Solution is optimized for performing real-time predictions for supporting instant underwriting decisions or evaluating a claim as new information is made available.
  • Reporting: Aggregated summary reports and configurable dashboards provide valuable information both to management and for tracking key performance indicators related to each functional area.
  • Reason Codes: In addition to predictions and recommendations, the STATISTICA solution provides information about the reasons for the decision both for the awareness of key personnel and regulatory reasons, when applicable.
  • Integration with Data Sources: The STATISTICA solution simplifies access to data from your company’s customer database, policy database, claims database, and third party data sources.
  • Integration with Policy Rules: STATISTICA includes very flexible tools for integrating segmentation rules, policy rules, or overrides into the model-based scoring process.
  • Prioritizing Fraud Investigation. With advanced fraud detection techniques in STATISTICA Data Miner, claims can be rank ordered by their likelihood of fraud, helping to prioritize claims to be investigated.
  • Ad Hoc Analytics and Text Mining: Apply advanced automatic text mining methods to classify and cluster insurance claim reports; then use ad hoc drill-down methods to detect emerging trends. STATISTICA Text Miner offers a large selection of retrieval, preprocessing, and analytic/interpretive procedures for unstructured text data and Web pages.

Included Technologies

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Contact Us

StatSoft, Inc
2300 East 14th Street
Tulsa, Oklahoma, 74104
(918) 749-1119
info@statsoft.com