Life Insurance

In many ways, life insurance has not changed much over decades except for the utilization of blood tests during the underwriting process and recent patterns in underwriting fraud. The things that have changed are the increased competition among life insurance companies and the impact of lower yields from investments. Both these factors demand more accurate and aggressive underwriting decisions and better integration between claims payouts and the links to the underwriting decisions for the respective policies.

The challenges facing the life insurance industry are varied and complex. For example, fraud is a costly source of lost revenue that can be minimized with data mining techniques by finding atypical claims. Successful insurance companies are moving past simple rules based approaches to fraud detection toward more sophisticated, predictive tools to proactively detect systematic characteristics of fraudulent transactions and flag them in real time. These companies are using a combination of traditional approaches for predictive modeling (e.g., linear modeling) and the latest developments in advanced analytics and data mining to deliver more accurate underwriting models. Utilizing customer and claims data, the models accurately identify the most important factors responsible for historical claims. Another important emerging analysis trend is the analysis of losses based on their original underwriting decisions.


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.
  • 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.

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2300 East 14th Street
Tulsa, Oklahoma, 74104
(918) 749-1119