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Text Mining Insurance Losses – Video

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STATISTICA Decisioning Platform(TM) Integrates Predictive Analytics into Organizations’ Business Processes and Decision Making

StatSoft announces the STATISTICA Decisioning Platform™ – a new decision support technology that provides a new, enhanced platform for StatSoft decision support solutions for Banking, Insurance, and Manufacturing. It is an extension of the STATISTICA Enterprise analytics software platform, which integrates predictive analytics, text mining, and a rules engine to deliver recommendations, results, and guidance to front-line workers and decision makers within the respective departments and business units of an organization.

The proactive and on-demand recommendations achieve improved performance, product quality, customer satisfaction, market share, and other organizational objectives. The STATISTICA Decisioning Platform™ includes user personalization, a “workbench” for predictive analytics and text mining for quantitative analysts, management and versioning of predictive models, a Rules Builder™ for composing, testing, and deploying decision rules, and high performance STATISTICA Enterprise Server software for off-loading predictive model-building and scoring.

Predictive modeling is omnipresent across all aspects of commercial and government organizations, including the marketing, sales, manufacturing, and service functions. The rapid growth of data from various sources describing in detail critical aspects of the environment in which an organization operates, and processes that make an organization successful, have elevated predictive modeling to become a critical business activity. The STATISTICA Decisioning Platform™ guides decision making throughout an organization by “pushing out” recommendations and integrating them directly in core line-of-business systems – relevant insights delivered in a timely fashion to the people who need them in a format that empowers them to act upon those insights.

The STATISTICA Decisioning Platform™ provides business analysts with a flexible Rules Builder™ for defining and reviewing business rules. The Rules Builder packages a powerful set of logical primitives for defining the business rules. These Rules become reusable templates in a workflow workspace that are stored and managed under access control permissions and versioning/history in the STATISTICA system so that questions such as “Why was this rule changed?,” “Who changed it?,” and “What were the applicable rules in place on January 1, 2011?” are all possible to answer (and also to meet regulatory requirements). These Rules nodes can be re-used and applied across different processes, product lines, etc., when that is relevant. STATISTICA Rules Builder also contains powerful tools to accelerate the sometimes challenging work of debugging and validating rules by enabling business analysts to simulate scenarios to check and confirm, for example, that their rules definitions match their organization’s business requirements.

The leading-edge capabilities of the STATISTICA Decisioning Platform™ provide organizations with a wide variety of business benefits.  For example, the ability to:

Financial Services:

  • Reject fewer credit applications and reduce default rates
  • Increase profit with high-risk products such as consumer sales financing on a mobile platform at the point of sale

Insurance:

  • Manage both subrogation and fraud propensity within a single workflow
  • Estimate claim complexity and reserve requirements based on capturing a few key variables

StatSoft, Inc., founded in 1984, is one of the largest global providers of analytic solutions with offices in 30 countries worldwide. StatSoft’s flagship product, STATISTICA, is the enterprise predictive analytics platform for deploying analytic applications across departments, sites, and organizations.

STATISTICA Data Miner Predictive Modelling Solutions for the Insurance Industry

Life, Disability, Automotive, Health, Property and Casualty, etc.

Companies in the insurance industry are using STATISTICA Data Minerto be more effective and competitive in the utilization of historical data, using the latest predictive modelling and data mining approaches to recognize patterns within terabytes of data. STATISTICA Data Miner allows companies to predict trends in customers’ behaviours and responses, claims, and losses.

Major successes and savings have been achieved by companies using STATISTICA Data Miner for predictive modelling for rate making, fraud detection, and customer segmentation.

Areas of Application

Rate making

STATISTICA Data Miner identifies the most important root causes in the frequency and magnitude of historical losses. Predictive Models relating these primary factors to the frequency and magnitude of losses are then used to update rate tables accordingly, making the insurers more accurate and competitive in their policy rates when compared to more traditional rate making approaches. In the past, General Linear Models were the industry standard approach. Now, more effective prediction of losses is achieved through the use of predictive modelling techniques such as recursive partitioning (i.e., “tree methods“). 

Customer segmentation

STATISTICA Data Miner‘s Clustering module may be used for customer segmentation, by grouping the entire customer base into clusters, identified on the basis of various demographic and behavioural factors. These clusters can then be used for a variety of predictive modelling applications to determine the efficacy of the clusters in predicting outcomes of interest. 

Fraud detection

Claims fraud is a significant and costly concern, costing insurance companies several billion dollars annually. Losses due to fraud have increased dramatically in the past ten years. Despite actions by insurance companies, a large amount of fraud remains undetected.

STATISTICA Data Miner helps the insurance company anticipate and quickly detect fraud and take immediate action to minimize costs. Through the use of sophisticated data mining tools, millions of claims can be searched to spot patterns and detect even subtle variations in billing practices, by analyzing above normal payoffs along different factors like geographical region, agent, and insured party. 

Association Rule GraphSpecifically for health insurance, STATISTICA Data Miner‘s Associations Rules may be used to analyze claim forms. Using the Associations Rule module, the payer will be able to find relationships among medical procedures performed together, patterns in diagnoses and procedures across providers, etc.

PDF Insurance Fraud Detection Case Study

Claims analysis

STATISTICA Data Miner helps users understand subtle business trends in claims, which would have been otherwise difficult to spot.

STATISTICA Generalized Linear Models has the Tweedie distribution. This distribution is a flexible predictive modelling option. It can include exact zero and continuous data.

Predict which customers will buy new policies

STATISTICA Data Miner provides the insurance firm with reporting, tracking, and analysis tools to identify trends. Sequential pattern mining functions are powerful and can detect sets of customers associated with frequent buying patterns to inform future sales and marketing campaigns and tactics.

PDF STATISTICA Data Miner in the Insurance Industry, White Paper