STATISTICA Decisioning Platform®

 

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STATISTICA Decisioning Platform is StatSoft’s solution to help your organization make decisions more efficiently utilizing predictive analytics. Obstacles that impede business objectives often provide the best opportunities to develop more informed business decisions. By applying predictive analytics to determine patterns of historical data, a business enterprise can better refine and achieve its objectives for customer retention, customer acquisition, employee performance, decreased risk, and increased profitability.

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Decisioning Platform General Overview

Powerful. Rules-based. Predictive.

What is truly groundbreaking about the STATISTICA Decisioning Platform is its complete integration of the 7 key attributes for effective use of predictive analytics within an organization:

  1. Decision Rules – the management and execution of business rules based on:
    1. business context (e.g,. which customers to target)
    2. regulations (e.g., whether a communication can be made in your state)
    3. interpretation of predictive model outcomes and what to do about them (e.g., when probability of fraud exceeds .5 and the policy initiation date is less than 6 months prior to today's date)
  2. Predictive Modeling – the utilization of your organization's historical data to discriminate, cluster, segment, and forecast effectively using the latest techniques in STATISTICA Data Miner
  3. Model Management – the efficient deployment, management, and monitoring of predictive models via STATISTICA Enterprise Server
  4. Text Mining – the utilization of unstructured data combined with numeric data
  5. Scoring Server Batch and Real-Time Execution – employing predictive models either in batch mode (e.g., in a data mart or data warehouse) or in real-time scoring applications (such as an online credit scoring application), using the scalable Web Services-based STATISTICA Live Score
  6. Open Architecture and Automation – the flexibility to integrate with existing systems using industry standards (e.g., OLE DB, ODBC, etc.) and the STATISTICA Application Programming Interface (API)
  7. Data Visualization – the understanding of what the predictive models are doing and why, through graphical monitoring

Decisioning Platform Workspace

The STATISTICA Decisioning Platform is a proven solution that provides an effective platform to:

  • combine structured and unstructured data,
  • manage simple and complex segmentation (pre-scoring) and policy (post-scoring) rules, and
  • incorporate predictive models and conditional scoring logic into efficient, managed decisioning flows that can be directly deployed to batch or real-time scoring environments without requiring any "re-programming."

Decisioning Platform Workspace Selector

Delivering Predictions to the Right People

The STATISTICA analytics suite of applications efficiently delivers accurate predictive models for improved decision-making throughout an organization. There are several components to make this happen:

User Personalization

STATISTICA Enterprise Login Dialogue BoxWithin an organization, personnel with differing skills and responsibilities collaborate to achieve an outcome. STATISTICA includes user personalization, so that differing user groups see the data, capabilities, user interfaces, options, and workflows specific to their areas of responsibilities. For example:

  • Quantitative analysts have access to the full suite of powerful predictive modeling options.
  • Business analysts define and verify the business rules for which predictive models apply to which processes/products, and for when/how to override the predictions  due to other business rules or regulatory guidelines.
  • Lines of business workers see results and recommendations specific to their objectives and business processes.

Model Management

Within an organization, there are many areas for applying predictive analytics. For example, predictive models can deliver recommendations for different products, departments, customers, and so on.  STATISTICA Decisioning Platform makes it easy for the quantitative analysts who are responsible for the verification, deployment, and ongoing management of these models. Models are managed in one central location, on the STATISTICA Server. Models are managed with versioning and history so that analysts have complete control over which version meets the regulatory requirements and is approved.

Scoring

In all the ways in which predictive analytics can be utilized, there are different business needs that require different types of scoring of data. In some cases, real-time scoring is needed, such as when the information on an insurance claim changes or when an instant credit decision is required. In other cases, a set of data, in a file or database or data warehouse, needs to be scored off-line. For example, a set of prospective customers is scored based on their propensity to purchase a new product, so that customer service personnel will focus time and attention on the most likely prospects who will become profitable customers.

Decision Rules

Predictive analytics requires both predictive modeling and decision rules working hand-in-hand. An organization’s quantitative analysts use STATISTICA’s data mining approaches to detect and capture patterns in their historical data. Those patterns have a business context. In some cases, there are specific rules that influence or supersede the recommendations from the predictive models, such as business rules, governing laws, and other factors.  For example, in North America, insurance rules differ by state. Based on the characteristics of a claim, a predictive model may predict a high likelihood of subrogation, but business rules would also be employed to determine whether subrogation is possible in the particular state in which the claim was filed.

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Decisioning Platform For Financial Services

A Powerful Tool for Financial Services

With STATISTICA, the tasks of building and deploying scorecards, scoring models, and flows can now be completed in a fraction of the time, allowing more models to be managed and routinely recalibrated. More customers can be approved for credit with higher limits, without increasing the default rate. Batch scoring of all customers and accounts will be faster, and real-time scoring for on-line or other real-time applications will be more responsive.

The STATISTICA Decisioning Platform addresses the typical array of challenges for medium and large financial services organizations:

  • regulatory pressures to provide consistency and transparency in credit risk decisions
  • a wide array of loan products to meet the needs of a variety of customer segments, both in personal and commercial lines
  • demands to increase the profitability of loan products without increased default risk of exposure to losses
  • collaborations between business stakeholders supporting credit products and the quantitative and IT staff responsible for implementing the systems and models for making credit decisions

The STATISTICA Decisioning Platform addresses these needs by:

  • combining predictive analytics, text mining, and flexible rules and rules management to enable consistency and transparency in credit decisions
  • providing an integrated platform in which the predictive models to support a large number of loan products are managed, with access control, versioning, and history, to eliminate the time-consuming and error-prone process of replicating conditional scoring models and rules for deployment
  • delivering a scalable platform that can score large data volumes efficiently, and perform real-time scoring in milliseconds while referencing sequences and combinations of rules and conditional scoring (predictive) models, as well as logic for returning reason codes
  • empowering quantitative analysts with an integrated, flexible workbench of predictive analytics, text mining, data transformations, and graphical data analysis for optimal credit risk modeling

The STATISTICA Decisioning Platform is the only enterprise predictive analytics and decision management software platform:

  • For use across all departments and roles (analysts, adjusters, investigators, IT engineers)
  • That combines predictive analytics, text mining, and rules to cover all aspects of evaluating and scoring claims, customers, and applicants. Text mining is beneficial for making use of adjuster notes, medical reports, and other documents. Rules integrated with predictive models translate predictions into business decisions.

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Decisioning Platform For Insurance

Solid Solutions for Insurance Providers

Insurance companies are utilizing predictive analytics, text mining, and decision rules throughout their organizations to:

  • score claims through their lifecycle for fraud, recovery, complexity, and reserving
  • to improve underwriting
  • to identify and retain their best customers

The STATISTICA Decisioning Platform is the only enterprise predictive analytics and decision management software platform:

  • For use across all departments and roles (analysts, adjusters, investigators, IT engineers)
  • That combines predictive analytics, text mining, and rules to cover all aspects of evaluating and scoring claims, customers, and applicants. Text mining is beneficial for making use of adjuster notes, medical reports, and other documents. Rules integrated with predictive models translate predictions into business decisions.

Why Predictive Analytics and Rules?

Predictive Analytics Insurance Claim Flow DiagramSTATISTICA's Predictive Claims Flow™ can benefit your organization in such areas as:

  • Recovery: Scores claims throughout their lifecycle for probability of recovery, including subrogation opportunities. Some opportunities for recovery can be defined by rules, which ensure compliance with regional laws.
  • Fraud Detection: Automates and standardizes the scoring of claims for fraud through the claims lifecycle. Earlier detection minimizes losses and increases recovery. Text mines adjuster notes, medical reports, and other documents relevant to each claim. Allows the definition of rules to define the threshold for escalating a claim to an investigator.
  • Reserving: Updates estimates as new information is collected about each claim for more accurate reserving.
  • Claims Complexity: Scores claims for expected complexity to assign the claims to the appropriate adjuster to identify opportunities to reduce losses by assigning “high touch” processing and to “fast track” claims that are low complexity.
  • Underwriting: Employs historical claims analysis including text mining to uncover the factors that drive risk and losses.  Improves pricing decisions for each product for more competitive rates and to decrease risk.
  • Sales and Marketing: Determines characteristics of best customers, including profitability and loyalty factors, to improve sales and marketing initiatives.

Example Applications and Outcomes

The ability  to quickly deploy complex decision rules involving sophisticated and continuously updated predictive models against the latest data will have significant business impact. STATISTICA Decisioning Platform delivers solutions for organizations in a variety of industries:

  • Insurance: An insurance company is achieving significant savings in reduced losses by flagging claims that are more likely to involve fraud, and automatically routing those claims to investigators.

  • Banking: A large financial services company was able to empower their loan specialists with the ability to make instant decisions to credit applicants.
  • Risk management: Another large international bank uses the Decisioning Platform for all credit risk scoring, scorecard model management, segmentation, and policy rules in a single platform that unifies models and flows both for highly efficient batch scoring and real-time scoring.
  • Marketing: A major marketing company increases its response rates and increases profits by providing customer service representatives automated guidance based on accurate predictive models and rules, routing the most appropriate and profitable offers to the right prospects.
  • Manufacturing: A manufacturer of complex machinery uses predictive models and flows to monitor the predicted product quality and performance across each step of the manufacturing process. This approach enables a line-of-site view tying raw material characteristics, manufacturing tolerances, and the performance of sub components to performance and quality during final product testing and in the field (warranty claims).

 

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