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BETTERDECISIONING

STATISTICA Decisioning PlatformTM

for Financial Services

Combining Predictive Analytics, Text Mining,

and Rules Management for Reducing

Credit Risk and Increasing Profits

Financial Services companies face the challenging task of making credit decisions in a complex and uncertain environment.

Decisions regarding credit limits and approvals must be

compliant with regulatory and policy rules, reflect known

segmentation (rules) among products and customers, and

incorporate standard as well as advanced and emerging

predictive risk modeling techniques, such as text mining.

The STATISTICA Decisioning Platform™ for Financial Risk

Management is a proven solution at some of the largest

and most progressive financial institutions in the world.

The STATISTICA Decisioning Platform provides the most

effective platform for financial services organizations

to combine structured and unstructured data, manage

simple and complex segmentation (pre-scoring) and policy

(post-scoring) rules, and to incorporate predictive models

and conditional scoring logic into efficient managed

decisioning flows. These flows can be directly deployed to

batch or real-time scoring environments without requiring

any “re-programming.”

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 online or other real-time applications will be

more responsive.

The STATISTICA Decisioning Platform addresses the typical array of challenges,

and scales to financial service organizations of all sizes:

• 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, flexible rules and rules management, and leveraging

non traditional data sources using techniques such as text mining

• 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,

LOB managers and workers, etc.)

• that combines predictive analytics, text mining, and rules to cover all aspects of

evaluating and scoring claims, customers, and applicants. Text mining is for making

use of adjuster notes, medical reports, and other documents. Rules integrated with

predictive models translate predictions into business decisions.

“The bottom line is we need rules combined with predictive

analytics and text mining to gain more profitable customers

and decrease our risks. Some credit decisions are completely

driven by rules. Other processes take the output from

predictive models and translate them into credit decisions and

other offers. Also, rules govern our compliance with relevant

regulations. In STATISTICA Enterprise, rules and models for

different product lines are easy to manage, and applications

are scored in less than a second!”Senior VP of Risk, Major European Bank

Include:• Business Rules• Segmentation Rules• Regulatory Requirements

Model:• Credit Default Probability• Time To Default• Credit Limits

Declined

Compute andreport reasonfor rejection

ReportCredit Limit

Prepare:• Data• Predictor Selection• WOE Coding• Segmentation

Deploy:Repository forBusiness Rulesand Models

Approved

Retrieve:Historical Data

Application Data,Credit History

Build:Base Models

Applicationfor Credit

Business Consumer

AutomaticDecisioning

STATISTICA Enterprise – The server platform for delivering analytic and business intelligence applications to departments and divisions within the enterprise via centrally-managed queries, analysis templates, report templates and dashboards.

STATISTICA Text Miner – A large selection of retrieval, pre-processing, and analytic/interpretive mining procedures for unstructured text data and web pages. Optional specific solution packages.

STATISTICA Data Miner – The most comprehensive selection of data mining solutions for the enterprise, with powerful model development and deployment (solution publishing) tools and database/data warehouse integration. Optional solution packages for specific applications and domains.

STATISTICA Live Score – The server platform for integrating predictive modeling into business processes and line-of-business applications through highly-efficient, real-time scoring via predictive models managed using STATISTICA Data Miner and STATISTICA Text Miner.

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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

Within 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 and risk modelers have access to the full suite of powerful

predictive modeling options.

– Business analysts define and verify the business rules and conditional scoring logic

for which predictive models to apply to which processes/products, and for when/how

to override the predictions from the models due to other business rules or regulatory

guidelines

– Lines of business workers see results and recommendations specific to their objectives

and business processes.

– Risk analysts can create and schedule the standard model evaluation, population

stability, and other reports required to monitor and document the quality of the

decisioning process.

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 is approved and meets regulatory requirements.

Deployment to Production

A typical bottleneck for efficient utilization of decisioning

flows to support risk management is the time required

to deploy models to the production environment. In

the STATISTICA Decisioning Platform, this process does

not require any reprogramming of data preprocessing

steps, rules logic, or prediction models. Instead, entire

decisioning flows, and the references to rules, models,

and scoring logic that they contain, can be moved from

the development to the system test environment, and

then to the production environment via simple point-

and-click operations by authorized users. Decision flows

and the components they reference are managed as

versioned templates and objects that can be moved

across environments and do not have to be recreated or

reprogrammed.

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

offline. 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 prospects most likely to become

profitable customers.

© Copyright StatSoft, Inc., 1984-2012. StatSoft, StatSoft logo, STATISTICA, Decisioning Platform, and Better Decisioning are trademarks of StatSoft, Inc.DPFIN201204r01

US Headquarters:StatSoft, Inc.2300 East 14th StreetTulsa, OK 74104Phone: (918) 749-1119Fax: (918) 749-2217Email: info@statsoft.comStatSoft.com

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Bulgaria: StatSoft Bulgaria Ltd.

Czech Rep.: StatSoft Czech Rep. s.r.o.

China: StatSoft China

Egypt: StatSoft Middle East

France: StatSoft France

Germany: StatSoft GmbH

Hungary: StatSoft Hungary Ltd.

India: StatSoft India Pvt. Ltd.

Israel: StatSoft Israel Ltd.

Italy: StatSoft Italia srl

Japan: StatSoft Japan Inc.

Korea: StatSoft Korea

Netherlands: StatSoft Benelux BV

Norway: StatSoft Norway AS

Poland: StatSoft Polska Sp. z o.o.

Portugal: StatSoft Ibérica Lda

Russia: StatSoft Russia

Spain: StatSoft Ibérica Lda

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Sweden: StatSoft Scandinavia AB

Taiwan: StatSoft Taiwan

UK: StatSoft Ltd.

About STATISTICA and StatSoft

StatSoft Inc. is one of the largest global providers of analytic software. STATISTICA is an enterprise-wide, scalable,

Web-enabled system that is used by a variety of industries in mission-critical applications where predictive modeling

helps increase productivity and bottom-line profitability, while also helping protect life, improve safety, and save the

environment.

While easier to use and more cost effective than its competitors, STATISTICA is one of the most technologically advanced

tools in the industry, with uncompromising attention to detail and overall quality, which ensures success for its users.

For two consecutive years, STATISTICA has been recognized as the primary data mining tool of choice in an annual survey

conducted by Rexer Analytics of corporate and consultant data miners. STATISTICA was also recognized for receiving the

highest satisfaction ratings among those surveyed.

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Decision Rules

Predictive analytics requires both predictive modeling

and decision rules. The two work hand-in-hand. An

organization’s quantitative analysts can use the predictive

modeling and data mining approaches in the STATISTICA

platform to detect and capture patterns in their historical

data. Those patterns have a business context. For

credit risk modeling, decision rules subset and transform

the applicant’s data into segments of interpretable,

transparent customer groups, and policy (post-scoring)

rules automate the interpretation of the risk prediction

into specific next steps for the application, as well as

reason scores to communicate back to the applicant.

By incorporating STATISTICA’s new models, profits can increase 80% or more with improved acceptance rates, while defaults remain at approximately the same level.