Deploying Analytics with a Rules-Based Infrastructure...Challenge: operationalize fraud models Legacy claims system uses fixed business logic Analytics models predict provider fraud

Deploying Analytics

with a Rules-Based

Infrastructure

James Taylor, CEO

Your presenter

CEO of Decision Management Solutions

Decision Management Solutions works with clients to improve their business by applying analytics and analytic technology to automate and improve decisions

Spent the last 8 years developing the concept of Decision Management

20 years experience in all aspects of software including time in FICO, PeopleSoft R&D, Ernst & Young

2 ©2011 Decision Management Solutions

1 2 3

4 5 6

AGENDA

Zero value

analytics are easy

Operational

analytics are

hard(er)

Introducing

business rules

Deploying

analytics with

business rules

Decision

Management

Wrap Up

©2011 Decision Management Solutions 4

The one slide you need

It is easy to have analytic success without creating business value

It is especially easy to fail to deliver business value when focused on operational analytics

Business rules and a business rules management system provide an ideal platform for analytics

Decision Management ties analytics and business rules together in an effective framework

Zero value analytics are easy


The operation was a

success…

But the patient died

“

”


Making information more

readily available is

important, but making

better decisions based on

information is what pays

the bills.

“

”



What is a decision?

Data is gathered, considered, analyzed

A choice or selection is made

That results in a commitment to action

Operational analytics are

hard(er)

Different kinds of decisions


Economic impact Low High

Type

Strategy

Tactics

Operations

Analytic power in operational decisions


How do I…

prevent this customer from churning?

convert this visitor?

acquire this prospect?

make this offer compelling to this person?

identify this claim as fraudulent?

correctly estimate the risk of this loan?

It’s not about “aha” moments

It’s about making better operational decisions

Operational decisions are different

High Volume

Low Latency

High Variability

Ensure Compliance

Personalize Manage Risk

Unattended Operation

Self-Service Straight Through

Processing

After Smart (Enough) Systems, Prentice Hall 2007


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Insights must drive action


Time to deploy models matters


The three legged stool


Business

Case: Varolii


Personalized, automated consumer communication SaaS

Challenge: apply advanced analytics

Analyze past behavior of consumers

Drive recommendations to their clients

Actionable and automatic

Solution

Identify key decisions

Analytically derive new rules based on past success

Integrate client rules with analytic rules

Introducing business rules

What are business rules?

… statements of the

actions you should take

when certain business

conditions are true.

“

”



Business rules drive decisions

Decision

History

Experience

Policy Regulations

Legacy

Applications

public class Application {

private Customer customers[];

private Customer goldCustomers[];

...

public void checkOrder() {

for (int i = 0; i < numCustomers; i++) {

Customer aCustomer = customers[i];

if (aCustomer.checkIfGold()) {

numGoldCustomers++;

goldCustomers[numGoldCustomers] = aCustomer;

if (aCustomer.getCurrentOrder().getAmount() > 100000)

aCustomer.setSpecialDiscount (0.05);

}

}

}

Unmanageable business rules


Manageable business rules

Smart (Enough) Systems, Prentice Hall June 2007. Fig 4.3

If customer is GoldCustomer

and Home_Equity_Loan_Value is more than $100,000

then college_loan_discount = 0.5%

If member has greater than 3 prescriptions

and prescription’s renewal_date is less than 30 days in the future

then set reminder=“email”

If patient’s age is less than 18

and member’s coverage is “standard”

and member’s number_of_claims does not exceed 4

then set patient’s coverage to “standard”


Decision

Service

A Business Rules Management System

After Smart (Enough) Systems, Prentice Hall June 2007. Fig 6.6

Design

Tools Rule

Management

Applications

Rule Engine

Operational

Database

Rule

Repository

Production

Application

Validation and

Verification

Testing

Deployment



Case: Health Management

Personalized health recommendations

Challenge: multiple sources of tailoring

Medical research

Data mining of participant and outcome information

Best practices in personal health

Solution

Replace Java code with JBoss Drools

Implement best practices as decision tables

Decision trees from analytic results, medical research

Implement as additional decision tables

Deploying analytics with business rules

Business rules and analytics

Broader set of data for business rules to act on

Association rules as business rules

Decision trees as business rules

Predictive (risk) scorecards as business rules



Integrate operational and analytic

Operational

Systems

Analytic

Systems

Predictive Analytics

Business Rules


Association rules speak for themselves

If basket contains Hats

AND basket contains Socks

THEN offer category is Active Accessories

Screenshots courtesy of KXEN


Deploying a decision tree

Screenshots courtesy of IBM


Scorecards are a powerful tool

Years Under Contract

1 0

2 5

More than 2 10

Number of Contract Changes

0 0

1 5

More than 1 10

Value Rating of Current Plan

Poor 0

Good 10

Excellent 20

Score

Reason Codes

Explaining results

Transparency

It is really clear how a score card got its result

Compliance

Easy to enforce rules about use of specific attributes

Simplicity

Easy to use and explain

Easy to implement

Although not necessarily easy to build

30


Deploying a scorecard

Screenshots courtesy of FICO™


The power of business rules

Visible, business friendly analytic implementation

Avoiding the mistrust of a “black box”

Platform for all three groups to share

All three legs can participate and collaborate

Time to deploy

A BRMS handles much of the complexity

Support for defining actions

Wrap into decisions


Integration options

Native model execution

Generate code or SQL

Let the rules call the models when they need them

Models as rules

Manual or automatic import of models

Create rules and rule artifacts that are executable

Database scoring

Traditional

Separate services

Let the rules call scoring services


Cautions

PMML variations still exist

Make sure you understand limitations and issues

Variable creation and PMML

PMML 4.0 supports variable creation

Most tools do not export variable definitions

Matching data

Operational and analytic data are not always the same

From a flat analytic data set to object models

Once a model is in rules it can be edited….


Case: Major medical insurer

Dental Claims Processing

Challenge: operationalize fraud models

Legacy claims system uses fixed business logic

Analytics models predict provider fraud

Only currently applied after the fact – pay and chase

Solution

Add a rules-based decision service to review claims

Add rules to define new variables

Make analytics visible and reviewable by experts

Easily add judgment as well as analytics

From analytics to decision management


Don’t start by focusing on the data

Derived information

Analytic insight

Better decision

Available data


Start by focusing on the decision

Derived information

Analytic insight

Better decision

Available data

Decision Discovery

Decision Services

Decision Analysis


Business

Process

Legacy

System Website

Enterprise

Application Cloud Mobile

Business

Rules

Decision

Service

Ask for a

decision

Get an

action

Predictive

Analytics

External

Data

Segmentation

Clustering

Risk

Propensity

Policy

Regulation

Best Practices

Know-how

Data

New approaches

Refinements


Case: Fiserv

Core banking systems for mid-sized banks

Challenge: create value-add analytic offering

Core functionality perceived as commodity

Analytics delivers unique value

Customers value (but don’t understand) analytics

Solution

Identify key decisions

Build rules-based, cross-channel decision services

Automate analytic model creation and deployment

Empower customers to “own” these decisions

Wrap Up


The one slide you need

It is easy to have analytic success without creating business value

It is especially easy to fail to deliver business value when focused on operational analytics

Business rules and a business rules management system provide an ideal platform for analytics

Decision Management ties analytics and business rules together in an effective framework

Action Plan

Identify your decisions before analytics

Adopt business rules to implement analytics

Bring business, analytic and IT people together


Thank you!

James Taylor, CEO [email protected]

www.decisionmangementsolutions.com

mailto:[email protected]

Documents

Deploying Analytics with a Rules-Based Infrastructure...Challenge: operationalize fraud models Legacy claims system uses fixed business logic Analytics models predict provider fraud