deploying analytics with a rules-based infrastructure...challenge: operationalize fraud models...
TRANSCRIPT
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Deploying Analytics
with a Rules-Based
Infrastructure
James Taylor, CEO
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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
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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
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©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
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Zero value analytics are easy
©2011 Decision Management Solutions 5
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The operation was a
success…
But the patient died
“
”
6 ©2011 Decision Management Solutions
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Making information more
readily available is
important, but making
better decisions based on
information is what pays
the bills.
“
”
7 ©2011 Decision Management Solutions
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©2011 Decision Management Solutions 8
What is a decision?
Data is gathered, considered, analyzed
A choice or selection is made
That results in a commitment to action
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Operational analytics are
hard(er)
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Different kinds of decisions
©2011 Decision Management Solutions 10
Economic impact Low High
Type
Strategy
Tactics
Operations
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Analytic power in operational decisions
©2011 Decision Management Solutions 11
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
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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
12 ©2011 Decision Management Solutions
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Insights must drive action
©2011 Decision Management Solutions 13
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Time to deploy models matters
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The three legged stool
©2011 Decision Management Solutions 15
Business
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Case: Varolii
©2011 Decision Management Solutions 16
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
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Introducing business rules
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What are business rules?
… statements of the
actions you should take
when certain business
conditions are true.
“
”
18 ©2011 Decision Management Solutions
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©2011 Decision Management Solutions 19
Business rules drive decisions
Decision
History
Experience
Policy Regulations
Legacy
Applications
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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
20 ©2011 Decision Management Solutions
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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”
21 ©2011 Decision Management Solutions
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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
22 ©2011 Decision Management Solutions
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©2011 Decision Management Solutions 23
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
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Deploying analytics with business rules
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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
25 ©2011 Decision Management Solutions
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©2011 Decision Management Solutions 26
Integrate operational and analytic
Operational
Systems
Analytic
Systems
Predictive Analytics
Business Rules
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©2011 Decision Management Solutions 27
Association rules speak for themselves
If basket contains Hats
AND basket contains Socks
THEN offer category is Active Accessories
Screenshots courtesy of KXEN
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©2011 Decision Management Solutions 28
Deploying a decision tree
Screenshots courtesy of IBM
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©2011 Decision Management Solutions 29
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
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Deploying a scorecard
Screenshots courtesy of FICO™
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©2011 Decision Management Solutions 31
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
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©2011 Decision Management Solutions 32
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
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©2011 Decision Management Solutions 33
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….
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©2011 Decision Management Solutions 34
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
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From analytics to decision management
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©2011 Decision Management Solutions 36
Don’t start by focusing on the data
Derived information
Analytic insight
Better decision
Available data
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Start by focusing on the decision
Derived information
Analytic insight
Better decision
Available data
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Decision Discovery
Decision Services
Decision Analysis
38 ©2011 Decision Management Solutions
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
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©2011 Decision Management Solutions 39
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
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Wrap Up
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©2011 Decision Management Solutions 41
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
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Action Plan
Identify your decisions before analytics
Adopt business rules to implement analytics
Bring business, analytic and IT people together
©2011 Decision Management Solutions 42