decision models using dmn and bpmn standards: mortgage recommender

DEVELOPING COMPLEX-ENOUGH DECISION MODELS

USING DMN & BPMN STANDARDS

Gil Ronen [email protected]

Jacob Feldman, PhD [email protected]

OBJECTIVE

Question: Is the new OMG Decision Model and Notation standard (DMN) useful beyond toy problems?

Given our collective experience analyzing, modeling and deploying dozens of Business Rule systems our objective was to explore DMN interactions with existing standards and determine its value-added in the context of a complex-enough business decision

Ronen & Feldman (c) 2014 2

SYNOPSIS

• Setting the stage for the complex-enough business

decision to be modeled

• Introduction to the new OMG Decision, Model &

Notation standard (DMN)

• Interactions between state-of-the-art business

standards for modeling decision logic (OMG DMN

and BPMN)

• End-to-end model validation

• Conclusions


BUSINESS BACKGROUND: MORTGAGE RECOMMENDATIONS

Business Opportunity:

• Lenders offer multiple products and programs

• Lenders support multiple channels

• channels may offer the same product from different

lenders

• Customer touch-points may not be knowledgeable

about the mortgage domain or specific lender products

• Highlighting benefits of different products is time-

consuming and error-prone in a sales setting

Solution:

• Automate mortgage loan recommendations


BUSINESS CASE: OBJECTIVE-BASED MORTGAGE RECOMMENDATION

1. Customer provides objective and skeletal

preferences

2. Generate loan constraints

3. Match loan constraints to lender products

4. Determine base rate

5. Determine risk-based pricing adjustors

6. Determine monthly payment

7. Determine objective-based option ranking

8. Present ranked options to customer


REQUEST/RESPONSE

Request Objective Requested Program Requested Product

Category

Requested Product

Term Requested LTV

Requested Loan

Amount

Lowest Monthly

Payment Non-Prime Fixed 30 87.50 $350,000

Progra

m

Catego

ry

Ter

m Liens LTV 1st LTV 2nd Amount

Mortgag

e

Insuranc

e

Tax &

Insuranc

e

Principle

& Interest

Total

Monthly

Payment

Benefits

Prime Fixed 30 First 87.50% --- $350,000 $175.00 $437.50 $2,017.01 $2,629.51

Corresponding Prime product

carries a lower rate; Requires

qualifying by more stringent

criteria.

Non-

prime Fixed 30 First 85.00% --- $340,000 $170.00 $425.00 $2,123.38 $2,718.38

Price advantage at 85% over

higher LTV; Specific to a

particular lender.

Non-

prime ARM 3/1 First 87.50% --- $350,000 $175.00 $437.50 $2,126.64 $2,739.14

ARM products typically offer

lower rates initially; 3/1 is fixed

for first 3 years.

Non-

prime Fixed 30

First+

Secon

d

80.00% 10.00% $360,000 $0.00 $450.00 $2,364.94 $2,814.94

Avoids Mortgage Insurance;

Scenario includes 2 loans

closing simultaneously.

Non-

prime Fixed 40 First 87.50% --- $350,000 $175.00 $437.50 $2,238.85 $2,851.35

A longer term reduces the

monthly payment.

Non-

prime Fixed 30 First 87.50% --- $350,000 $175.00 $437.50 $2,243.40 $2,855.90 Requested scenario.


EXISTING STANDARD: BPMN

• BPMN = Business Process Model & Notation

• Understanding and communication of internal business procedures in graphical notation

• Highlights collaboration and transactions between business actors (roles and organizations)

• Concerned with temporal aspects (flow, life-cycle)

• Supports business continual improvement (business controls, re-engineering)

• Already incorporates a Business Rules Task in the context of Business Decision Management (in BPMN 2.0)


NEW STANDARD CONTEXT: BDMS

• BDMS = Business Decision Management System

• BDMS is at the center of modern enterprise architectures

• Business decisions affect customer satisfaction, competitive analysis, and profitability in any businesses

• Examples: loan approval, insurance underwriting, customer service tactics, clinical guidelines, risk management, compliance, and many others


NEW STANDARD: DMN

• DMN = Decision Model & Notation

• New OMG standard for decision modeling

• Beta version 1.0 made available Set. 26, 2013

• Target audience primarily business users (work

product modifiable not only by IT)

• Provides constructs to support modeling decisions so

that they can be represented graphically, modeled

by analysts and, optionally, automated

• Compliments BPMN (and CMMN)


DECISION REPRESENTATION COMPONENTS

• Business Process

• Decision Requirements

• Decision Logic


DECISION REQUIREMENT CONSTRUCTS

• Decision Requirements Graph (DRG)

• Decision Requirements Diagram (DRD)

• Decision

• Input Data

• Business Knowledge Model

• Knowledge Source

• Connectors (Information, Knowledge, Authority)


DMN MODELING


Decision

Requirements

Diagrams (DRD)

Decision Logic

(Standardized

Decision Tables))

Integration with

Business Processes

(BPMN)

DECISION LOGIC

“A business knowledge model may contain any

decision logic which is capable of being represented

as a function. This will allow the import of many existing

decision logic modeling standards (e.g. for business

rules and analytic models) into DMN. An important

format of business knowledge, specifically supported

in DMN, is the Decision Table. “


DMN NOTATION


DRD

Output of the

Decision-2 is used

as an input for the

Decision-1

This Decision Table

represents Business

Knowledge-2

(decision logic)

DECISION DIAGRAMING TOOLS

• Commonly Used Microsoft tools:

• Visio

• Excel

• Business Process Management tools:

• Any BPMN tool

• E.g. ProcessOn

• Specialized DMN tools

• “DecisionFirst” – Decision Management

Solutions


EXAMPLE MODEL: DECISIONFIRST MODELER & OPENRULES


DecisionFirst Diagram

with a URL that points to

the OpenRules Decision

Table

DMN LITERAL EXPRESSIONS

• Not every problem is a nail (Decision Table)

• Literal expressions are text describing how output

values are derived from input values

• The expression language may, but need not be,

formal or executable

• Examples include: plain English, first-order logic,

Java code, etc.

• FEEL


DMN DECISION REPRESENTATION

•Business Process • Decision Requirements

• Decision Logic


BUSINESS PROCESS




•Decision Requirements • Decision Logic


DECISION REQUIREMENTS

Match Loan

Constraints to

Lender Products

Determine

Product Decision

Table

Decision Requirement Graph (DRG) for Objective-based Mortgage Loan Recommendations

Lender Products

Determine

Objective-based

Mortgage Loan

Recommendations

Determine

Objective-based

Recommendations

Determine

Objective-based

Ranking

Ranking Strategy

Decision Table

Client Objectives

Client Objectives

and Preferences

Determine Lien-

based Scenarios

Determine

Requested

Scenario

Determine Term-

based Scenarios

Determine Risk-

based Scenarios

Risk-based

Options Decision

Table

Requested

Product Decision

Table

Lien Options

Decision Table

Term Options

Decision Table

Lender Pricing

Policy

GSE Loan Amount

Guidelines

Credit Information

Generate Loan

Constraints

Determine Loan

Constraints

Decision

Business

KnowledgeInput Data

Knowledge SourceInformation

Requirement

Knowledge

Requirement

Authority

Requirement

Determine Base

Rate Decision

Table

Determine

Adjustors

Decision Table

Principle &

Interest

Calculation

(PMT)

Mortgage

Insurance

Decision Table

Taxes &

Insurance

Decision Table

Real-time Pricing

Data

Determine Monthly

Payment

Secondary

Markets


FILTERED VIEW: HIGH-LEVEL

Match Loan

Constraints to

Lender Products

Determine Monthly

Payment

Determine

Objective-based

Mortgage Loan

Recommendations

Determine

Objective-based

Recommendations

Determine

Objective-based

Ranking

High-level DRD: Objective-based Mortgage

Loan Recommendations


FILTERED VIEW: DECISION

Client Objective

and Preferences

Generate Loan

Constraints

Determine Lien-

based Scenarios

Determine

Requested

Scenario

Determine Term-

based Scenarios

Determine Risk-

based Scenarios

Risk-based

Options Decision

Table

Requested

Product Decision

Table

Lien Options

Decision Table

Term Options

Decision Table

DRD for the Decision

Generate Loan Constraints Match Loan

Constraints to

Lender Products

Lender Pricing

Policy

GSE Loan Amount

Guidelines

Credit Information




• Decision Requirements

•Decision Logic


DMN DECISION TABLE

Term Options Decision Table NI Collect

# Request Objective

Requested

Product

Category

Requested

Product Term

Recommended

Product Category

Recommended

Product Term

Recommended

Liens

LOWEST MONTHLY

PAYMENT, EQUITY BUILDER,

LOWER RATE

FIXED, ARM see products

list FIXED, ARM see products list

FIRST,

FIRST+SECOND

1

LOWEST MONTHLY

PAYMENT

FIXED ARM 3/1 FIRST

2 FIXED 15 FIXED 20 FIRST



5 ARM 7/1 ARM 3/1 FIRST



8

EQUITY BUILDER

FIXED 30 FIXED 20 FIRST



11 ARM FIXED 20 FIRST

12

LOWER RATE

FIXED 30 FIXED 20 FIRST


14 FIXED ARM 5/1 FIRST

15 ARM Not 1/1 ARM 1/1 FIRST


DMN CUMULATIVE DECISION TABLE

Determine Adjustors Decision Table NI SUM

# Recommended Program Recommended Liens Recommended 1st Lien LTV Adjustor

# PRIME, NON-PRIME FIRST, FIRST+SECOND [0…100]

1 0

2 FIRST [85.01..100] 0.0025

3 NON-PRIME 0.01


IMPLEMENTATION TOOL: OPENRULES

• OpenRules is a general purpose Business Rules and Decisions Management System available as an Open Source product

• Allows subject matter experts and software developers to create, test, execute, and maintain enterprise-class decision support applications

• To this point the slides show a tool-independent representation

• Below slides show the translation from the DMN graphical representation and DMN decision logic representation into the OpenRules table-based executable representation

• Implementation executes and results are reported


TOP-LEVEL DECISION

Decision GenerateLoanConstraintsAndMatchProducts

Condition ActionPrint ActionExecute

Number of Loan Options Decisions Execute

Generation Loan Constraints (initial

loan options) GenerateLoanConstraints

> 0 For each loan constraint, Match It to

Lender Products MatchToLenderProducts

Decision Main

Condition ActionPrint ActionExecute

Number of Loan Options Decisions Execute

Generate Loan Constraints and

Match them to Lender Products

GenerateLoanConstraintsAndMatch

Products

> 0 Determine Monthly Payments for

Generated Loan Options DetermineMonthlyPayments

> 1 Determine Objective-based Ranking RankLoanOptions


TERM OPTIONS DECISION TABLE

DecisionTableMultiHit TermOptionGenerationRules

# If If If ActionAny Then Then Then Then Then Then Then

#

Request

Objectiv

e

Requeste

d Product

Category

Requeste

d Product

Term

Add New

Recommendatio

n

Recommended

Program

Recommende

d Product

Category

Recommende

d Product

Term

Recommende

d Liens

Recommende

d 1st Lien LTV

Recommende

d 2nd Lien

LTV

Recommende

d Loan

Amount

1

Lowest

Monthly

Payment

Fixed :=add(decision) := ${Requested

Program} ARM 3/1 First

::=

$R{Requested

LTV}

0

::=

$R{Requested

Loan Amount}

2 Fixed 15 :=add(decision) := ${Requested

Program} Fixed 20 First

::=

$R{Requested

LTV}

0

::=

$R{Requested

Loan Amount}



::=

$R{Requested

LTV}

0

::=

$R{Requested

Loan Amount}



::=

$R{Requested

LTV}

0

::=

$R{Requested

Loan Amount}

5 ARM 7/1 :=add(decision) := ${Requested


::=

$R{Requested

LTV}

0

::=

$R{Requested

Loan Amount}



::=

$R{Requested

LTV}

0

::=

$R{Requested

Loan Amount}



::=

$R{Requested

LTV}

0

::=

$R{Requested

Loan Amount}


GENERATE SCENARIOS

Decision GenerateLoanConstraints

Decisions Execute

Term Option Generation Decision TermOptionGenerationRules

Price Option Generation Decision PriceOptionGenerationRules

Lien Option Generation Decision LienOptionGenerationRules

Requested Product Generation Decision RequestedProductGenerationRules


DETERMINE ADJUSTORS DECISION TABLE

DecisionTableMultiHit DetermineRateAdjustorRules

If If If Conclusion

Recommended

Program

Recommended

Liens

Recommended

1st Lien LTV Adjustor

= 0

First [85.01..100] += 0.0025

Non-Prime += 0.01


END-TO-END VALIDATION


RECAP

• Loan recommendation problem presented

• Process modeled using BPMN 2.0

• Decision logic modeled using new DMN standard

• Problem implemented in OpenRules

• End-to-end testing provides verifiable results

• Customer stated preferences in conjunction with

lender product and pricing data and a set of

mortgage configuration rules produce a ranked set

of mortgage loan options and their corresponding

benefits


CONCLUSIONS

• BPMN provides insufficient support for BDMS

• DMN formalizes package of material in support of decision logic

• DMN’s ability to bring together context of decision table invocation, authority levels for decision management maintenance and governance, and interdependencies between decisions can bridge the gap between business process representations and low-level IT data models and code

• Encapsulation of decision logic brings with it the benefits of modularity and flexibility as-well-as transparency throughout the enterprise from business people to IT staff

• Vendor support remains to be seen


decision models using dmn and bpmn standards: mortgage recommender

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