1. Shown with the Business Case Master Data Management at EUREX Graphical Business Rules Management Volker Grossmann, Innovations Jan Trnka,STABIL IT

2. Business Rules

change most frequently

are difficult to reconcile

bear a high risk

are error-prone

hazards: incompleteness, contradiction, redundancy

are hard-wired

Business IT Systems Rules Rules Rules Rule changes are tedious, risky and expensive 3. How to Solve This Dilemma?

separate from program code

do not hard-wire

make them easy to reconcile

manage by Business and IT

test separately

apply changes automatically

manage centrally

Business IT Systems Rules Rules Rules Rules All this is accomplished by a BRMS that makes rule changes fast, safe and easy BRM 4. Cooperation between Business and IT Business IT Results from using Visual Rules

Architecture

Integration

Deployment

Infrastructure

Focus on technical aspects

Clear specs from business

Less maintenance efforts

Agile software Less costs Better quality

Focus on business aspects

Fast and easy changes

Business logic ownership

Target

Define,

Simulate,

Test and

Document business rules

Tasks 5. Visual Rules 6. Rule Elements Decide Make a decision Assign Calculate values and update data Fire Action Execute an action Call Flow Rule Call a flow rule Call Decision Table Call a decision table Call Service Call a service Done & Return Immediately return to the calling rule Repeat Repeat the following part of the rule End Repeat Immediately exit a Repeat Return Exception Create exception and continue at exception handling Handle Exception Specify what to do when an exception is thrown 7. Flow Rules

Flow rules are created using simple drag&drop

Flow rules consist of decisions, assignments, actions and exceptions

8. Decision Tables

Decision Tables can also be created via drag & drop

Decision Tables can contain decisions, assignments, actions and exceptions

9. Testing

Test cases define input and expected output of a rule

Detected deviations of input/output/internal data or actions are reported

10. Management

Rules are fully versioned

Visual compare & merge capabilities

11. Package and Rule Dependencies

Rule and rule package dependency visualization

12. Documentation 13. Introduction: EUREX

Joint venture of Deutsche Boerse and SIX Swiss Exchange

• One of the world largest derivative exchanges

• One of the largest Repo and SLB markets providers in Europe

• > 500 Participants (Banks)

Repo Market

• Leading European Repo market place since 1995

• Exclusive usage by the Swiss Federal Bank (SNB) for conductingmonetary interventions

SLB Market

• Leading European market place for securities lending & borrowing = 60000 securities from 87 countries worldwide

www.eurexrepo.com

Introduction

14. Problem Description: Master Data Maintenance

10000 securities is a limit for manual maintenance

Problems:

• Data quality

• Consistency

• Compliancy with specifications

• Time (time to market)

Goals for new solution:

• Automate the process => lower costs

• Increase the quality

• Process much higher data volume (100000 securities) => increase performance

Problemdescription

15.

Rule-Based Data Maintenance

Rule-based Data Maintenance Valid & consistent Data Automated Process

Valid

Consistent

Unified format

How? Data, or Data fragments

Incomplete

Inconsistent

Various formats

complete filter & merge capture validate release distribute 16.

Rule-Based Data Maintenance

Rule-based Data Maintenance Minimal Human Interaction Persistent Data Storage Information Capture Presentation DataDissemination

Valid Data:

File

WebService

DB Table

E-Mail

Automated, Rule-drivenProcess

Incomplete Data

Fragments:

File

WebService

Web-Extract

E-Mail

DB Table

17. What it really does

Data input as e-mail, file, Web-page

Various formats (XML, csv, text, Edifact)

Consolidation of data from different sources (Bloomberg, Telekurs, ..)

Rule-basedvalidation of all data according to business requirements

Rule-based composition ofsecurities into baskets and markets

Rule processing uses 35 decision trees> 2,000 rules

Automatic data dissemination to the trading platform

Rule-Based Data Maintenance at Eurex

Automated,Rule-drivenProcess 18. Impact of Visual Rules

Change of business logic without change of source code

Responsibility is with the business unit, not with IT (the natural know-how owner is responsible)

Experiments with data and rules are possible

Intuitive and easy to use user interface

Side effects

User must know his business

Rule outcome is exclusively yes or no

Bad rules may screw-up the system (versioning required)

Rule-Based Data Maintenance at Eurex

19. Business Impact

100000 securities processed within 3 hours

Data volume increase by factor 10

Degree of automation = 98%

Cost saving

Eurex data quality is now market reference!

Rule-Based Data Maintenance at Eurex

20. What do Analysts say? 21. Visual Rules Components 22. Detailed Eclipse-based Modeler Architecture Visual Rules Modeler Test Editor Flow Rule Editor Workspace Decision Table Editor Eclipse Platform JDT(Java Development Tools) EMF(Eclipse Modeling Framework) GEF (Graphical Editing Framework) EMF Commands Rule Meta Model (Ecore) EMF Validation Rule Model Validation (OCL and Java) BIRT (Business Intelligence and Reporting Tools) Equinox (OSGi) Java Code Generator (Velocity Templates) Rule Model Export (HTML) Java Integration API Rule Navigator Java Import Ant Tasks Rule Models (EMF Resources) Rule Integration API Data Model Synch API Extension Points Advisor Security Functions Actions Services Custom UI Debugger Debugging Framework Execution/ Testing JDT Launch Compare/Merge Team API 23. Visual Rules Enterprise Platform 24. Any Questions ? Volker Grossmann, Product Management Visual Rules [email_address] Jan Trnka, CEO STABIL IT [email_address]