The document outlines the implementation of a rule-based data maintenance system at Eurex, aimed at automating the management of securities data to enhance quality and compliance while reducing costs. It highlights the importance of visual rules management systems (BRMS) that enable quick rule changes without altering source code, shifting responsibility for data management to business units. The new approach has significantly increased the volume of processed securities and improved data quality, making Eurex a market reference in the field.

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 conducting monetary interventions SLB Market Leading European market place for securities lending & borrowing = 60‘000 securities from 87 countries worldwide www.eurexrepo.com Introduction

14. Problem Description: Master Data Maintenance 10‘000 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 (100’000 securities) => increase performance Problem description

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 Data Dissemination Valid Data: File WebService DB Table E-Mail Automated, Rule-driven Process 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-based validation of all data according to business requirements Rule-based composition of securities 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-driven Process

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 100’000 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]