Master Data Management – A Pilot Study

Student : Gouri Pradhan

Student ID : 42351502

Supervisor : Prof. Michael Johnson

13th June 2012

Presentation Structure

2

Initial problem specification

Related work and background information

Approach and methodology to solve the problem

Project outcomes

Project Overview

• Master Data Management - A Pilot Study

• Carried out for CGSGAM

• A division of CBA

• Focus on Legal Entities

- Companies that issue financial securities

• Used Talend MDM Software

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Master Data and Master Data Management (MDM)

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• Key reference data within an enterprise

• Shared by different IT systems Master Data

• A program undertaken to effectively manage a single accurate record of master data

Master Data Management

(MDM)

This section covers…

5

Initial problem specification

Related work and background information

Approach and methodology to solve the problem

Project outcomes

6

MDM Definition

• MDM is a framework of processes and technologies • The aim is to create and maintain a reliable, sustainable,

accurate, and secure data environment • The data environment represents a “single version of truth” • It is used both intra- and inter-enterprise

• across a diverse set of application systems, • across lines of business and user communities

- Berson and Dubov (2007)

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DAMA-DMBOK Functional Framework for MDM

MDM Methodologies

MIKE 2.0 MDM Solution Offering

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Analyze current

business processes Get ‘Legal Entity’

information Understand links

between business areas

Project Phases for Pilot MDM Project

Phase 1

Business Study and MDM Strategy

Analysis

Phase 2

Data Analysis and Data Modeling

Phase 3

Implementation Plan

Identify current

data sources Conduct data

quality analysis Propose Target

Data Model for ‘Legal Entity’

Propose

Implementation Plan

Provide guidelines

for further work

This section covers…

9

Initial problem specification

Related work and background information

Approach and methodology to solve the problem

Project outcomes

What is CFSGAM?

• Financial asset management business

• Manages diverse range of assets including equities, property

securities, listed infrastructure

• Growth through mergers and acquisitions in many global markets

• It has range of diverse hardware platforms, applications suites

and in-house developed custom software

• Data management is a key area of interest to support growth

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CFSGAM Investment Management Process

Research and Analysis

Portfolio Management

Order Management

Investment Portfolio

Management

Investment Accounting

Reporting

The Front Office The Middle & Back Office

Role of Legal Entities

• CFSGAM researches companies to invest in their equities

• CFSGAM manages the investment portfolio for their clients

• Legal entities are primarily companies or parties that issue securities

• Legal entity has two roles in investment management

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Legal Entity

Issuers of financial securities

Counterparty in a financial

transaction

Key issues with Legal Entities

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• Different identifiers across different systems

• Application specific definitions

• External data sources use their own identifiers

• Hierarchy of entities is not defined

• No standard way of uniquely defining legal entity

ABCD Bank

Ref ID:1234

Ref ID: X123

Ref ID: BB01

Identified by

MDM Strategy Analysis

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Focu

s o

n

Problem Oriented Solution Oriented

Approach

Da

ta D

rive

n

Pro

cess

Dri

ven

‘Data driven, Solution oriented’ • Focus on improving data quality

of existing data • Focus on achieving target data

model to satisfy LEI standard adoption

- Following MDM strategies were analyzed and the most suitable one was selected

Data Quality Analysis

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Talend MDM Software used to carry out Data Profiling

• Analysis using current legal entities data extract

• Null values found in Name column, GICS Codes column, Country Code • Duplicate records found

Analysis

Analysis Results

Legal Entity Identifier (LEI) Standard

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A global LEI standard is proposed because:

• Recommended by the Global Financial Management Association (GFMA) • Single, universal standard identifier for legal entities • Will consist of a unique 20-character alphanumeric code

• Assigned to all entities that are counterparties to financial transactions

Legal Entity Identifier Characteristics

The accurate and unambiguous identification of legal entities engaged in financial transactions is critically important for monitoring of systemic risk by regulators.

Structure of LEI Standard

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The following six data elements will all form part of the minimum set of reference data attributes that will be required by the regulatory community on the launch of the LEI

Core Data Elements for LEI

Official name

Address of the headquarters

Address of the legal formation

Date of the first LEI assignment

Date of last update of the LEI

Date of expiry, if applicable.

Companies (such as CFSGAM) will have to prepare their internal systems to integrate with the data provided by LEI standard.

Proposed Data Model for ‘Legal Entity’

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The data model is required for future integration needs of LEI standard

All the identifiers from different systems Identifiers

Legal and all other names Name

Registered Address Address

Contact Information, Company website information General Information

Trading information for listed companies Trading Information

Regulatory Status Regulatory Information

Hierarchical relationships including ultimate parent Hierarchy

Credit Analysis/Rating information about Issuer Credit Analysis

Environment-Socio-Governance Ratings Score ESG

Fun

ctio

nal

Are

as

The model defines the functional areas for which information should be maintained.

MDM Implementation Plan

19 We can add this to Footer

The phases above covers ‘legal entity’ specific details.

• Understand current data state

• Define future data state requirements

• Define scope and timeline

The phases of the proposed MDM implementation plan

Business Assessment and Strategy

Definition

Technology Assessment

and Selection Blueprint

Roadmap and Foundation

Activities

Design Increment

Incremental Development, Testing, and Deployment

• Define current state architecture

• Define key functional requirements

• Vendor evaluation and selection

• Implement the data model

• Perform end-to-end testing

• Deploy into production environment and monitor

• Develop logical and physical data models

• Define reporting environment and dashboards

• Adjust design based on the outcomes of reports

• Define business rules

• Carry out data profiling and updates

• Review data quality and take corrective actions

This section covers…

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Initial problem specification

Related work and background information

Approach and methodology to solve the problem

Project outcomes

Conclusion – Project Achievements

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Conducted business process analysis

Performed data quality analysis

Identified current issues with data

Studied requirements of LEI standard

Proposed target data model

Provided overall implementation plan

Future Work

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Extend the scope of MDM to cover other data entities

Implement end-to-end data quality framework including data and process governance

Move towards Enterprise Information Management

Thank You

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