The Role of Data Governancein a

Successful CDI Platform Initiative

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The Speaker

Kanon CozadSenior Vice PresidentDirector of Application DevelopmentUMB Bank, n.a. Kanon.Cozad@umb.com

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UMB: Background

• UMB offers complete banking and related financial services to both individuals and business customers.

- UMB’s vision : To be recognized for the unparalleled customer experience.

• Over $8 Billion in Assets

• Over 3700 associates

• Over 140 branch locations in 8 states

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Project Challenge

UMB’s CDI Platform Initiative:

Provide a 360-degree, holistic view of UMB’s customer relationships

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Business Drivers:

• Increase efficiencies of our front line associates by consolidation of customer data.

• Improve cross sale opportunities by consolidation of current product offering and identification of complimentary products.

• Empower our associates to fulfill UMB’s mission:- To know our customers and anticipate their needs; advocate and advise;

innovate and surprise.

Technical Drivers:

• Multiple sources of customer information; multiple versions of the truth.

• Difficult existing customer aggregation routines.

• Wanted a more flexible technical platform on which to build.

Compelling Business & Technical Drivers

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Overview of UMB’s Solution

• IT Systems– Acquired systems for customer relationship management (CRM)

and customer data integration (CDI) from Oracle.•Consolidated legacy applications and customer data into these.

– Acquired system for customer data quality from Trillium.• Improved customer data, didn’t just consolidate it.

• Business Organizations– Established data stewardship program to identify and prioritize

applications and data for consolidation and improvement.– Established data governance process to help break down

organizational silos and share customer data as an enterprise asset.

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Overview of UMB Data Governance Process

• Business process priorities are identified– Then translated into technology that can enable these.

•Technology selected is either already in place or new.– Change is facilitated

• Including changes to both sales processes and technology

• The focus is on sales processes, for now– The primary goal is to transform the sales process.– Formerly, it was organized per line of business (LOB).– Going forward, sales processes reach across LOBs.

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Project Process:

• November 2004 UMB identified need for new Enterprise CRM solution

• Completed Vendor/Partner analysis; chose Siebel SFA as front line system and Siebel Universal Customer Master (UCM) as CDI platform

• Went live in March 2006 with 726 users.

• Plans to roll out to over 1000 users by end of 2007

Project Process

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Project Challenge

The solution…

Establishing the baseline

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Hogan CustomerInformationFile

Hogan Demand DepositsHogan

Time Deposits

SHAWConsumer &CommercialLoans

Hogan RPM(RelationshipPricing Model)

Global Plus(Trust)

FDRCredit Cards(monthly feed)

CorporateReference Database

InvestmentBanking

BrokerageInsurance

Mutual FundsSafe Keeping

MAINFRAMEPreprocessing

MQ

Nightly Edge System Processing

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UCM

MQ

CRM

Automatically Update an existing

Best Version Record

Manual (Data Stewardship)

Create New Best Version Record

Trillium Data Matching Engine

Best Version Records

Best Version Records

Inserts from Edge System

Delta Loads

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CRM

SR

Best Version RecordsData Layer

Business Object Layer Presentation Layer

Main FrameWeb Services

Edge System

Service Request Data Flow

UMB Call Center

Delta Loads into UCM

Staging Tables

UCM Tables(Final

Representation)

Trillium UCMInterface

MQ Series

Organization or Individual Records

For Insert or Update

TrilliumDirector

TrilliumCleanser

TrilliumMatcher

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TrilliumDirector

TrilliumCleanser

TrilliumMatcher

Trillium Director

Directs the flow of Requests coming to and from the UCM Connector intoEither the Cleanser or Matcher.

Trillium Matcher

Using the pre-selected records from the UCM Connecter, the Matcher has Match Routines Combined with rules based around Profile informationto determine if a Staging record matches a record already in UCM Base tables.

Routines analyze the following:•Organization/Individual Name Components•Address Components (House #, Street, city, State, Zip)•Social Security / Tax Id•Date of Birth•Phone Number

Trillium Cleanser

Cleanses Profile data. Also uses a process called Geocoding to analyze and correct Address Related components. Additionally,Mix cases Profile components(i.e. PETER DESILVA would be mixed

cased to Peter deSilva)

Profile Components that are cleansed:

•Name (Business Name, Suffix, Prefix, First, Last, etc.)•Address (Street Name, City, State, Zip (zip+4), Country•SSN / Tax-Id Cleansing (formats all SSN’s to ‘#########’format. Additionally, if SSN is determined to be invalid, it records it to ‘000000000’

•Creates a Candidate code using Profile data used to help determine what records are sent to Matcher.

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UCM Insert Process Flow

Insert UCM ConnectorCall to Cleanser

Trillium Cleanser• Standardize Names• Fix Address Components• Mix Case• Format/Standardize SSN• Create Candidate Code

Trillium Director

Get all records from base where either SSN

or Candidate CodeEquals the SDH (staging) record

Trillium Director

Trillium MatcherUse match routines and rules to determine if SDH record isequal to any UCM Baserecords.

Trillium will return 1 of 3 possibilities:•Match•Suspect•Fail

MatchResult

MatchMerge SDH Cleansed record into UCM Base record using survivorship rules. Survivorship rules drive the updates (if any) to profile components.

FailInsert Cleansed SDH Record into UCM Base as new Customer

SuspectA suspect is 1 of 2 instances.1 - The SDH record was close but not exact

enough for an auto-merge. Key components may have been slightly different.

2 - The SDH record matched to multiple UCM baserecords and could not determine the best version record to merge into.

In any of these cases, the SDH record goes intoData Stewardship. The UCM interface has an Application that allows the Business Units to Merge/Link the SDH record into the best version in UCM.

Staging

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Data Stewardship

The role of Data Stewards

• Evaluate Matching rules and compliance to data policies

• Testing of system upgrades and how they affect data quality

• Manual override of cleansing rules to address anomalies

• Communication of merge criteria to front end users• Validate merge and unmerge request from front

end users

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Data Governance

• Definition: Data Governanace (DG) is usually manifested as an executive-level board or committee that institutes and enforces policies and procedures for the business use and technical management of data across the entire organization.

• At UMB, DG provides the roadmap Translates to practices through entire enterprise, not just one LOB

– Integrates oversight efforts in order to set standards.

• At UMB data governance provides direction; data stewardship puts direction into action.

• UMB uses Compliance as a Trojan Horse.

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Data Governance

• Business Drivers for DG:– Compliance– Auditable data for regulatory reports– Leverage data as a corporate asset– Make cross-LOB dependencies more efficient

• Technical Goals for DG:– Control the use of data– Improve data– Share data more broadly– Cross-functional change management and proposal

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Plans for the Future

• Review data governance policy to make sure it addresses emerging communications methods.

• Identify further external sources of data to help complete the customer profile.

• Use consolidated data to profile our customers and deliver product offerings appropriate to their buying patterns.

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Wrap-up

And there you have it…

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The Speaker

Kanon CozadSenior Vice PresidentDirector of Application DevelopmentUMB Bank, n.a. Kanon.Cozad@umb.com