How CIT Met the Need for Speed and Agility

in Business Through Data Virtualization

October 19th, 2017

Nagaraj VijapurkarData virtualization Lead

CIT Group, Inc.

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Abstract

How CIT Meet Need for Speed and Agility in Business

Through Data Virtualization

Enterprises face a variety of data management challenges that

influence their ability to leverage accurate, meaningful

information, quickly and efficiently. Data virtualization is an

enabling technology which can address many of these

challenges.

This session will explore how data virtualization is being used to

dramatically reduce data proliferation and ensure that all

consumers are working from a single source of the truth. It will

also look at how data virtualization can drive standardization,

measure & improve data quality, abstract data consumers from

data providers, expose data lineage, enable cross-company data

integration, and serve a common provisioning point from which to

access all authoritative sources of data.

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Data – Key Principles

Cloud

Cloud

• Universal data access across internal, external, web, structured or unstructured

Realize Value from all Data

• Flexible integration options with fine control – virtual real-time, cached or

scheduled batch

Minimize Replication

• Abstracted data delivered as reusable data services Managed access control,

service levels

Abstracted and Unified Data Services

• Performance and scalability

• Data governance, lineage, management

• Easily integrated into existing IT infrastructure

• Shared metadata services and metadata-driven data integration approach

Enterprise Class – Powerful and Agile

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Party Master – Real time integration using Denodo

Data Service Layer

Risk Origination

Salesforce CRM

Compliance On-

boarding

Reference data CW

Party Master

(MDM)

Regulatory

Credit Risk

Business

Reporting

Rest api

soap

Rest api

Party identification

process

Standardization &

Enrichment

Unique Customer

Consolidation

Data Acquisition

AR Systems Strategic Data hubs

Rest api Rest api Rest api

batch

batch

batch

batch

5CIT — Internal Use

Augment Dataset / Data stores

Architecture – Current and In Progress

DCC Systems

Loans Lease

Lease Hub Loan Hub Trade Hub

(CSDH)

Treasury

Hub

Ref. Data

Std. values & Crosswalk

• PS BU, PS OU

• Currency Rates

• TDR & Cross Ref.

DSL (Data Inbound Views)

Deposit Hub

(BDM)

Canonical Enterprise Views

Party Loan Lease DepositsTrade Mortgage Securities &

Derivatives

Cash @

Bank

Debts

Sub Ledger

(CSL)

PS Repository Credit Risk Party Master

(MDM)

DSL (Data Outbound Views)

GL Summary

FinArch

(Regulatory)FRY 9C, 14 Q/A/M, CECL, LiquidityActimize

Other Downstream Application / Data marts / Reporting

ARCQRM SFRGES CFDI

ReportingTreasury Comm. Loan Origination

and Services

CCRR

Reverse

Repos

TaxHub Party Master

(MDM)

Mortgage hub

(SDM)

CIT Systems

Loans Lease Comm.

services

Reverse

RepoDepositsDerivative,

Securities

& Debts

CF

OWB Systems

Loans Lease Mortgages Deposits Derivative,

Securities

& Debts

CF

ARC PS

Reference data

DQ

Monitoring

Operational

Metadata

- New Strategic Hubs

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Key Benefits

Application Development Benefits

• Applications development can start immediately against data “mock ups” before the actual data source is

accessible. This approach was used in the OWB integration started.

• The underlying data source(s) can be radically changed without impacting the applications using the data.

For example, the company has changed the vendors that supply data, but the data virtualization layer

made the new vendor look like the old vendor to the applications. Greatly reducing any need to recode the

application.

• Regulation and policy change rules can be applied quickly and viewed for refinement of compliance

parameters throughout the development cycle

• Business Process and regulation changes

• Early identification of Gaps from source system and requirement perspective saving cost and time

• Well-time Business Insight, Data Security, Audit and Compliance

Data Governance Benefits

• Easier to build one enterprise view of corporate data

• Easier to monitor data quality. The data monitoring tools can be independent of the underlying data

storage locations and technologies