What are the main obstacles in the way of successful digital transformations within large financial organizations? Read the blog and watch the full webinar here >> https://www.tamr.com/blog/webinar-3-strategies-to-drive-more-data-driven-outcomes-in-financial-services/

1. 3 Strategies to Drive More
Data-Driven Outcomes in
Financial Services
Powered by Tamr

2. 3 Strategies to Drive More Data-Driven Outcomes 2
Randy Bean
CEO, NewVantage
Partners
Ravi Hulasi
Head of Strategic Sales
Engineering, Tamr
Speakers

3. 3 Strategies to Drive More Data-Driven Outcomes 3
2020 Result Themes
● Data-Driven Business Transformation:
Connecting Data/AI Investment to
Business Outcomes
● Focused on c-executives and a
top-down perspective
● NVP Survey Financial Services
represent 67.1% of 2020 survey
respondents
● Tamr surveyed 300 executive at
financial organizations with $1B+

4. 3 Strategies to Drive More Data-Driven Outcomes 4
2020 Participating Financial Firms
Financial Services & Insurance
AIG Fidelity Investments PNC Bank
Allstate First Republic Bank S&P Global
Ally Financial Freddie Mac Santander Bank
American Express Hanover Insurance Scotia Bank
American Family Huntington Bank State Street
Bank of America JP Morgan Chase Sumitomo Bank
Bank of China Lincoln Financial Group Sun Life Financial
Berkshire Hathaway London Stock Exchange Swiss Reinsurance
BNY Mellon M&T Bank TD Ameritrade
Capital One Mastercard TD Bank
Charles Schwab MetLife TIAA
Citigroup MFS Investments Travelers
Citizens Bank Moody’s UBS
Credit Suisse Nationwide Insurance Voya Financial
Deutsche Bank New York Life Wells Fargo

5. 3 Strategies to Drive More Data-Driven Outcomes 5
Industries such as financial services have invested heavily in
data management and data initiatives and are seen as a
bellwether for Big Data investments.
*98.8% of survey participants are C-executives
Industry Participation 2018 2019 2020
Financial Services 77.2% 73.8% 67.1%
Healthcare 8.8% 16.6% 25.6%
Additional Leaders 14.0% 9.6% 7.3%
Respondent Role 2018 2019 2020
Chief Data Officer / Data Leader 55.6% 56.8% 62.2%
Chief Analytics Officer / Analytics Leader 15.3% 16.0% 11.0%
Chief Information Officer / Analytics Leader 13.9% 17.3% 21.9%
Chief Marketing/Digital Officer / Strategy Leader 2.8% 4.9% 1.2%
Other 6.9% 2.5% 1.2%

6. 3 Strategies to Drive More Data-Driven Outcomes 6
4 Key Themes and Findings
1. Data and AI investment is up, but the pace of investment is
slowing
2. AI results continue to be early stage with limited deployment
3. Firms struggle to become data-driven as progress is slower
4. People and process issues continue to be greatest barrier
to outcomes.

7. 3 Strategies to Drive More Data-Driven Outcomes 7
Theme 1: Data and AI Investment are up, but the pace of
investment is slowing
Investment in Big Data/AI 2019 2020
Investing in Big Data/AI 97.2% 98.8%
Pace of Investment in Big Data/AI 2019 2020
Pace is Accelerating 91.6% 51.9%
At a Steady Pace 8.4% 46.9%
Principle Driver of AI/Big Data Investment
Transformation 53.7%
Innovation 26.8%
Competition 8.5%
Cost-Savings 6.1%
Regulation 4.9%

8. 3 Strategies to Drive More Data-Driven Outcomes
Theme 2: AI results continue to be an early stage
with limited deployment
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Investment in Big Data/AI 2018 2019 2020
Greater than $500M 12.7% 21.1% 18.3%
$50M--$500M 27.0% 33.9% 46.5%
Under $50M 60.3% 45.0% 35.2%
AI Investment and Adoption 2020
AI in Widespread Production 14.6%
AI in Limited Production 51.2%
AI in Pilot 26.8%
No AI in Use 7.3%

9. 3 Strategies to Drive More Data-Driven Outcomes 9
Theme 3: Firms struggle to become data-driven as
progress is slower
Business Adoption of Big Data/AI a Challenge 2018 2019 2020
Yes 64.7% 77.1% 73.4%
No 35.3% 22.9% 26.6%
The State of Big Data/AI in 2020 2019 2020
Managing Data as a Business Asset 46.9% 50.0%
Forged a Data Culture 28.3% 26.8%
Driving Innovation with Data 59.5% 64.2%
Competing on Data and Analytics 47.6% 45.1%
Created a Data-Driven Organization 31.0% 37.8%

10. 3 Strategies to Drive More Data-Driven Outcomes
Theme 4: People and process issues continue to be
greatest barrier to outcomes
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Principle Challenge to Becoming Data Driven
People/Business Process/Culture
Technology
2018 2019 2020
80.9% 92.5% 90.9%
19.1% 7.5% 9.1%
Principle Responsibility for Data 2018 2019 2020
Chief Data/Analytics Officer 47.9% 48.1% 40.2%
Chief Information Officer 15.5% 4.9% 11.0%
No Single Point of Accountability 23.9% 28.4% 26.8%
Other Executive 12.7% 18.6% 12.0%
Success of the CDO Role 2020
Successful and Established 27.90%
Nascent and Evolving 49.10%
Struggling with Turnover 23.00%

11. 3 Strategies to Drive More Data-Driven Outcomes 11
Tamr digital transformation survey
identified the need for data to be:
● Accurate (64%)
● A driver for clear insights into
informed decision making (64%)
● Sourced from key systems (61%)
Digital Transformations Apply More Pressure On Your Data

12. 3 Strategies to Drive More Data-Driven Outcomes 12
Key Weaknesses Preventing Success
● Constant data changes over time (75%)
● Existing data management practices don’t scale (55%)
● Unifying hundreds or thousands of data sources from across the org
(47%)

13. 3 Strategies to Drive More Data-Driven Outcomes
Tamr’s expertise in Financial Serviceserv
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Privacy, GDPR, CCPA
Identify and discover PII and
customer data across the
enterprise
Claims Management
Unify claims data across all internal
channels and 3rd party agencies
Customer Analytics
Analyze your customer base and
find areas for cross-sell and up-sell
Spend and Procurement
Classify spending and identify
patterns
AML and KYC
Enable robust CDD and
beneficial ownership
identification
Reference Data
Onboard and unify high impact
internal and external sources
Reference Data
Onboard and unify high impact
internal and external sources
Reference Data
Onboard and unify high impact internal and
external sources

14. 3 Strategies to Drive More Data-Driven Outcomes
Use Case: Reference Data
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15. 3 Strategies to Drive More Data-Driven Outcomes
Reference data is critical to digitizing your business
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Sources
Internal:
● Customer
profiles
● Transactions
● Interactions
● ...
Uses
KYC, CDD, AML, Sanctions
Customer 360 and Sales Analytics
Account Operations - optimize staffing and
prioritize provided services
Securities mastering and servicing
Counterparty risk & identification, FCPA and Vendor
Intelligence
Reference Data Operations
Analytics
Counterparty and Vendor Risk
Cross-selling
Accurate Entity
Identification
Stitch together a complete picture of every
entity and boost operational excellence
External:
● Sanctions
● News
● Credit risk
● ... Current and upcoming regulations - MiFID II, CCAR, FRTB

16. 3 Strategies to Drive More Data-Driven Outcomes
Common challenges managing reference data
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Business units handle their
data in silos
Reference data is built around a
specific MDM
Inefficient or human-intensive
reference data processes
Underutilizing internal
systems that don’t talk to
each other
Resource-intensive
process to onboard
additional sources

17. 3 Strategies to Drive More Data-Driven Outcomes 17
Scalable: Human-augmented machine learning allows scale without sacrificing accuracy
Faster: Results delivered in days vs. months or even years using traditional approaches
Better optimized: When experts aren’t spending endless days on data prep, they can focus on more specialized efforts
More flexible: Teams can respond to the unexpected, faster and more effectively than ever before
It opens new opportunities: With cost-to-know reduced, projects shelved for “high costs and risk” can finally get the
attention they deserve.
Human input Operational integrationMachine learning
This calls for a modern solution

18. 3 Strategies to Drive More Data-Driven Outcomes
Master your reference data centrally
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Reduce storage costs
Optimize resource utilization
Increase adoption of a
centralized data repository
Decrease “rogue” instances
of reference data and reduce
number of data silos
Identify ineffective sources
BU #1 Reference Data BU #2 Reference Data BU #3 Reference Data New external data sources
Centralized and deduplicated
reference data store
Data consumption Data consumptionData consumption
ML-assisted
Matching Review
Automated
matches

19. 3 Strategies to Drive More Data-Driven Outcomes
How Tamr overcomes data debt
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ALIGN CLUSTER CONSOLIDATE
Machine Learning Expert Input
Schema Mapping Record Matching Golden Records
Sources OutputTamr Unification System
Internal Data
External Data
Tables Entities
Low Business Value High Business Value
Clients
Analytics
Sanctions &
Risk
Customer
onboarding
Cross-sell offers
A US-based G-SIB
estimates $20M+ in
annual savings from
Tamr

20. 3 Strategies to Drive More Data-Driven Outcomes
Three Strategies...
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1. Access to data is critical. Pick a
business problem of strategic
importance to begin with and run
with it
2. Identify upfront the analytic
outcomes you need to see at the
end of the project
3. Select best of breed vendors that
will take the technology burden
off your data experts

21. 3 Strategies to Drive More Data-Driven Outcomes
Q&A
21

22. 3 Strategies to Drive More Data-Driven Outcomes
Thank you!
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