Trusted analytics and predictive data models require accurate, consistent, and contextual data. Even with the vast amount of internal business data available, financial services institutions are looking to trusted 3rd party data to fuel analytical models with new and relevant attributes to gain meaningful insights.   With over 9,000 data attributes describing the people, places, and a myriad of details for any given location, Precisely is uniquely positioned to help Financial Services companies create new and innovative insights from data. Stay ahead of the competition and gain a competitive advantage with trusted data for confident business decisions.   During this webinar, you will see how our clients are leveraging innovative strategies to unlock the power of data. Use cases will include: Commercial Lending: How do I efficiently understand collateral?Mortgage: Improved understanding of comps in a volatile market?Credit Card: How do I drive more card transactions via location understanding? Network Optimization: Where are my customers and how do they want to interact with me?Cross Sell: Who is my customer and what products should I offer her?Investment Banking: What alternative data helps me better understand investment opportunities?ESG: How can I better understand and predict the impact of new ESG initiatives on my profitability?Improve Efficiencies: Increase accuracy of comps and create amenity scores to improve Automate Physical Appraisal Waiver decision-making

1. 9000 Ways to Optimize
Outcomes in Financial
Services:
Best-in-Class Data Sets

2. Today’s presenters
Tim McKenzie
Solution Architecture,
Manager, Precisely
Dan Sorensen
Data Enrichment
Manager, Precisely

3. Exploding need for trusted data
83% of CEOs
want their
organization to be
more data-driven
Digital transformation
investments to
top $6.8 trillion
globally by 2023
68% of Fortune 1000
businesses now
have CDOs – up 6x
in the last decade
Global data
infrastructure spending
expected to reach
$200 billion this year
Data is the fuel for decision-making today
3
IDC IDC Gartner Forbes

4. Source: Corinium Intelligence 2021
73%
say a lack of
technology or
services to facilitate
data integration is
creating challenges
for their teams
82%
say data quality
concerns represent
a barrier to their
digital transformation
projects
80%
find it challenging
to ensure data is
enriched at scale
consistently
82%
say deploying
accessible location
data across their
enterprises is
challenging
There’s still work to do
4
We surveyed 300+ C-Level Data Executives in the Americas, EMEA and Asia Pacific

5. LOCATION
MASTER DATA
MANAGEMENT
GOVERNANCE
& QUALITY
ENRICHMENT INTEGRATION
Your unique data
integrity journey
will reflect your
business
needs
Data
Integrity
Data integrity
is a journey
• Every journey to data integrity is unique and
driven by business initiatives
• Market trends are accelerating the need for
data integrity
• Enrichment is a critical component to data
integrity in the Financial Services vertical

6. How does location data inform decisions in FS?
Credit Card
How do I drive
more card
transactions
via location
understanding?
Mortgage
Improved
understanding
of comps in
volatile market?
Commercial
Lending
How do I
efficiently
understand
collateral?
ESG
How do extreme
weather events
affect the
creditworthiness
of my portfolio?
Investment
Banking
What alternative
data helps me
better understand
investment
opportunities?
Network
Optimization
Where are my
customers and
how do they
want to interact
with me?
6

7. Real world data challenges in Financial Services
• Neighborhoods
• School Districts
• Points of Interest
• Risk
• Location ID/Lat & Long
• Business Locations
• Demographics
• Weather
• Global Boundaries
• Mobile Data
• Points of Interest
• Risk
• Location ID/Lat & Long
• Property Attributes
• Mobile Data
MORTGAGE CREDIT CARD ESG
• Location ID/Lat & Long
• Demographics
• Property Attributes
• Mobile Data
• Points of Interest
• Risk
• Mobile Data
• Demographics
• Location ID/Lat & Long
• Property Graph
• Risk
• Property Attributes
CROSS SELL/UP SELL INVESTMENT BANKING COMMERCIAL LENDING
• Address Fabric
• Business Locations
• Mobile Data
• Demographics
• Travel Time/Distance
• Bank Deposits
NETWORK
OPTIMIZATION
• Location ID/Lat & Long
• Administrative
Boundaries
• Business Locations
TRANSACTION
MONITORING

8. High Value Use Case Examples

9. Enrich addresses to improve fraud
identification

10. Fraud is of increasing concern across the financial services sector
How many people of businesses attempted to
defraud your organization in the past 12 months?
Growth Mid-market Enterprise
None
0%
0%
0%
71%
1 – 1,000
63%
26%
1,000 – 10,000
25%
22%
58%
Over 10,000
10%
6%
17%
Unable to
determine
2%
0%
0%
Key Findings of the True Cost of Fraud Study:
Financial Services and Lending
Attacks and Costs: Fraud costs and attack volumes for financial services
firms remain significantly higher compared to before the pandemic.
Costs continued to rise above early 2020 levels, with banks reporting the
highest figure of $4.36 for every $1 of fraud loss. Mortgage firms also had
a comparably higher cost of $4.20 for every $1 lost to fraud.
…And it’s only going to get worse
Aite-Novarica Group believed that synthetic identity fraud for unsecured
U.S. credit products is expected to grow from $1.8 Billion in 2021 to $2.42
Billion in 2023.
It also found that, in a survey of top fraud executives, “synthetic
identities resulting from application fraud” as the number one threat
they are most concerned about in the near future.
Source: LexisNexis from 2022 Source: PaymentsJournal.com article from May 2022
Source: Alloy report from 2022
How much do you estimate your organization
lost through fraud over the last 12 months?
4%
No fraud losses
$1-$100,000 6%
$100,001-$500,000 21%
$500,001-$1,000,000 43%
$1,000,001-$10,000,000 24%
Over $10,000,000 3%
Unable to determine 0%
Source: Alloy report from 2022

11. Common
process
and technology
gaps regarding
addresses
within Financial
Services
Address issues typically identified by Internal Audit, Fraud
and Data Governance as Risk
ADDRESS
SHARING
There is also no ability
to see how many
account mailing
addresses are the same
across wealth clients
ADDRESS
FLAGGING
Current technology
does not check and
flag client mailing
addresses that are
non-residential
ADDRESS
ATTRIBUTES
Difficulty seeing
other data related to
an account mailing
address, such as
nearby businesses

12. Several capabilities are required
to achieve the requirements
Validate addresses across multiple dimensions:
Address validity, property type, business registration if commercial property, CMRA address e.g., UPS store
Good Address Bad/Incorrect Commercial
Residential High-Rise Abandoned
Vacant Lot
Mail Receiving
Agency
Correctional
Center

13. Several capabilities are required
to achieve the requirements (continued)
Append other property attributes to a geocoded
address, such as points of interest to understand
nearby businesses at a given location
Check if there are multiple account holders with
the same mailing address, or a single account
holder with multiple mailing addresses
Sporting Goods
Dealership
Recreational Center
Auto Repair
Account Holder
123 Parkway Dr.
Account Holder
101 State St.
456 Parkway Dr.
987 Main St.
Account Holder
123 Parkway Dr.
Account Holder
123 Parkway Dr.

14. Insights Produced With Address Validation and Enrichment reduce risk.
Positive Business Outcomes from Address
Enhancement
• Address validity
• High-rise
• Single family/tenant
• Residential vs. commercial
• If commercial address – businesses registered there
• Good address, vacant lot
• Good address, abandoned building
• Commercial Mailing Receiving Agency (CMRA – “UPS Store”)
• Good address, but non-USPS deliverable
The Precisely team found the following results:
• Commercial businesses registered at an address
• Correctional center
• Addresses that require secondary address information
(Suite or apt)
• Residential dwelling – ownership names
• Home property value
• Multiple account holders at
same address
• Same account holder at same address with
multiple accounts
Additional data points

15. Add context to credit card transactions
to increase customer satisfaction

16. Presentation name
16
58%
of credit cardholders surveyed by
Experian said they need help
understanding their credit card
statements.
(Source: Experian)
47%
47% of credit cardholders surveyed by
CreditCards.com said they have had to
contact their credit card company to
clarify a transaction on their statement.
(Source: CreditCards.com)
Lack of
insights
is costly

17. Enrich transactions to add context
Credit card transactions provide limited information
about the vendor.
Presentation name
17
Utilize Data Sets to enrich your data, transactions,
and more! Providing customers with enhanced details
that provide peace of mind and a better experience.

18. Data Enrichment Opportunities
for Card Providers
Location Data Intelligence
• Leverage Branded Card first
party location data to gain
additional insights around
customers to augment
purchase-based observations
• Visitation behaviors
• Brand affinity
• Where do consumers go and
NOT use their Branded card
for payment
• Cross-shopping behaviors
18
Purchase Based Intelligence
• Organize, analyze, and present
data collected from
cardholders to help gain a
better understanding of
purchase behaviors
• Transaction counts by location,
region, etc.
• Basket sizes and basket size
comparisons
• Trade Areas by consumer
neighborhood
• Identify "nearby" stores to
places where a card is used
Marketing Segments
• Leverage location data and
purchase data to create
marketing profiles and
segments
• New customers
• Lapsed customers
• Frequent customers
• High Spenders
• Profiles: Fitness Enthusiasts,
fast-food fans, outdoor
enthusiasts, etc.

19. World Boundaries Premium includes:
• Administrative data, such as county, district, and locality
• Neighborhood location
• Postcodes
• Land use overlays including features of interest like airports,
hospitals, schools, and golf courses
• Identification of areas of disputed territory
• English and local language boundary names
A structured hierarchy for over 800,00
unique named locations:
• Level 1: Country
• Level 2: State or equivalent
• Level 3: District or equivalent
• Level 4: City or town
• Level 5: Locality or first level neighborhood
• Level 6: Second level neighborhood
Enable Search and Improve Transaction Detail with World
Boundaries Premium
19

20. Enrich Global Merchants with Context
20

21. Address and Spatial Insights through a Unique
ID Framework 8 Addresses:
• 6200 S Gilmore Rd, Fairfield, OH
• 6120 S Gilmore Rd, Fairfield, OH
• 6120 S Gilmore Rd Ste 150, Fairfield, OH
• 6120 S Gilmore Rd Ste 200, Fairfield, OH
8 Unique Address ID’s:
• P0000HYPD80Q
• P0000HYZMV57
• P0000HYPD80R
• P0000HYPD80S
6200 S GILMORE RD,
FAIRFIELD, OH
4 Buildings:
• B000CTPYF8L8
• B000CTPYF99M
• B000CTPYF63D
• B000CTPYF656
• P0000HYQK2ST
• P0000HYPD80P
• P0000HYPD80O
• P0000HYPOIVL
5 Property Boundaries:
• C102672217
• C102758578
• C102786693
• C102786694
• C102556839
• 6120 S Gilmore Rd Ste 203, Fairfield, OH
• 6120 S Gilmore Rd Ste 204, Fairfield, OH
• 6120 S Gilmore Rd Ste 400, Fairfield, OH
• 8685 Winton Rd, Cincinnati, OH
26 Retail Entities:
• D000PISCYAUE
• D000PISJWRQA
• D000PIVA7GJ1
• D000PISEUVXF
• D000PISO8X7T
• D000PISKP2SD
• D000PIT0MFHX
• D000PISKGOT3
• D000PISVLY9B
• D000PISUA7CJ
• D000PISGFU1V
• D000PISG3XSE
• D000PISMIU72
• D000PISG0YSZ
• D000PIT0RIZ8
• D000PISWRPRZ
• D000PISWIKN3
• D000PIXAJBDJ
• D000PIWZX5LU
• D000PIWKSHJ5
• D000PIXP2VZD
• D000PIXOHTCA
• D000PIXSON2E
• D000PIXW3CLI
• D000PIY4I0ZX
• D000PIXVP1XB

22. Understand critical attributes around
complex, multi-family properties loans

23. Presentation name
Understand complex multi-family
properties around lending
23
• Identify risks that may affect multifamily properties to
assess loan performance.
• Develop modeling tools with accurate data to predict
the financial impact of future events, like floods, fires, etc.
Identify:
• Co-tenancy risk
• Adjacency risk
• Commercial property risk

24. Common
questions
related to
large, complex
properties.
What is the size
and scope of
multi-family
properties?
What changes
have occurred
to this property
over time?
What is the risk
at this
property?
How accurate
is our valuation
of this
property?

25. Business Objectives
Understand the complexities of properties in their portfolio as
well as relationships between these properties
• How many addresses are part of a multi-dwelling
unit/complex
• How many addresses share a primary address
• How many sub-units are at a given location
• How many addresses are within the same building
• How many locations are within the same parcel
• How many businesses exist in each building and complex
• What are the characteristics of each building
• How is risk impacted by additional parcels/buildings related
to an address

26. 2681 Monterey Hwy, San Jose, CA 95111
26
1 Input Address Output: 446 total buildings on shared parcel

27. Apartment complex – unique addresses
902 Affinity Ln
1439 Affinity Ln
614 Affinity Ln
3 seemingly unrelated addresses -> Apartment complex with 45 buildings & 582 unique addresses

28. Impact on portfolio risk
28
Wildfire Risk in Aspen, CO
• Address and primary building fall in
• Additional buildings on shared parcels fall in

29. How do deep property insight deliver positive
business outcomes for complex property analysis?
Environment
Better
understand
environmental
risk on large,
complex
properties
Accurate
Comps
Streamline
process of
finding
comparable
properties of
similar size and
composition
Insurance
Improved
assessment
of
insurance
needs
Counterparty
Risk
Improve visibility
of counterparty
risk by
understanding
common
ownership
Property
Change
Power time series
models to
understand
change in a
properties over
time
Collateral
Assessment
Create better
collateral value
models with
improved
perspective on
the extent of a
property
29

30. Data Enrichment: Key Considerations

31. Selecting a data
vendor
6 things you
should consider
• Data transparency
• Commitment to quality
• Consistent, user-friendly
• Multi-sourced & fresh
• Flexible delivery options
• End-to-end data integrity

32. Data Enrichment – A global product portfolio
Addresses & Property
Verified and validated address and
property data for map display and
analytics
Boundaries
Administrative, community, and
industry-specific boundaries for data
enrichment and territory analysis
Demographics
Demographic and consumer context
data for better understanding people
and behavior
Points of Interest
Detailed business, leisure, and
geographic features for location
and competitive intelligence
Streets
Robust street-level data for mapping,
analysis, routing, and geocoding
Risk
Natural hazard boundaries related to
flood, fire, earthquakes, and weather
Expertly curated datasets containing thousands of attributes for faster, confident decisions

33. Why Precisely
We offer a complete solution for our
telecom customers:
• Hyper-accurate addresses and
location attributes
• Broader enrichment
of addresses with valuable context
• Collaborative solution approach
and continuous support

34. Questions?

35. Simplifying Risk Management
Geo addressing and Data
products are available to our
customers via the Precisely
Data Experience (PDX)
File format options will
be available per the
licensing terms of the
customer contract

36. Try it out
for yourself!
developer.precisely.com
Simplifying Risk Management

37. Let’s continue the
conversation…
Contact us
Set up a 30-minute exploratory
conversation
+1-877-700-0970
“Get in touch” on www.precisely.com
www.precisely.com
Demos
White Papers
Case Studies

38. Thank you