Banks and credit unions are constantly at risk of losing customers or members, and in order to stem the flow, they may offer their best customers better rates, waive annual fees and prioritize treatments. However, such retention strategies have associated costs, and you cannot afford to make such offers to every single customer. The success and feasibility of such strategies is dependent on identifying the right customer for the right action. SAS® Customer Analytics for Banking turns raw data into insight that banks and credit unions can use to manage marketing strategy intelligently and increase customer retention. The integrated software infrastructure enables business users to analyze complex customer behavior hidden in large volumes of historical data. You can then use that information to answer critical business questions, such as which customers are likely to try a new product and which are likely to leave the bank entirely. Learn more at http://www.nafcu.org/sas

1. SOLUTION OVERVIEW
SAS Customer Analytics
®
for Banking
Lower acquisition costs, improve retention rates and increase wallet share
Overview ■ Challenges
Banks are constantly at risk of losing • No single view of the customer.
customers, and in order to stem the flow, Customer data often resides in multiple
they may offer their best customers bet- operational systems across different
ter rates, waive annual fees and prioritize lines of business, leading to disparate
treatments. However, such retention and duplicate customer data.
strategies have associated costs, and
• Inability to predict customer
you cannot afford to make such offers to
behavior. Inconsistent and incomplete
every single customer. The success and
customer data, plus lack of collabora-
feasibility of such strategies is dependent
tion across departments, make it hard
on identifying the right customer for the
to build effective behavioral models.
right action.
• Ineffective or nonexistent
Identifying which customers are most segmentation/customer profiling.
likely to leave is just the first step; you Early withdrawals and low retention
must also be able to subsegment cus- rates jeopardize opportunities for
tomers at risk of attrition into those cus- recovering acquisition expenses over
tomers most likely to respond positively the long term.
to specific offers. Likewise, cross-selling
• Decreased customer loyalty.
and up-selling campaigns also should be
Increased competition continually
targeted at those customers most likely to
erodes customer loyalty.
respond to and be accepted for offers.
SAS® Customer Analytics for Banking
turns raw data into insight that banks
can use to manage marketing strategy
intelligently and increase customer reten- You can then use that information to
tion. The integrated software infrastruc- answer critical business questions,
ture enables business users to analyze such as which customers are likely to
complex customer behavior hidden in try a new product and which are likely
large volumes of historical data. to leave the bank entirely.

2. Better understand and
drive decisions related
to customer profitability
■ Key Benefits
How SAS® Can Help Uncover New Sales Opportunities,
and Increase Wallet Share
SAS Customer Analytics for Banking
SAS Customer Analytics for Banking
delivers specific analytical techniques to Fast and accurate segmentation, model
enables you to:
help you understand and drive decisions development and management for all
• Create a single view of the customer.
related to customer profitability. The solu- consumer-banking products give you
• Uncover new sales opportunities tion enables you to segment customers greater insight into retention and cross-
and increase wallet share. according to a multitude of variables – sell/up-sell strategies. Predictive analytics
• Improve retention rates. demographics, geographies, account (e.g., decision trees) can help you identify
• Reduce marketing costs. history, etc. – to create more meaningful potential cross-sell and up-sell prospects.
and targeted marketing programs. Easy-to-use segmentation capabilities
enable analysts to better understand
■ Key Differentiators The solution helps you improve reten- which customer characteristics lead
Only SAS Customer Analytics for Banking tion rates by determining causes and to reduced usage and attrition. That
provides you with: predicting future customer attrition. In understanding can then be used to
• Superior data management capabilities. addition, by applying analytics to his- experiment and identify specific groups
torical data, you can increase revenue for model development or action.
• A banking-specific data model and
and wallet share by knowing which
prebuilt analytic capabilities.
customers are good candidates for Improve Retention Rates
• Improved productivity via user-
cross-selling and up-selling.
friendly interfaces and intuitive, SAS Customer Analytics for Banking
Web-based reporting. lets you develop, validate, deploy and
Create a Single View of the Customer track customer analytics models with
SAS Customer Analytics for Banking greater speed, more flexibility and at a
consolidates all customer data into lower cost than outsourcing alternatives.
one place – regardless of source. The You can perform ongoing, on-demand
solution cleanses the data and trans- scoring of new and existing customer
forms it to provide a complete picture applications to identify the best custom-
of the entire customer relationship. In ers for retention and cross-sell/up-sell
addition, the solution: strategies. Detailed analytics, such as
cluster analysis, give you insight into the
• Supports both customer-centric and
major factors that influence customer
household-centric views.
retention, and an accurate early-warning
• Delivers consistent, accurate, verifi- alert system identifies those customers
able and up-to-date information. likely to leave in the future.
• Includes a comprehensive warehouse
data model that serves as a single Reduce Marketing Costs
version of the truth and standardizes
banking data elements to ensure con- SAS Customer Analytics for Bank-
sistent terminology and reporting. ing enables you to connect offers to
the right customers using predictive
analytic techniques based on demo-
graphic, geographic and behavioral
data across the organization.

3. Capabilities • Data cleansing provided in native
languages, with specific language
• The ability to be deployed in multiple
databases, including SAS, Oracle,
Superior Data Management awareness and localizations for more Microsoft SQL Server, Teradata
than 20 worldwide regions. and DB2.
An enterprise data management environ-
ment lets you access data from virtually • Out-of-the-box standardization rules • Business data definitions consistent
any system in any form (e.g., bureau, that conform data to corporate stan- with global banking data standards.
application, billing-payment and transac- dards, plus the ability to build cus- • A customer analytics-specific data
tion data), transform and cleanse data, tomized rules for special situations. mart with hundreds of derived and
and handle data migration projects – all • An interactive GUI that enables data aggregated variables to facilitate
through a versatile environment that is stewards to profile operational data analytics and reporting.
easy to deploy. In addition, the solution and monitor ongoing data activities. • Support for a variety of business issues.
provides: • Customized and reusable data quality
• An easy-to-access, consistent, robust business rules that can be accessed Reporting and Business Intelligence
data mart for integrated data extrac- directly within process job flows.
Comprehensive, easy-to-use business
tion, householding/deduplication, • The ability to migrate or synchronize
intelligence software provides insights to
mapping and loading capabilities. data between database structures,
empower users at all levels to make bet-
• The ability to add custom fields to the enterprise applications, mainframe
ter decisions faster. Capabilities include
comprehensive banking data model. legacy files, text, XML, message
portals and dashboards, report viewing,
• Wizards for accessing source sys- queues and a host of other sources.
report building, advanced data explora-
tems, creating target structures, • The ability to join data across sources tion, Microsoft Office integration, guided
importing and exporting metadata, for real-time access and analysis. analysis, metadata management,
and building and executing data ETL guided SAS OLAP cube creation and
process flows. Banking Data Model application development. In addition,
• A dedicated GUI for profiling data and the solution includes:
A comprehensive, scalable data model
identifying and repairing source system • A Web-based, interactive reporting
provides a single version of the truth for
issues, while retaining the business interface for business users.
an enterprise data warehouse covering
rules for later use in ETL processes.
all key banking areas. Historical data is • Query capabilities for all levels of
• Data cleansing and augmentation, stored at a granular level to support all users across multiple BI interfaces.
and can be customized for real-time reporting and analytical requirements. • The ability to slice and dice multidi-
processes. The solution supports all consumer- mensional data using a special slicer
• Enterprise connectivity to data lending products and has the flexibility to dimension and by applying filters on
sources – ODBC, IBM DB2/UDB, extend to new lines of business as needs any level of a hierarchy.
Microsoft Access and Excel, Microsoft arise. The solution also includes:
• Critical first-alert, call-to-action dash-
SQL Server, Netezza, Oracle, Sybase, • A comprehensive dictionary that boards that let you detect and pre-
SAS, Teradata, core banking systems describes thousands of banking data empt scorecard instability, as well
and more. elements. as deliver performance information
• Support for unstructured and • A complete mapping of physical data to executive management and other
semi-structured data. structures to business terms. decision makers.
• Data quality embedded into • Both logical and physical data • Dynamic business visualization tools
all processes. models – e.g., ERwin data models for interactive data exploration, visual
and SAS metadata. queries and more.

4. • Access to SAS capabilities for data including creating variables on demand provide early-warning indicators when
access, reporting and analytics without requiring code development. a key customer’s behavior is about
directly from Microsoft Office, includ- • The ability to combine model predic- to change.
ing Word, Excel and PowerPoint. tions to form a potentially stronger
• Wizard-driven report creation within solution (e.g., averaging, voting Greater Productivity
Microsoft Office tools. and maximum).
Only SAS provides prebuilt processes
• Model evaluation to compare multiple and analytic techniques with a ready-to-
Data Mining and Predictive Modeling models in a single framework for all deploy architecture specifically designed
data sources. to address a wide range of banking
SAS Customer Analytics for Banking
enables data miners and business business challenges, which boosts the
analysts to create highly accurate pre- Why SAS®? productivity and self-sufficiency of your
dictive and descriptive models based business analysts and subject matter
Superior Data Management experts. In addition:
on the analysis of vast amounts of data
within the bank. Results can be shared Only SAS gathers all customer data into • A guided, user-friendly interface
throughout the organization to deliver a single version of the truth by pulling enables business analysts to develop
analytical information and incorporate together data from all touch points and predictive analytical models for cus-
models into business processes. The distribution channels. The solution also tomer analytics, including those for
solution also includes: automatically validates data as part of segmentation, retention, cross-sell
• A powerful set of interactive data prep- the data integration process so you can and up-sell.
aration tools for optimally addressing be confident in its integrity throughout • SAS’ award-winning business intel-
missing values, filtering outliers and the organization. ligence technology enables intuitive,
developing segmentation rules. Web-based reporting.
• An unmatched suite of predictive Banking Data Model and • A portal framework hosts scorecard-
and descriptive modeling algorithms, Prebuilt Analytics ing, dashboards and other reporting
including: decision trees, neural SAS helps you jump-start your analytic capabilities to disseminate information
networks, memory-based reason- capabilities with banking-specific logical throughout the organization.
ing, hierarchical clustering, linear and and physical data models. In addition, • Business users have ready access to
logistic regression, associations, mar- SAS enables you to: online reports containing performance
ket basket analysis, sequence and data in historical comparisons with
• Reduce costs and implementation
Web path analysis, and more. drill-down capabilities on the latest
time with prebuilt customer data
• A convenient GUI application for marts and predictive models. key metrics, such as line of business
exploring segmentation and creating revenue and retention rates.
• Accurately forecast customer behav-
data sets for model development,
ior using SAS’ powerful predictive
analytics.
• Analyze data for trends to segment
markets, determine customer value
and calculate retention scores that
About SAS
SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market.
Through innovative solutions delivered within an integrated framework, SAS helps customers at more than 50,000 sites improve
performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world
THE POWER TO KNOW® www.sas.com
.
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