How credit unions are avoiding data analytics mistakes

August 9, 2017 by W.B. King
Aggregating data is one thing, but effectively analyzing it or predicting member behavior is quite another. And, many times well-intended executives make mistakes in this all-important pursuit.

So what are the biggest mistakes CUs make when it comes to data analytics? Credit Union
Journal queried a panel of experts to find out.

“Our primary methodology was too focused on transactional data from within the core at first.
The challenge is that, like many credit unions, some transactional data, such as credit card and
mortgage servicing, is housed elsewhere,” said Redwood Credit Union’s CIO Tony Hildesheim.
“Without all of your loan data, your reporting engine is not all that effective.”

Symitar Solutions Team Business Consultant Patty Moore added that a common mistake she
sees CU executives making when collecting data is “failing” to view performance measures in
context.

“In talking with credit unions who are interested in or pursuing predictive analytics, they have
more certainty about what they want to predict,” said Moore, “such as which loans have a high
probability of charging off [or] which members are at risk for closing, but they do not always
have an associated action plan to go along with the predictions.”

Asking the right questions
For the $1 billion Santa Rosa, Calif.-based Redwood CU, which supports 285,000 members at
19 branches, data gathering must answer at least one of the following five important questions,
explained Hildesheim. Does the analytics report:

1. Allow you to take an action?
2. Allow you to make a decision?
3. Does the data drive profitability?
4. Does the report drive staff engagement?
5. Most importantly, does the report drive member engagement?

“Our primary methodology is to focus on bringing the data together and establishing
normalization and definitions,” said Hildesheim. “The actual analytics is not all that difficult, once both the meaning and question are established.”

In many cases, credit unions executives make data-related mistakes by looking at data in
isolation, said Tim Keith, co-founder and chief strategy officer of Infusion, a Little Rock, Ark.based firm specializing in in data analysis for marketing campaigns.

“Credit unions need to seek partners with a proven track record who are willing to devote
qualitative time to the partnership,” said Keith. “The unfortunate reality is that there are many excellent vendors who focus solely on larger institutions and simply do not have a servicing model designed to work with the vast majority of credit unions.”

Keith further explained that most credit unions operate as two to three member bases within a
member base. These include single-service savings members, indirect loan members (with only
a nominal savings balance) and relationship members. Without data integrated across products,
he said, there is “no way” of distinguishing these groups, which is “fundamental to
understanding” the member base.

“Single service members typically make up 15 to 50 percent of an institution’s member base.
Without a household-level view that brings together accounts within a relationship, the institution has no way of distinguishing the member who has five different account types with the institution versus the member that only has savings,” he said. “Identifying single service members allows the institution to begin the process to assess how much potential those members have to bring additional business.”

Among Infusion’s clients is the $550 million Bartlett, Tenn.-based First South Financial Credit
Union. A recent data-gathering pain point centered on analyzing credit card data and signing
members up for cards during the onboarding process, explained Senior Vice President of
Marketing Delynn Byars.

“Marketing to indirect loan members has been a huge success,” said Byars, whose CU supports
approximately 56,000 members at 16 branches. “Many credit unions face a challenge with these
members because they don’t have the same level of awareness or attachment as those who
opened their accounts via other avenues.”

Byars explained that the CU worked with Infusion to develop an onboarding strategy, which
included an onboarding process with offers geared toward indirect members. At the beginning of
2016, she said, the CU’s product and service penetration was 2.89 for indirect members. By the
end of June 2017 that figure had increased to 3.35.

“Now that may not sound like a lot, but these members have basically no loyalty or affinity for
us,” said Byars. “They’re more like prospects.”

Data warehouse woes
One way to avoid data missteps is by understanding what data should be stored where,
explained Hildesheim. It doesn’t make sense, he said, to “copy data from one database to the
warehouse” if the analytics engine can access that data directly without performance of that
system.

“Transactional and financial data are two types of data that we determined needed to be stored
in the warehouse versus, for instance, web and online banking use that is directly accessible,”
said Hildesheim. “We are fortunate that our core provider [Symitar] also has a data solution
called Advanced Reporting for Credit Unions.”

Moore explained that Symitar’s ARCU has 315 pre-built standard reports. ARCU clients range
from $52 million in assets to $8 billion, with the average asset size for an ARCU client being
$1.1 billion.

“The larger-than $1 billion in assets credit unions are typically the ones with the in-house
resources to pursue predictive analytics on their own,” he said. “Trend reports include year
over-year, month-over-month, day-over-day comparisons so that anomalies can be detected,
patterns identified and data viewed in historical context along with goals and peer comparisons.”

Recently, Hildesheim employed ARCU to answer data-related questions, such as “Why do
members leave” and “How to detect signs of potential mobile fraud.” For the latter question, five critical elements were identified, including deposit velocity across the entire member base and geolocation data.

“Leadership needs to focus on making sure the right questions are being asked for the results
that they trying to achieve,” said Hildesheim. “Otherwise, you risk just ending up with a report
that doesn’t add value.”

Original Source: https://www.cujournal.com/news/how-credit-unions-are-avoiding-data-analytics-mistakes?brief=00000158-73f9-d502-a5fd-7bfbd3d10000

Infusion marketing campaigns generated over 100,000 new accounts for financial institutions

Financial institutions experience exponential growth as a result of data-driven, omni-channel marketing campaigns

Little Rock, Arkansas, August 21, 2017 – Infusion, a provider of data-driven direct marketing campaigns that generate strategic growth for community banks and credit unions, has generated over 100,000 new accounts for financial institutions.

To date, Infusion has generated 102,263 accounts with balances of $2.3 billion in response to its digital ad, email and direct mail campaigns. Of the accounts generated, 54,000 are deposit accounts, 39,000 are loans and 8,000 are electronic services. Over 65 percent of accounts generated resulted from cross-selling campaigns to existing customers, while 33 percent were accounts opened by prospective customers. Notably, 30 percent of the campaign responders opened additional deposit and loan accounts during the marketing campaign in which they responded.

The vast majority of these accounts were generated through Infusion’s unique Pay for Performance model, meaning Infusion is paid based on measurable objectives being achieved during the execution of the marketing campaigns. The development and implementation of these programs is driven by the Infusion ProfitGenerator® process, which starts with an in-house assessment of the financial institution’s core data and the development of a strategic omni-channel marketing plan to boost growth in central categories. Then, Infusion conducts and pays for the execution of the marketing campaigns, tracks and measures the results across channels and quantifies the ROI. Financial institutions are only charged when measurable, pre-determined results have been met.

“Crossing the 100,000 accounts generated threshold is a major milestone for both Infusion and our clients, and proves financial institutions can experience exponential growth by using data to anticipate the needs of their customers or members,” said Tom Cloninger, co-founder and chief executive officer at Infusion. “And the continued account generation financial institutions experienced from our campaigns underscore how strategic, targeted marketing sets the stage for sales opportunities beyond just the promoted product.”

About Infusion
Headquartered in Little Rock, Arkansas, Infusion uses data analysis and proprietary industry normative data to create and execute multi-channel marketing campaigns that generate strategic growth for financial institutions. The Infusion ProfitGenerator process and corresponding campaigns are used to grow deposits, loans and transactional fee income at small and medium sized banks and credit unions. For more information, visit http://www.profitgenerator.com/.

Original Source: https://www.cuinsight.com/press-release/infusion-marketing-campaigns-banks-generated-100000-new-accounts-financial-institutions

Infusion Announces Results of ASE Credit Union Cross-selling Campaigns

Little Rock, Arkansas, November 10, 2016 – Infusion, a provider of data-driven direct marketing campaigns that generate strategic growth for community banks and credit unions, announces announces new client Montgomery, Ala.-based ASE Credit Union has increased loans and deposits after completing the first wave of its ProfitGenerator® Cross-sell Program.

Infusion’s cross-sell campaigns inform existing customers or members about additional financial services their bank or credit union has to offer. The first wave of the cross-selling program for ASE Credit Union included two campaigns to promote checking accounts and two to promote loans. The campaigns produced 890 responses (new checking accounts and loans) with balances of $7.6 million. Campaign responders also opened 349 other deposits and loans during the campaign they responded to. In addition to buying a loan, loan campaign responders also increased deposits with ASE by a net of $1 million during campaigns.

ASE Credit Union is a state-chartered credit union in the Greater Montgomery Metro area serving Montgomery and the eight surrounding counties. ASE serves more than 27,000 members in Alabama and elsewhere. ASE operates five home branches, three in Montgomery, one in Millbrook, one in Wetumpka, and access to thousands of service centers nationwide. ASE was initially chartered as Alabama State Employees Credit Union in 1954 and then granted a community charter in 2001.
Infusion uses its ProfitGenerator process to turn core data into targeted campaigns that project final results and ROI for financial institutions. Infusion’s analysis of core data and proprietary targeting methodology are able to efficiently target existing financial institution clients to successfully expand customer relationships.

“Infusion’s ProfitGenerator Cross-sell Program is able to educate our members on how we can meet their financial needs through the distribution of targeted information,” said Calvin Cherry, vice president of marketing at ASE Credit Union. “We saw real growth in loans and deposits at the credit union coinciding with the campaigns and look forward to continuing our relationship with Infusion to better inform our members of the services we offer.”

About Infusion
Headquartered in Little Rock, Arkansas, Infusion uses data analysis and proprietary industry normative data to create and execute multi-channel marketing campaigns that generate strategic growth for financial institutions. The Infusion ProfitGenerator process and corresponding campaigns are used to grow deposits, loans and transactional fee income at small and medium sized banks and credit unions. For more information, visit http://www.profitgenerator.com/.

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