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Build credit union revenue streams with data analytics By Wendy Grieco

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The pandemic has upended the business strategies of enterprises in many industries. For financial institutions, a decline in lending has required them to consider other strategies to stoke growth. For many credit unions, it has changed their emphasis from primarily focusing on member retention to an approach designed to grow revenue. To facilitate this evolution,
The post Build credit union revenue streams with data analytics appeared first on ibi.

The pandemic has upended the business strategies of enterprises in many industries. For financial institutions, a decline in lending has required them to consider other strategies to stoke growth. For many credit unions, it has changed their emphasis from primarily focusing on member retention to an approach designed to grow revenue.

To facilitate this evolution, credit unions are increasingly mining data to identify profitable areas of focus. By using data analytics, credit unions can do more with less, making the most of their marketing resources and controlling costs while identifying promising new revenue sources.

Developing data analytics strategies

With a multitude of data sources in the modern business environment, it’s important to take a big-picture look at the data your credit union is collecting to identify the best approach to maximizing that data. In doing so, you’ll likely see a variety of ways that you can use data analytics to build revenue streams.

These include:

Embracing innovation

With fintech companies creating new financial products and changing the way existing ones are delivered, credit unions and other financial institutions must change to keep up with consumer demand. Many of these products are targeted at improving processes that are inefficient and hard to use.

Credit unions can use data analytics to identify which products and services are most likely to benefit from innovation. Even though these advances may reduce fees from services such as checking accounts by creating no-cost alternatives, it’s crucial to offer them to help retain members.

Credit unions need to compete with fintech firms that may create cutting-edge financial applications but often don’t have a large customer base and associated data. By adopting the most promising innovations, credit unions can both enhance member retention and create new revenue streams.

Check out new revenue opportunities

In this new financial world, credit unions must not only retain members but also provide them with attractive products and services that generate revenue.

Data analytics can be a key tool in this process. Some areas where opportunities for increased revenue may appear include:

Lending: With restored capital requirements focussed on deposits, credit unions may have opportunities to pick up the slack in areas such as mortgage lending, auto lending, and home equity loans.
Value-added services: Credit unions are well placed to offer exclusive services, programs, and products designed to boost member loyalty and generate additional revenues.

These might include:

Affiliate discount programs
Loyalty reward benefit plans
Commercial matchmaking fees
Car purchase program

Putting data analytics to work

After selecting a data analytics strategy and potential products and services that could benefit from its implementation, it’s time to dig into the data and see what the numbers say.

Some key indicators to evaluate include:

Lifestyle indicators

Lifestyle indicators are among the wealth of data captured by modern software apps. These indicators can include factors such as homeownership status, marriage, and other characteristics that help you identify members who may have secured mortgages with other financial institutions. Another example of a lifestyle indicator could be a large check deposit into a member’s account, which may indicate that the member has received a bonus or inheritance and may be open to discuss investment opportunities.

Predictive data

In addition to lifestyle indicators, predictive algorithms can ingest data related to member actions to identify an interest in loan products. An example would be members who search on a credit union’s site for information on mortgage loan origination or refinance options. After your data analytics solution has singled out these members, you can approach them with targeted offers in your online and mobile banking apps to take advantage of their demonstrated interest in your specific product offerings.

You can offer current lending clients add-on products such as auto loans, home equity loans, and checking and savings accounts.

Members in need of assistance

The pandemic has caused some members to experience financial distress, while others have reacted cautiously, increasing saving and paying off debt. By carefully evaluating their data, credit unions can identify customers who may need help and tailor programs to assist them. For instance, by identifying members who are receiving unemployment insurance, credit unions can offer specialized services such as information on how to tap 401(k) plan loans or rollovers or offer free financial planning sessions.

Another indicator of potential financial distress could include members who no longer receive direct deposits from employers. Whether or not members in this category need assistance, contacting them can help to increase member loyalty and emphasize the personal touch credit unions can offer compared to large financial institutions such as money center banks.

As these members return to better financial health, the support you provided will place your credit union in a good position to benefit from their increased business.

Member balance sheet improvement opportunities

With consumers in the U.S. saving more and lowering debt, credit unions can assist their members by providing them with access to financial planning services and products.

Offering wealth planning and retirement planning services can help credit unions overcome revenue declines they are experiencing linked to lower loan volumes. Such services can generate solid revenue streams in the form of ongoing management fees in addition to fees for related services.

Another potential revenue source from this trend centers on savings applications based on incentives, which have been growing relative to traditional fee-based savings accounts. By using innovative savings technologies, credit unions can capitalize on this trend and create new revenue streams by offering their members products that help them save.

Data analytics based on customer behavior can help guide the type of products you create for these purposes.

Improve revenue streams from existing products and services

Credit cards and revolving credit are examples of products that can benefit from insights gained from data analytics. By analyzing member behavior by segment, credit unions can more precisely target their marketing efforts. Understanding the patterns which characterize different member groups can help optimize your ability to generate increased revenue.

For instance, demographic information relating to the uptake of products by age can be helpful in determining what products are most likely to be attractive to new members in various age groups.

Analyzing your data, whether for creditworthiness, product mix by age group, or any other relevant metric requires a data analytics solution that can mine the totality of your data for actionable insights. ibi, a TIBCO company, provides organizations around the world with analytics that help them maximize the value of their data. If you are ready to talk, set a time with our, Ask the Expert.

On June 22nd, join me for a webinar with CUTimes: Understand the Member Journey to Drive Growth for Your Credit Union to learn more

About the Author

Jon M. Deutsch is Managing Director of Financial Services Solutions at TIBCO Software. Jon leads the effort to develop market-leading enterprise data and analytics solutions for global financial services, with a focus on credit unions.

 

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