How Does Leveraging Data Help Serve Members?

Digital banking trends are not just growing more popular – digital options and functionality is enhancing the member experience and quickly becoming a service expectation.

Think about what you used to go to a store to buy that you now have delivered to you by Amazon. In order to effectively leverage these tools, credit unions must prioritize the role of data. More automation, artificial intelligence and machine learning tools are now being introduced that help provide actionable insights to credit unions that enable profitable growth.

Ongoing digital expansion is presenting a unique challenge and opportunity for more keen, nuanced data sources to provide the “who, what, where, when and how” of member behavior. To respond to digital trends, credit unions need to not only be gathering necessary data but intentionally deploying and leveraging it in order to best serve their members. A data-driven strategy can enable credit unions to generate personalized service interactions and relevant product offers for members.

Data Optimization: Why It Matters

Many times it can seem like credit unions are looking in the rear view mirror and reacting to events that have already happened, rather than looking for and anticipating what’s ahead. This isn’t usually due to a lack of data, but a lack of data analytics that can best interpret data trends. By investing in data analytics and predictive modeling, institutions can yield powerful insights that provide a more strategic view of their member services, loan offerings and risk management. Identifying profitable growth opportunities enables credit unions to continue to invest in the technology they need today and in the future.

Data analytics and predictive models can help credit unions see how emerging economic trends may impact different areas of business. That, in turn, can help the institution:

• Set expectations on portfolio performance;
• Empower confident decision-making;
• Set pricing strategy to optimize for yield, payoff and profit;
• Conduct product and service analyses and recommendations;
• Monitor and observe user behavior, and create profiles that help the credit union target similar members;
• Analyze competitors and make comparisons with benchmarking metrics;
• Effectively assign and deploy capital; and
• Mitigate risk.

Four Impact Metrics for ­Optimized Data

1. Deliver analytics for strategic growth. Using current intelligence and predictive analytics, credit unions can leverage analytics to build strategic growth plans across their business. Analytics can enable insight into risk, operations, mergers and acquisitions, loan participation, marketing, member behaviors and more. Reviewing data can help the credit union identify new opportunities to strategically improve and adapt. Whether it’s identifying new efficiencies, enhancing core competencies, improving brand messaging or adapting to feedback, analytics offer consultative support that helps back strategic growth initiatives.

2. Integrate data resources for accurate forecasting. Consolidating and analyzing data is a key component of understanding the wants and needs of current and prospective borrowers. Painting a more accurate “big picture” of borrower trends requires leveraging different data sources, including:

• Business systems across the organization (e.g. core processing, LOS, card processing and marketing systems);
• Consumer engagement channels (e.g. social media pages and website interactions);
• Third-party data (e.g. behavioral and purchase habits or data from bureaus, LexisNexis, Amazon, etc.); and
• External market analysis and data sources (e.g. predictive and prescriptive data analytics models).

Aggregating data presents opportunities for modeling and predictive analytics that can help quantify strategic options for future business growth from a single reporting source.

3. Deploy assets effectively. Drawing on trends and insights from data sources can help credit unions reach more educated conclusions about expanding certain business areas, or retracting other areas of the business, in order to most effectively reach and attract untapped markets and consumer demographics. Taking steps to optimize data and leverage analytics can help credit unions generate new financing opportunities and effectively deploy business assets that result in the highest growth impact. This could include demographic data that identifies a member’s stage of life, current financial products, buying history, payment history and interaction history, which can be used to leverage insights around when and how to find the best loan or financing options currently available to meet their anticipated needs.

4. Manage your risk exposure. Predictive analytics models are quite valuable for enhancing a lending institution’s risk modeling and pricing to ensure a favorable ROI on your portfolio. Previous loan data, banking and deposit data, and insurance tracking data collections can all be tracked for red flags for loan default risks, as well as other types of financial loss that can help credit unions assess and anticipate risk exposures.

Optimized data helps credit unions develop a 360-degree perspective on members and business, which is an important perspective to have in today’s competitive environment where fintechs, banks and other organizations are targeting members with their own data insights. Leveraging the power of data in a single, integrated engine is a strategic way for credit unions to navigate the road ahead.

Mike Bryan Vice President of Data Strategy Allied Solutions Carmel, Ind.