Charting Your Future Through Enterprise Data Analytics
Lending remains critical to both a credit union's member service and revenue generation. However, even highly competitive retail and business loan offerings must contend with several challenges. With the influx of non-traditional and online lenders, consumers and businesses have more options to secure funds than ever before. In addition to the heightened competition in lending, while persisting low interest rates might be excellent for member service, they inevitably hinder loan revenue. Low interest rates, combined with requirements to keep more money in capital reserves, means credit unions simply cannot afford to let excess funds go un- or underutilized. They must lend wisely with the funds that are available, especially until they can generate more revenue from their loan portfolios. To optimize financial performance, credit unions cannot leave funds on the table, nor can they shoot from the hip in determining how to best allocate those funds.
Strategizing around revenue growth should begin with the elimination of disparate spreadsheets for housing data in favor of a single, centralized repository. Only when both internal and external data from the core, general ledger and third-party systems is combined can a credit union accurately pinpoint both limitations and opportunities for revenue growth. As credit unions increasingly realize the value in tying the measurement of revenue to their back-end systems, they must begin by consolidating, organizing and harnessing their own data.
With all metrics in one location, credit unions can maximize profitability based on data – not guesswork – and answer the questions: What are our risks? What areas are most profitable? Easier access to data enables credit unions to then use data as the foundation for building strategic plans based on what they wish to sell. Many organizations continue to rely on industry standards; however, by using their own data, credit unions can accurately segment data by audience, product, interest rate, and term or risk rating, and create communications and marketing programs assured to deliver the right offer to the right person at the right time. The correlation between this level of precision and response and return rates will be evident, as will the impact on revenue.
Integrated data solutions also provide credit unions with a more holistic view of relationships, which is critical to evaluating revenue growth opportunities. Credit unions should rely on data points to both summarize relationships and identify whether a relationship holds risks, or on the flip side, if there are opportunities to deepen the relationship. For instance, a CFO with access to relationship data who analyzes loan to deposit ratio might uncover underutilized deposits. Knowing this represents revenue left on the table for the institution, and the CFO can bring these insights to the finance team, analyze “what if” scenarios and ultimately determine the best outcome for these funds.
With this granular level of data, a credit union's marketing team is then well equipped to build a campaign to resonate with the right audience. They can create the strongest possible omnichannel member interaction strategy based on the target audience, whether the aim is to reach millennials who are compelled by SMS messages or Generation Xers who prefer to receive offers via email. Relationship-building and cross-selling efforts become more powerful when all departments are working from the same data and when the results of relationships and marketing activities are not only reviewed, but truly measured.
Focus on Unification
Business intelligence solutions can't do their jobs if they’re set to only evaluate a data silo that focuses on certain areas of the institution or specific business lines. Understanding revenue growth opportunities requires credit unions to foster a unified user experience for data analytics that serves the needs of the entire institution. It is not possible to evaluate revenue without looking at cost – they are opposite sides of the same coin. If a credit union is not containing costs and risk, its revenue objectives will undoubtedly be deterred.
Giving employees across the institution and across departments – from CEOs and CFOs to marketers and tellers – the ability to interact with data analytics is the best way to answer the ultimate question: How can we improve our organization's results? Empowering employees with the data they need based on their roles enables the institution as a whole to take into account the countless factors impacting their organizational performance.
Consider Profit Risk
When addressing revenue growth, credit unions must look beyond asset liability, credit and operational risk. There is another element that is critical to revenue – profit risk. Credit unions must evaluate risk on their income statements, not just their balance sheets, as many activities that positively impact a balance sheet do not necessarily translate into sustained profitability and revenue growth. Knowing with certainty what products members need and providing those products requires an in-depth assessment of profit risk at the regional, branch, product, member and relationship level. By effectively identifying profit risk, credit unions can future proof their organization, diversify product penetration, reduce risk and increase wallet share.
It is nearly impossible to discuss revenue growth without bringing up lending. And, gaining a competitive advantage in both retail and business lending remains a tall order. Yet, credit unions’ most valuable tool for driving profitability and revenue – their own data – all too often goes underused. By applying analytics throughout the enterprise, credit unions can gain the insight to not just recap the past but to chart their futures.
Naseer Nasim is CEO of Baker Hill. He can be reached at 800-821-8664 or firstname.lastname@example.org.