In an increasingly complex and competitive financial environment, small credit unions are on the ropes. Implementing efficiencies through reliance on a data analytics program might be their best chance to not just survive, but thrive.
Once the posterchildren for the movement, the proud collection of institutions serving single employers, church bodies, other affiliated groups, or nonurban areas has been wilting under pressure from all angles.
Over the last decade, an average of one credit union per day has been compelled to merge or forced into conservatorship by NCUA.
What’s particularly disheartening is that small credit unions haven’t shared in the post-recession spoils reaped by their larger credit union peers.
According to statistics from CUNA, while credit union membership growth continues to push toward 3% — a pace well above the U.S. population growth rate — the 48% of credit unions with assets less than $20 million are experiencing a 1.2% decline, while the 75% of credit unions with assets less than $50 million are sagging at a 0.6% clip.
That disparity also evidences itself in lending operations. Overall, credit union auto lending has risen 19.6% year-over-year as of June, but that number drops to just 3.5% for small credit unions. And while first mortgage loans outstanding rose 9.6% annually as of the end of the second quarter, small credit unions actually slipped by 0.1%.
The double whammy is that there is nearly no difference in operating expenses among credit unions with less than $1 billion in assets.
What’s a small CU to do? For starters, work smarter, not harder.
That’s where data analytics comes into play. Often mischaracterized as the province of the rich and powerful, proper application of the troves of data you possess about your credit union and your members provides you a chance to level the playing field in a cost-effective fashion.
For executives at small credit unions, access to a comprehensive data analysis platform will revolutionize the way you approach your job by returning two related and highly valuable assets: Time, and the ability to see the forest for the trees.
Consider the competitive advantage gained by regaining the hours you spend performing painstaking, rudimentary tasks such as gathering and assembling data from various departments, confirming the integrity of that data, and potentially recalibrating the reports spawned by that data.
Analytics platforms eliminate all of those headaches, allowing you to slice-and-dice the data a keystroke at a time and concentrate on recognizing and strategizing for the challenges and opportunities that exist for your credit union.
The ability to create consistent, multifactor reports is an invaluable tool from a business perspective but also keeps you in the clear from a compliance point of view, as examiners have come to not just appreciate but expect a high capability for producing documentation of every action taken by your operation.
The cost savings gained by recognizing ways to streamline or expand certain business functions, and allocate personnel accordingly, more than offsets the investment in a data analytics platform, especially when you stop to consider all of the aspects in which you can apply analytics within your credit union:
Loan portfolios: Monitoring volume and concentration levels, and also interest rate fluctuation, within credit card programs, mortgages, student loans, personal loans, and more.
Collections: Management of troubled accounts, with an emphasis on changing patterns that lead to an inordinate number of delinquencies and charge-offs.
Applications: Particularly in a variable, credit-based lending environment, evaluating and revamping policy based on the performance of various classes and types of loans, while factoring in the impact of credit score migration, as well as running what-if scenarios involving declined loan requests.
Deposits: Tracking the integrity of draft share, regular share and investment holdings, and maintaining proper loan-to-share ratios.
Marketing: Amalgamating deep, informational and behavioral member data from internal and external sources to assess the likelihood of members’ interest in various products and services, and tracking the productivity of messaging and offers.
Compliance: Maintaining comprehensive records of transactions and interactions to certify the organization’s commitment to documentation. From a defensive posture, monitoring for signs of disparate impact and other potential Fair Lending Act tripwires, as well as compliance with newly effective or upcoming regulations such as the Truth In Lending Act/Real Estate Settlement Protection Act Integrated Disclosure Rule (TRID). From a proactive posture, maintaining a robust Bank Secrecy Act and Anti-Money Laundering stance.
Accounting: Assessing profitability (organization-wide, and among individual members), liquidity, and capital levels, as well as allowance of lease and loan loss (ALLL) tolerances.
Internal: Monitoring productivity of various branches, departments, and even individual employees.
One executive at a small credit union recently stated that implementing data analytics was the best investment she’s ever made. With all of the pressures on small credit unions today, it’s time to investigate making that investment in the sustainability of your organization.