api-lead-approach
the-amazon-lending-experience
executing-advanced-analytics-do-s-and-don-t
lending-transformation-old-vs-new
data-journey-building-strong-analytical-practices
4-step-iterative-process-building-a-relevant-analytics-practice
significant-measures-towards-new-normal
building-a-strong-analytics-practice-recipe-for-success
data-warehouse-evaluation-and-implementation
explainable-ai-trust-and-transparency
forecasting
top-50-members-using-transactional-website-jun-2020
top-50-cus-with-highest-and-lowest-efficiency-june-2020
importance-of-financial-risk-management
secret-sauce-for-long-term-sustainable-business-intelligence-succ
top-pfm-technologies
secret-sauce-for-long-term-sustainable-business-intelligence-succ
top-pfm-technologies
data-warehouse-and-bi-technologies-opportunities-challenges
top-chatbot-technologies
keys-to-building-an-effective-branch-or-atm-network
top-50-credit-unions-with-highest-and-lowest-accounts-per-member
lowest-and-highest-net-income-per-branch
marketing-holy-grail
top-50-most-and-least-delinquent-credit-unions
modern-marketing-technologies
incremental-low-cost-data-driven-wins
power-of-storytelling
the-cost-of-not-investing-in-data-governance
questions-you-should-ask-before-investing-in-data-warehouse
learnings-from-new-data-based-on-auto-loan-pricing
5-questions-you-need-to-ask-before-investing-in-data-governance
digital-marketing-maturity-models-for-credit-unions
marketing-expense-per-member
top-2-reasons-that-are-holding-credit-unions-back-when-they-are-i
using-data-analytics-to-manage-lending-complexity-while-driving-h
5-reasons-your-credit-union-should-invest-in-data-and-digital-now
top-50-most-and-least-efficient-credit-unions
retail-financial-services-outlook-during-covid-19
use-of-operational-analytics-to-mitigate-the-impact-of-covid-19
top-50-credit-unions-based-on-asset-size
cu-peer-comparison-dashboard
cu-peer-benchmark
all-about-machine-learning-engineering
top-web-design-trends
most-important-social-media-marketing-trends
state-of-digital-marketing-maturing-in-credit-unions
top-kpis-for-email-marketing
data-cloud-and-the-digital-transformation-imperative
digital-trinity-and-you
phases-of-financial-industry
analytics-roundtable-workshop
invitation-to-join-digital-transformation-hub
analytics-in-the-credit-union-business
value-of-member-centricity-and-analytics-in-the-growth-of-cus
all-about-membership-analytics
top-fraud-management-technologies
getting-started-with-your-data-analytics-journey
explore-vizualization-for-credit-unions
investment-in-website-personalization-technologies
data-analytics-supporting-cu-s-first-member-philosophy
loyalty-rewards-and-retention-technologies
member-experience-analytics
channel-analytics-and-its-importance
project-portfolio-management-technologies
investment-in-self-service-data-preparation-technologies
self-service-data-preparation-technologies
new-frontier-in-customer-experience-management
role-of-marketing-analytics-in-credit-unions
important-aspects-of-consumer-lending-analytics
kpis-on-website-analytics
journey-towards-bank-less-banking
investment-in-crm-technologies
top-omni-channel-vendors
conversational-banking-solutions
/top-kpis-for-chief-information-officer
mistakes-to-avoid-when-implementing-a-omnichannel-member
top-things-to-consider-when-building-dashboards
making-digital-marketing-more-agile-through-tag-managers
cecl-solution-providers
mistakes-to-avoid-while-implementing-marketing-automation
p2p-payment-integrated-solutions
kpis-for-social-media-tracking
kpis-for-human-resources-management
investment-in-fintechs-should-or-should-not
top-kpis-for-online-banking
investment-in-marketing-automation-technologies
investment-in-e-signature-technologies-should-or-should-not
tips-and-tricks-to-a-successful-bi-program
kpis-for-credit-card-business
kpis-for-digital-marketing
kpis-for-consumer-lending
hot-topics-for-credit-union-data-leaders
kpis-for-debt-collections
kpis-for-finance
website-personalization-tools
data-integration-technologies
robotic-process-automation-tools
why-data-analytics-initiatives-fail
electronic-signature-softwares
data-governance-tools-for-credit-unions
digital-and-mobile-banking-technologies
report-inconsistencies-are-frustrating
is-your-culture-ready-for-data-analytics
three-big-data-myths
turning-transaction-data-into-a-goldmine-a-becu-case-study
call-for-presentation-for-2019-credit-union-analytics-summit-is-n
top-10-keys-to-successful-data-analytics-practice
credit-union-chooses-accountscore-for-open-banking-transaction-da
how-much-do-you-spend-to-serve-a-customer
marketing-automation-technologies-for-credit-union
alexa-ask-first-abilene-fcu-for-my-balance
dataweb-content-management-technologies-for-credit-unions
efficiency-ratio
web-analytics-technologies
data-warehousing-software-for-banks
customer-experience-software
the-best-kept-secret-for-credit-union-data-analytics
mark-sievewright-on-technology-trends
naveen-jain-on-credit-union-analytics-summit-2018
why-analytics-doesn-t-make-a-difference-by-gary-angel
cuas2018-harnessing-the-right-data
build-a-financial-phone-assistant-for-your-credit-union-in-3-step
2018-culytics-analytics-challenge-winner
update-from-naveen
error-resolution
benefits-of-conversational-apps
who-are-your-most-valuable-members-part-1
how-alexa-can-help-your-credit-union
top-10-kpis-for-measuring-retail-channel-performance
how-much-is-too-much-personalization
top-10-kpis-for-measuring-contact-center-efficiency
pressure-on-margins-for-auto-loans-indirect-auto-loans-declining
best-business-intelligence-technologies-for-credit-unions
establishing-a-thriving-data-analytics-practice-is-a-journey
educational-presentations-from-the-2017-axfi-conference
modelling-alternatives-for-cecl-a-deep-future-analytics-study
data-analytics-use-cases-for-credit-unions-infographic
data-analytics-opportunities-in-credit-union-business
loan-application-analytics-with-cufx
machine-learning-delivers-great-consumer-experiences
deep-insights-of-credit-union-members-data-with-machine-learning
web-analytics-reporting-tips-for-credit-unions
big-data-strategy-roadmap-our-data-journey
webinar-framework-for-member-focused-decision-making
too-many-regulations-hurt-credit-union-members
digital-marketing-automation-solutions
online-banking-boom
transformation-transactions-to-relationships
top-dispute-management-technologies
2020-retail-trends
future-of-artificial-intelligence
2020-culytics-summit-attendee-dashboard
repositioning-the-role-of-marketing
marketing-automation-a-step-towards-marketing-transformation
strategic-agility
using-data-to-navigate-through-the-new-normal
digital-transformation-bcu
highest-and-lowest-new-loan-balances-per-branch-as-of-jun-2020
-new-members-ratio-as-of-june-2020
cus-with-highest-and-lowest-loan-grants-per-member-june-2020
self-service-data-preparation-technologies
highest-and-lowest-marketing-expense-per-member-june-2020
the-amazon-lending-experience
api-lead-approach
4-step-iterative-process-building-a-relevant-analytics-practice
data-journey-building-strong-analytical-practices
post-election-the-cu-outlook
most-and-least-delinquent-credit-unions-sept-2020
leveraging-ach-data-to-produce-real-outcomes
member-engagement-scores-benefits
member-engagement-key-to-serve-the-best
story-of-james-an-intelligence-transformation
executive-kpis-the-pulse-of-the-organization
untangling-member-journey
onboarding-strategy-to-deliver-success
the-importance-of-digital-technologies
top-interactive-financial-calculators
using-artificial-intelligence-to-improve-your-productivity
organizational-transformation-to-drive-growth
multi-year-journey-through-data-transformation
top-50-cus-with-the-highest-and-lowest-member-per-branch
digital-transformation-lessons-through-the-eyes-of-a-ceo
organizational-readiness-for-digital-transformation
ruthless-prioritization-to-do-more-to-learn-more-and-to-earn-more
performance-measures-for-digital-services
analytical-maturity-journey-towards-growth
less-is-more-the-necessity-of-focus-for-strategic-success
solving-the-crm-mrm-puzzle
insights-driven-messaging-member-and-product-onboarding
performance-measures-for-marketing
data-insights-that-drive-member-product-innovation
solving-the-crm-mrm-puzzle
the-agility-flywheel-a-strategy-that-never-goes-out-of-the-way
artificial-intelligence-as-a-playing-field-for-credit-unions
performance-measures-for-call-centers
top-automl-technologies
performance-measures-for-lending
building-business-case-for-data-analytics
driving-innovation-and-change
data-analyze-decide-and-create
digital-readiness-important-steps-to-achieve
digital-readiness-important-steps-to-achieve
enabling-credit-unions-with-ai
culytics-virtual-summit-2022-a-resounding-success
culytics-virtual-summit-2022-day-1
digital-banking-roundtable
digital-marketing-roundtable
transformative-lessons-from-a-chief-digital-officer
data-analytics-roundtable-mar-11
rewind-2022-culytics-day-key-highlights
data-analytics-team-roles
data-warehouse-development
data-analytics-team-size
is-your-data-analytics-program-not-delivering-results
active-deposit-management-for-profitable-growth
data-modeling
maximize-your-success-with-2023-CULytics-summit
biggest-opportunities-for-credit-unions
should-ceos-attend-the-culytics-summit
the-cost-of-a-wrong-decision
biggest-roadblocks-in-becoming-data-driven
a-journey-for-all-organizational-maturity-levels
maximize-your-data-analytics-checkup
navigating-the-data-analytics-landscape
improving-data-literacy
why-credit-union-leaders-should-invest-in-their-teams
why-credit-unions-should-not-invest-in-building-predictive-models
why-should-measure-the-success-of-data-analytics-program
cost-of-choosing-the-wrong-data-analytics-technology-stack
why-data-analytics-strategy-focus-on-supply-and-demand-side
kpis-to-measure-the-success-of-data-analytics-program
data-analytics-for-credit-union-branch-heads
data-organizing-principles
top-data-warehouse-storage-technologies
discover-the-hidden-truth-behind-watermelon-kpis
unveiling-the-hidden-dangers-of-cobra-effect-on-kpis
are-you-accurately-interpreting-your-kpi
unmasking-biases-a-guide-to-data-analysis-and-kpi-definition
uncover-the-power-of-proxy-kpis
unraveling-the-hidden-impact-of-sampling-bias-in-credit-unions
bi-department-structure
hidden-impact-of-confirmation-bias-in-credit-unions
getting-executive-attention-for-your-data-analytics-program
uncovering-biases-in-data-preprocessing
navigating-missing-data-in-credit-unions
navigating-sampling-bias-in-cu
unleash-the-power-of-real-time-data-use-cases
how-confirmation-bias-impacts-cus
breaking-down-selection-bias-in-credit-unions
unmasking-reporting-bias
elevate-your-cu-with-data-analytics-expertise
understanding-and-tackling-volunteer-bias-in-credit-unions
time-period-bias-in-credit-union
overcoming-biases-in-credit-unions
embracing-the-future-fast-future-fundamentals-program-equips-cred
unlock-growth-and-efficiency-credit-unions-guide-to-generative-ai
how-better-data-and-behavioral-biometrics-can-help-credit-unions-
harnessing-the-power-of-data-in-credit-unions
leveraging-third-party-data-a-strategic-guide-for-credit-unions
unlocking-member-insights-how-cus-can-leverage-third-party-data
enhancing-customer-experience-through-third-party-data
third-party-data-integration-techniques-and-technologies
the-future-of-lending-third-party-data-role-in-credit-decisioning
how-third-party-information-shapes-cu-strategies
using-data-to-improve-access-to-credit-for-low-income-members
designing-financial-products-for-low-income-members-using-data
measuring-and-enhancing-the-impact-of-support-programs
data-governance-why-selling-internally-is-important
selling-data-governance-in-your-credit-union
building-a-business-case-and-engaging-stakeholders
creating-a-data-governance-roadmap-and-executing-it
measuring-and-demonstrating-the-impact-of-data-governance
sustaining-momentum-keeping-data-governance-a-priority
overcoming-challenges-in-transaction-data-analysis-credit-unions
empowering-members-through-transaction-data
how-credit-unions-leverage-transaction-data-best-practices
unlocking-financial-independence-the-power-of-transaction-data
the-power-of-transaction-data-enrichment
avoid-financial-reputation-and-member-trust-issues
introduction-to-model-risk-management
week-1-mrm-a-practitioner-s-approach
week-2-guide-to-identifying-and-maintaining-models
survey-insights-navigating-mrm-in-credit-unions
week-3-application-of-mrm-insights-to-sound-model-development-eff
unlocking-the-secrets-to-attracting-gen-y-and-z
creating-a-seamless-member-experience-for-gen-y-and-gen-z
data-analytics-maturity-assessment-report
marketing-to-gen-y-and-z-strategies-that-work-for-credit-unions
the-imperative-of-engaging-millennials-and-gen-z
cu-build-lasting-relationships-with-gen-z-financial-literacy
how-social-responsibility-drives-gen-z-membership
loyalty-programs-that-work-keeping-gen-y-and-z-members-engaged
insights-on-engaging-millennials-and-gen-z-at-credit-union
ai-driven-member-experience
streamlining-operations-with-ai
innovation-and-member-inclusion-in-ai-credit-risk-models
ai-risk-management-enhancing-fraud-detection-and-cybersecurity
how-ai-is-transforming-data-analytics-for-credit-union
overcoming-ai-adoption-challenges-in-credit-unions
the-state-of-ai-in-credit-unions-survey-insights
creating-a-culture-of-innovation
building-the-foundation
closing-the-talent-gap
Comments
I would echo David's comments regarding the efficiency ratio. It really is more of a financial metric than a productivity measure. There are two shortcomings of the ratio. First, it includes interest rates and rates are not productivity. If margins are widening, efficiency improves, but productivity may actually be declining, so you get a false positive. A false negative can occur if rates are compressing too. I would also consider excluding PLL from the ratio, to reduce volatility and get a better read. The second shortcoming is if you have a line of business that consumes no net worth, but throws off a decent profit margin, it can also make efficiency worse. For example, if you have a large investment or insurance operation that runs at a 15% profit margin, it's really an 85% efficiency ratio. It will create a drag on efficiency as the line of business grows, but because it consumes no capital, an unlimited amount of volume at 15% profit margin would be a great thing to have. This same example would create a false negative reading on Expense to Assets. Expense to assets counts all expense incurred in the generation of non-interest income but ignores the revenue. A slightly better measure would be net operating expense to assets. Bottom line: There are a number of ways to look at “efficiency” and “productivity” and digging into each provides the most insight.
Hi Mike,
Thanks for your comments. Few things that I will like to point out.
1. Efficiency ratio is just one the factors to consider. It is by no means an end-all, be-all financial measure.
2. The efficiency ratio as mentioned in the blog does not include interest rates. It does not include interest expense. It is the ratio of Non-Interest Expense/Net Income. So, if the margins are widening because of lower interest expense then there is no impact on efficiency ratio.
3. In your example, if there a slight twist. The large investment that runs at 85% efficiency and insurance operation that runs at 80% efficiency. Where should credit union focus its efforts? I would say, it depends. Since efficiency ratio is just one of factors to consider when making a decision. It depends on the size of the opportunity, competition, barriers to entry, and so on. However, efficiency ration is one of the factors to consider when making a decision.
What are the key financial measures that credit unions should use to keep tab on their financial health? What are the top KPIs for looking into efficiency and productivity from your perspective?
Thanks.
Good comments by all. I think we are in clear agreement that a "single" measure of efficiency or productivity is probably like sasquatch ... rumored to exist, but never proven. Also, as Jon noted, the reason for your analysis drives what you use.
Regarding your questions … assuming no capital requirement, I would pursue both the 85% and 80% efficiency opportunities with equal rigor. Why? The ROE is infinite … it can’t be computed because there is no capital required. In a capital constrained industry (banks, credit unions) a source of income that does not require capital opens up other areas that do require capital (or provides a dividend opportunity).
If I had only one measure of productivity, it would be the following: (non-interest expense less non-interest income) / (loan balance plus checking & savings account balance). Effectively, it is net cost of operations per strategic balance dollar. It is efficiency divided by effectiveness. The lowest cost is the best. I would exclude MMkt, CD and IRA from the denominator because they should require minimal resource to attract and manage. Those funding sources are also rate sensitive – and because of that, have lower strategic value. In the research I have done, the top third performers take less net interest spread from their members and at the same time, have a higher ROA, because of superior operating leverage. The bottom third take the most net interest spread and have the lowest ROA, because of poor operating leverage. Again, any single measure of productivity has its shortcomings, but this is my favorite when evaluating credit union performance. For banks, my favorite is efficiency ratio as computed by FDIC formula because of the profit focus there.
A couple of comments. Efficiency ratio can be a misleading measure of credit union operating efficiency, because credit unions return to their members "above the line" through higher rates on deposits, lower rates on loans, and lower fees. Depending on member giveback, this can depress reported income. Expense/Assets may be a better measure of relative efficiency. I would also challenge the assertion that 50% is the optimum efficiency ratio. The efficiency ratio is driven by several factors, including operating model. At Alliant, for example, our relatively low operating expense derives from a low-cost acquisition model (SEG and word of mouth) and high member reliance on remote and self-service channel access. This hasn't prevented us from investing in talent and technology, nor has it limited growth, and giveback is in the top 2% of credit unions.
Hi David,
Interesting perspective.
1, What are your thoughts on using Efficiency Ratio for comparing branches and/or products to get a better sense of how they are performing?
2. I have been thinking more of non-interest expense/Assets as a measure. This measure will favor credit unions where members have higher balances, since then credit unions have to serve less members for the same asset size, which reduces their non-interest expenses. Looking back, even Efficiency Ration tends to favor credit unions where members have higher balances.
Interestingly, with this StarOne is still the most efficient credit union.
3. Another metric might be interesting is non-interest expense/member, which shows how much a credit union is spending to service each member.
I think the problem with using efficiency ratio for evaluating branches is accurately determining revenue or asset attribution. What revenue/assets are directly attributable to a given branch? With products, the challenge is cost attribution.
Your observation about higher average balances is correct. Also, revenue (adjusted for giveback) tends to be a function of balances, while operating expense is a function of number of members, so it makes sense that CUs with higher average balances would be more efficient - i.e., generate more revenue relative to expense.
I agree that a better relative efficiency measure for CUs is non-interest expense/assets. And yes, it tends to be correlated with efficiency ratio for the reasons above.
I agree that non-interest expense/member is a useful metric for managing productivity.
Interesting comments. My original commentary was focused on branch dependent financial services firms. Different business models that are more dependent on digital or mobiile channels might yield different efficiency ratios. I agree that the efficiency ratio is not necessarily a productivity measure, and certainly not the only measure one should look at when examining their business, but it is a telling metric. Higher rates are an incremental expense and can either be seen as a "member benefit" or a "cost of doing business". If you were a bank instead of a credit union, and you offered higher rates, it would be seen as a cost of doing business. Shareholder dividends would be the equivalent of member giveback.
Average cost to serve a member is an interesting metric. The bottom line with any retail branch-dependent FI is that it has a heavy fixed infrastructure cost, so like any fixed-cost business needs big customer volumes to first meet those breakeven expense levels, but anything above those levels yields higher profitability, which can be returned to members. One other point. My short speech on this topic was limited to 12 minutes so I was unable to go into the nuances of all the other key metrics one should examine. Perhaps at a future event I can expound on these topics in greater detail.