Will Automation Negatively Impact Member Income?

Throughout this fall’s planning cycle we’ve engaged in a number of conversations about the possible impact of automation and artificial intelligence on credit union operations. The working assumption is that there is a strategic advantage to automate certain tasks and functions in order to make better use of personnel for higher purposes.

Automation and AI, in other words, are fast becoming important operational initiatives for credit unions of all shapes and sizes.

But there is another area of interest when it comes to the impact of automation on credit unions – member income.

We share a number of articles and research papers with planning clients to prep for strategy dialogue, and we have a new one to add to the mix. It is a paper recently published by the Federal Reserve Bank of San Francisco. We’ll let the abstract speak to the paper’s focus…

The portion of national income that goes to workers, known as the labor share, has fallen substantially over the past 20 years. Even with strong employment growth in recent years, the labor share has remained at historically low levels. Automation has been an important driving factor. While it has increased labor productivity, the threat of automation has also weakened workers’ bargaining power in wage negotiations and led to stagnant wage growth. Analysis suggests that automation contributed substantially to the decline in the labor share.

What is the credit union strategy dialogue here? Member qualification for credit union loans in an era of stagnant member wages – especially if loan costs and terms continue to increase (take a look at this recent WSJ article for an interesting view on automobile prices and financing costs & terms from the consumer perspective – subscription required).

You’ll find the Fed’s paper here: https://www.frbsf.org/economic-research/publications/economic-letter/2019/september/are-workers-losing-to-robots/

Note that I’m not drawing conclusions of a bleak future. I’m simply suggesting that the topic of discussion should be of interest to credit union planners – with the question being, “How do we find success in serving members in the event labor shares continue to decline and/or wages stay stagnant?”

Seems like an important question to consider.

Glatt Consulting Planning

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Image by kalhh from Pixabay

Should We Be Concerned About Membership Growth?

The flexibility to add to fields of membership comes at an opportune time for credit unions – provided court opinions continue to fall in favor of the industry, and credit union’s change their perspective on marketing and business development investment.

Membership Growth Rate Slowing?

Glatt Consulting’s HealthScore includes membership growth as a component of the overall HealthScore calculation, and the industry has seen notable year-over-year membership growth score declines in each of the first two quarters of 2019. Q2 saw a score decline of 7.36% on the heels of a 3.2% decline in Q1. Prior to 2019, credit unions showed a decline only once in 18 quarters.

What is the cause?

We think there are two. First, slower growth in indirect auto loans (both total dollar volume and total indirect loans). Indirect is a channel that fuels membership growth for many credit unions, so the drop in indirect has a definite impact on membership growth.

Second, credit unions are coming up against limits to field of membership – in two different ways. First, credit unions do turn away those that are not qualified to join. Second, and relatedly, credit unions have come close to exhausting the “low hanging fruit” of membership growth – namely those that are already familiar with credit unions and/or that already belong to one or more. Attracting the “unfamiliar” is slow going.

The Challenge, and Competition Ahead

Credit unions, already experiencing slight declines in operating expense scores, may need to pump up spending even more to garner the attention of the next generation of credit union members – those that can belong as result of expanded memberships but that have no idea what a credit union is. These folks will be hard to reach using more traditional approaches – especially if indirect is a channel of concern (meaning credit unions continue to experience slower indirect channel growth).

Consider that SoFi, a non-credit union entity that nonetheless touts their service to “members,” outspends the average credit union to acquire/serve members by about $400/member. And they don’t spend in the same areas as credit unions.

To compete, credit unions will need to spend more, and spend better.

See: SoFi Is Paying Top Dollar To Acquire Its Prime Customers

Young People Don’t Own Homes

The frequent refrain today is that young people — Millennials, Gen Y, Gen Z, whatever you want to call them — don’t own homes or care to own homes. That may be true for some markets, particularly where the costs of purchasing make renting more economically sensible, but it certainly isn’t true across the board. How do we know? The Consumer Expenditures Survey, or CES.

What is this survey and what does it measure? To quote verbatim from the Bureau of Labor Statistics website, “the Consumer Expenditure Surveys program provides data on expenditures, income, and demographic characteristics of consumers in the United States. CE data are collected by the Census Bureau for BLS in two surveys, the Interview Survey for major and/or recurring items and the Diary Survey for more minor or frequently purchased items. The (CES) is the only Federal household survey to provide information on the complete range of consumers’ expenditures and incomes.”

And now to the critical question: what does the CES say about young adult homeownership?

To answer, let’s take a look at the latest survey results, focusing on the breakdown of homeownership by age ranges. We’ve charted the data below.

And what do we see. The homeownership segment for consumers under 25 is quite small indeed. Only 11% of the survey population are homeowners, and of that group only 4% have a mortgage (the market segment of interest to mortgage lenders). However, compare that to the 25-34 demographic. Homeownership jumps from 11% to 41%, with 34% making use of a mortgage. This represents a sizable shift and a viable, lucrative market.

So … what is your credit union to do to capture loans as renters move on to homeownership? For a number of credit unions the tendency is to wait until a properly seasoned member knocks on the door of the mortgage loan office and asks for a loan. That is an ill-advised strategy. The “wait and see” approach will not work. You can do better than that – and you need to start with outreach to the under 25 market. It is never too early to build awareness.

Perhaps the best way to develop, or at least catalog new strategy ideas is to look at the providers who seem to be doing well capturing this market. One example? SoFi (https://www.sofi.com). We encourage you to look at their marketing, and positioning for home loans. You’ll find their resources here for general mortgage information (https://www.sofi.com/home-loans) and here for consumer education and support (https://www.sofi.com/home-loan-help-center).

Also…watch their borrower story video below. It is very good. It focuses on showing that homeownership is attainable, and does not mean an end to social life. Good messages for young consumers contemplating (or fearing!) the transition from renting to owning.

SoFi Tells a Mortgage Story

And one more anecdote to share about approaching this market. We looked at one credit union’s efforts at attracting young homebuyers. What benefit were they offering to entice people to attend an in-person homebuyer seminar? A discount on future closing costs. We’ll cover the income side of the CES in greater detail in another post, but for now let’s just say that those younger borrowers could use cash today, not closing cost discounts tomorrow.

What is a better alternative? How about a prepaid gas card to cover the fuel costs for searching for a home? Something like this puts the credit union in the car with the young buyer as he/she/they look for the “home of their dreams.” Not a bad place to be.

So, apparently young people are buying homes after all. Feel free to ignore those experts that tell you young people will, now and forever, only rent.

Interested in downloading CES data and digging in? You’ll find it here: https://www.bls.gov/cex

Trends in Consumer Underwriting Standards

Red arrow pointing up

Did you know that the Federal Reserve conducts a quarterly survey of senior loan officers at about eighty large domestic banks and twenty-four U.S. branches and agencies of foreign banks? The survey, called the Senior Loan Officer Opinion Survey on Bank Lending Practices, is among the data considered by the Federal Open Market Committee (FOMC) in preparation for its policy discussions and decisions.

What good is that survey to you? Well, for credit union leaders the data, which can be downloaded via the Fed’s website, provides some indication of how credit underwriting standards and demand are changing at large institutions – standards than can impact many thousands of consumers and businesses across the country and influence overall industry policy. In your own strategic assessment of these trends you may be able to pick up on potentially harmful market changes, or emerging untapped opportunity.

What to Know About the Data

Here are a few things to know about the survey and survey data…

Question Types

The survey reports on three types of questions, each important to understanding underlying national lending trends. The first question pertains to demand, the second to underwriting standards, the third to willingness to make loans.

Net Percentage Responses

The survey reports data in terms of net percentage of respondents. For example, one of the reported results fields tracks the following:

Net percentage of domestic banks reporting stronger demand for auto loans

If the net percentage is a positive number, then a greater percentage of bank respondents are reporting that demand for auto loans has increased over the last survey period. Conversely, if the number is negative then there is a decrease in demand.

Using the Data

Knowing how loan demand and underwriting standards are moving in the marketplace is very helpful in terms of strategy planning. So what does the data look like and how can it be helpful to you? Consider the chart below. It tracks the net percentage of domestic banks tightening standards for credit card loans.

Let’s focus on the time period right before the Great Recession, which ran from December 2007 to June 2009. The prevailing trend at the beginning of 2007 was that the industry was not tightening standards, meaning the majority was not making it harder to get a credit card. This is evidenced by the chart dipping below 0% in Q2 and Q3.

By Q4, however, the line moved above 0% to 3.2%, and by Q4 2008 it hit 67% – an incredible mass movement to make it harder for consumers to get credit card loans. Banking institutions using the survey data during that time would have definitely seen that “something was up” as the tide changed and could, perhaps, have used the data as inspiration to take a harder look at their own marketplace risk. This certainly would have helped some credit unions as many were slow to tighten in the early days of the recession and as a result ended up with an abundance of risky loans – in some cases to the demise of the credit union.

Current Data Trends

So what does the latest survey tell us about key consumer product underwriting standards? In the chart below we highlight the net percentage of domestic banks tightening standards for auto loans, credit cards, consumer loans (excluding credit card and auto loans), and conforming mortgage loans. Interestingly, we see that tightening occurred for the majority of consumer loan types – with a healthy majority focused on tightening credit card standards. Conforming mortgages, on the other hand, saw a slight majority loosening standards.

So why are standards tightening for most consumer loan types but not for mortgages? It would help to have the demand side of the equation to compare to since sometimes standards are set in reaction to demand, such as tightening to temper aggressive demand growth. The chart below gives us the demand picture.

As is clear from the chart, aggressive demand is most definitely NOT the cause of tightening standards.

But what do we assume is happening then? Given that standards are tightening while demand is weakening it is likely that survey respondents are working to protect against future risk. There has been a lot of talk of late about fears of a slowing economy, inverted yield curves, recession. It makes sense given the rhetoric that survey respondents would want to be proactive in cleaning up portfolios by eliminating a risk tier or two.

Why are mortgages different? Why wouldn’t standards be tightening for mortgages too, perhaps even more so than credit cards? Likely two reasons. First, interest rate increases in 2018 slowed demand considerably. One way to try to stir up demand is to loosen standards slightly so that more borrowers are qualified. The other reason is that if institutions are working to reduce risk on consumer loan portfolios they’ll need some other place to put deposited funds, and mortgages are certainly a less risky option than unsecured consumer loans (keep in mind that we are not talking about subprime mortgage loans).

We encourage credit union lenders to keep an eye on the survey results, in addition to other factors, to maintain a well-rounded view of lending trends. For savvy credit unions, adding such information to the dataset allows for better informed lending policy decisions, and perhaps could lead to a unique market advantage. For example, you may be able to act counter to the trends, growing in certain loan categories even as others are pulling back. If you know your local market will behave differently than the market as a whole, then maybe you can work aggressively fill the competitive void that will exist as national lenders close the door on people in your local community.

The survey data is published quarterly and is available on the Federal Reserve’s website at https://www.federalreserve.gov/data/sloos.htm.

Note: The survey also tracks standards and demand for commercial loans.

The Next Branch? Maybe Not the Best Idea!

Lightbulb representing ideas
We recently saw a press release from a mid-sized credit union touting the launch of its latest new branch. You would think that a credit union highlighting yet another branch (they have a few) would be doing so after generating amazing results with the ones it already had. Well … not the case.
The chart below highlights the credit union’s HealthScore trends over the last few years. Keep in mind our HealthScore scale is 0-10 with 10 being high performing – and the industry average is 5.862.


And how about the table of results highlighting their component scores below? Low scores for earnings, operating expenses, and efficiency … and also for growth. High scores for some relationship metrics, but also an indication of concentration risk. This is probably not the best time to expand the branch network. Rather, this credit union should be working on cost reduction strategies along with strategies to drive deeper member relationships. All they did with this latest decision was add cost on top of cost. A rather risky proposition.

HealthScore Trend Table

Visit https://www.glattconsulting.com/healthscore/healthscore-trends to see additional details regarding score acronyms and trends.

Cycle_Date HS NW SE RA OE EF DL CO TX CS RS LA DM LM BM AG LG MG
03/31/2004 4.4706 7.5 7 3.5 2 6 3 1 9 6 3.5 4.5 4 4.5 6 8.5 0 0
06/30/2004 4.0882 7.5 7 3 2 6 2.5 1 9 6 4 5.5 4 4.5 6.5 0 1 0
09/30/2004 4.4412 7.5 7 4.5 2 6.5 2 1.5 8.5 5.5 4 5.5 4 4.5 6.5 1.5 4.5 0
12/31/2004 4.4412 8.5 7.5 5.5 1.5 7 2 1.5 8.5 2.5 4 6 4 5 7 0 5 0
03/31/2005 5.5588 8 7 8 1.5 8.5 2 1 9 7 4 5.5 4 4.5 6.5 9.5 0 8.5
06/30/2005 5.0294 8.5 7.5 8.5 1.5 8.5 2 1 8.5 5 4 6 4 4.5 6.5 4 0 5.5
09/30/2005 4.9706 9 8 8.5 1.5 8.5 2 1 9 6 4 6 4 4.5 6.5 2.5 0 3.5
12/31/2005 4.5588 9 8 8.5 1 8.5 2.5 1 9 2.5 4 6.5 4 5 5.5 0 2.5 0
03/31/2006 5.6765 9 7.5 5.5 1 6.5 3.5 1 9 4 4 6.5 4 5.5 5.5 10 10 4
06/30/2006 5.4706 9 7.5 6 1 7 3.5 1 9 1.5 4 7 4 5.5 5.5 6.5 10 5
09/30/2006 5.0882 9.5 8.5 6 0 7 4 1 9 1 3.5 7.5 3.5 6 5.5 1 9.5 4
12/31/2006 5.3529 9 8 6.5 1 7 3 1.5 9 3 3 7 4 5.5 5 6 7.5 5
03/31/2007 4.9706 9 8 5 1 6.5 3.5 1.5 9 4 3 6.5 4 5.5 5 4.5 0 8.5
06/30/2007 4.9412 9.5 8.5 2.5 7 6 3 1.5 9 4 3 7 4 5.5 4.5 0 2 7
09/30/2007 4.5294 9.5 8.5 5 1 6 2.5 1.5 9 3.5 3 7.5 3.5 5.5 5 0 2.5 3.5
12/31/2007 4.5 10 9 6 1 6.5 1.5 1 8.5 3 3 8 3.5 6 5 0 4.5 0
03/31/2008 5.1176 10 9 9 1 6.5 2 1.5 9 4.5 3 7.5 4 6 5 9 0 0
06/30/2008 4.8235 10 9 8 1 6.5 1.5 1.5 8.5 3.5 3 7.5 4 6 5 7 0 0
09/30/2008 4.6765 10 9.5 8 0 7 1 1.5 8.5 3 3 7.5 3.5 6 5 2.5 0 3.5
12/31/2008 4.5 10 10 7 1 7 1 1 8 3.5 3 7.5 4 6 5 2.5 0 0
03/31/2009 4.7353 9.5 9 5.5 1.5 8.5 0 1 7.5 4.5 2.5 6.5 4 6 4.5 10 0 0
06/30/2009 4.3824 9.5 9.5 0 0 8.5 0 0 7.5 6 2.5 6.5 4.5 6 4.5 9.5 0 0
09/30/2009 4.8235 10 9.5 9 1 9.5 0 0 7.5 5 2.5 6.5 4.5 6 4.5 6.5 0 0
12/31/2009 4.6471 9.5 9 6 1.5 9.5 0 0 7.5 5.5 2.5 6.5 4.5 6 4.5 6.5 0 0
03/31/2010 4.5294 9 9 2.5 1.5 8.5 0 0 7.5 4.5 2.5 6 4.5 5.5 4 8 0 4
06/30/2010 4.0294 8 8 0 1.5 9 0 0 7.5 2.5 2.5 5.5 5 5.5 4 8 0 1.5
09/30/2010 4.0294 8 8 0 1.5 9 0 0 8 2.5 2 5 5 5 4 6 0 4.5
12/31/2010 4 8 8 0 1.5 8 0 0 8 4.5 2 5 5 5 4 5.5 0 3.5
03/31/2011 3.6765 8 8 1 1.5 7 1 0 8.5 2.5 2 4.5 5 5 4 4.5 0 0
06/30/2011 3.5882 8 8 3 1.5 7 1.5 0 8.5 1.5 2.5 4 5 4.5 3.5 2.5 0 0
09/30/2011 3.7353 8 8 1.5 1.5 6.5 1.5 0 9 3.5 2.5 4 5.5 4.5 3.5 4 0 0
12/31/2011 3.9118 8 8 3 1.5 6.5 1.5 0 8.5 5 2 4 5.5 4.5 4 4.5 0 0
03/31/2012 4.8529 7.5 7.5 4.5 2 4 1.5 1.5 9 5 2 4 6 5 4 9.5 9.5 0
06/30/2012 4.5588 7.5 7.5 5 1.5 3.5 1.5 1.5 9 4.5 2 4 6 5 4 7 8 0
09/30/2012 4.4118 8 8 6 2 4 2 1.5 9 4 2 4 6 5 4 5.5 4 0
12/31/2012 4.1765 8 8 6 1.5 4 1.5 1 9 4 2 4 6 5.5 4.5 3 3 0
03/31/2013 3.8235 8 7.5 0 1.5 0 1.5 1.5 8.5 6 2 3.5 7 5.5 4 8.5 0 0
06/30/2013 3.4412 8 7 1.5 1 1 1.5 1.5 9 3.5 2.5 3.5 6.5 5.5 4 2.5 0 0
09/30/2013 3.2941 8 7.5 1 1 1 1.5 1.5 8.5 1 2.5 4 6.5 5.5 4.5 1 1 0
12/31/2013 3.3529 8.5 7 1 1 1.5 1 1.5 8.5 0 2.5 4.5 6.5 6 4.5 0 3 0
03/31/2014 4.0882 8 7 0 1.5 2 2.5 1 9 1.5 2.5 4.5 6.5 6 4.5 8 0 5
06/30/2014 4.1471 8 7.5 0 1.5 2 2.5 1 9 1.5 2.5 4.5 6.5 6 4.5 5 2 6.5
09/30/2014 3.7941 8 7.5 0 1.5 3 2.5 1.5 9 1.5 2.5 4.5 6.5 6 4.5 1 2.5 2.5
12/31/2014 3.9118 8.5 7.5 0 1.5 3 3 1.5 9 1 2.5 5.5 6 6.5 4.5 0 6.5 0
03/31/2015 4.0882 8 7.5 0 1.5 3.5 3 1 9 2.5 2.5 5 6.5 6.5 4.5 8.5 0 0
06/30/2015 4.0588 8 7.5 0 1.5 4.5 4 1 9 2.5 2.5 5.5 6.5 6.5 4.5 2 3.5 0
09/30/2015 4.0882 8.5 8 0 1.5 4 3 1.5 9 3 2.5 6 6.5 6.5 4.5 1 4 0
12/31/2015 4.0294 8.5 7.5 0 1.5 4 3 1.5 9 3 2.5 6 6.5 7 4.5 1 3 0
03/31/2016 4.2941 8 7.5 1.5 2 3.5 2.5 2 9 4 2.5 5.5 7 7 4.5 6.5 0 0
06/30/2016 4.1765 8 8 1.5 2 3.5 2.5 2 9 4 2.5 5.5 7 7 4.5 4 0 0
09/30/2016 4.2059 8 8 1.5 2 3 4 2 9 4 2.5 5.5 7.5 7 5 2.5 0 0
12/31/2016 4.0294 8.5 7.5 1 2 3 4 2 9 3.5 2.5 5.5 7.5 7.5 5 0 0 0
03/31/2017 4.2647 8.5 7.5 0 2 2.5 4 2 9 3.5 2.5 5.5 8 7.5 5 3.5 1.5 0
06/30/2017 4.2353 8.5 7.5 1 2 2.5 3.5 2 9 4 2.5 5.5 8 7.5 5 1.5 2 0
09/30/2017 4.2941 8.5 8 1 2 2.5 4.5 2 9.5 4 2.5 6 7.5 7.5 5 0 2.5 0
12/31/2017 4.2059 8.5 7.5 1 1.5 3 4 2 9 4 2.5 6 8 7.5 5 0 2 0
03/31/2018 4.9118 8.5 7.5 0 1.5 4 4 2 9 3.5 2.5 6 7.5 7.5 4.5 0 5.5 10
06/30/2018 4.4412 8.5 7.5 1.5 1.5 4 5 2 9 4 3 6 8 8 5 0 2.5 0
09/30/2018 4.3235 9 8 1.5 1.5 4 5 2 9 4 3 6 7.5 8 5 0 0 0
12/31/2018 4.2647 9 8 1 1.5 3.5 4.5 2 9 4 3 6 8 8 5 0 0 0