Fluctuations in the U.S. economy can significantly affect the performance of the accounts receivable management (ARM) industry. Although numerous economic indicators interact with the industry’s many segments, certain variables are far more impactful than others. Kaulkin Ginsberg’s statistical analysis of nearly three dozen economic variables suggests that the four with the greatest level of statistical significance to the ARM industry are consumer bankruptcy filings, retail sales, official unemployment rate and the home price index. These variables provide insight into a consumer’s spending habits, wage growth, household wealth, and likelihood of default, which are all critical considerations to the long-term success of the ARM industry.
Consumer Bankruptcy Filings
Consumer bankruptcy filings are the aggregate number of consumers filing for bankruptcy during a given year. This variable is positively correlated with the ARM industry’s growth. Although it’s counterintuitive that an increase in bankruptcy filings could be a positive for growth as they remove a potential debtor from the market, not all bankruptcy filings result in a complete discharge of debt obligations, and may still lead to an increase in business for repossession services. Additionally, those who do file for bankruptcy make up only a small portion of the population as a whole and serve as a strong indicator for U.S. economic trends.
This economic measure comprises the total value of retail sales during a given year, and it’s also positively correlated with the growth of the ARM industry. Perhaps more intuitive than consumer bankruptcy filings, retail sales is a strong indicator of consumer spending activities; as this variable grows, we are likely to see a greater potential for delinquencies as U.S. consumers, members of the largest credit economy in the world, use credit to make their purchases.
Official Unemployment Rate (U3)
The official U.S. unemployment rate is the percentage of the civilian population that is not working, but still seeking employment, and is considered as participating in the labor force. This variable is positively correlated with the growth of the ARM industry; as the U.S. unemployment rate increases, the operating environment appears more ideal for ARM services. This makes sense because shocks to the system, like an increase in unemployment, lead to an increase in the percentage of the population that is likely to fall delinquent on a bill or payment. Furthermore, it captures effects such as the loss of health insurance that could lead to an increase in delinquent medical bills.
However, this does not suggest that an indefinite rise in unemployment will support indefinite growth within the ARM industry. Too much unemployment leads to a stagnant economy, as we saw during the Great Recession when consumer spending fell significantly. Therefore, as the unemployment rate increases, within reason, there is a greater chance for a positive operating environment for the ARM industry.
Home Price Index
The home price index (HPI) is the average value of all homes in the U.S. relative to the average value of all homes in the U.S. as of Q1 1991. This variable is positively correlated with the growth of the ARM industry. Considering the average person’s home is their largest and most valuable asset, it makes sense that as the housing market grows in value, home owners are more open to taking on debt, while a drop in value will minimize a home owner’s willingness or ability to take on debt. Therefore, as the HPI increases in value, it creates a positive operating environment for the ARM industry.
The KG Index
Taking our analysis of the aforementioned economic variables and their interaction with the ARM industry a step further, Kaulkin Ginsberg’s market research team developed The KG Index with the goal of examining the effects of these economic variables on the ARM industry relative to a base period of Q4 2007 (i.e., this period provides a score of 100). We chose Q4 2007 as our base year for analysis since the Great Recession officially started during this quarter and the period is more or less the central point of our dataset, allowing for a better comparative analysis.
Concerning our selected economic variables, we weighted these variables on the basis of their explanatory power following our statistical analysis of the industry on an annualized basis. Additionally, we compared the correlation of our index with the annual revenue trend of the ARM industry over the same period to ensure this method aligns with revenue performance, which we view as a strong indicator for accuracy. Given a correlation score of 0.98, we believe this index conveys the overarching trends of the ARM industry in response to a changing economic environment. Next, we converted our annualized analysis of these economic variables to a quarterly analysis in order to assess how the ARM industry trends throughout the year. The results of this analysis were quite interesting and, in some cases, a little surprising as you can see below.
Overall, the ARM industry experienced significant growth from Q1 1998 to Q4 2005 where it peaked at 113.74 before falling through Q2 2006 to a trough of 95.25. In the years following, the index shows a rather slow (and somewhat volatile) growth pattern through Q2 2017 where, nearly 12 years later, it has finally exceeded the Q4 2005 and now sits at 114.49. While finally setting a new performance peak is exciting for the industry, economic data is always subject to revisions so we remain cautiously optimistic about Q2 2017 results.
On the one hand, slower growth for a mature industry makes a lot of sense. Just as a company generates exponential growth during its early years, only to be followed by a slowdown in growth after maturing, so too do industries. On the other hand, these data suggest that the ARM industry, nearly 12 years later, still hasn’t recovered from the economic slowdown of 2006 that led to the Great Recession, which is somewhat concerning. One could also take the above data as an indication that not enough is being done to support an industry that is essential to the proper functioning of the U.S. credit economy.
Additionally, we can see a seasonal performance trend within the data starting in Q1 2010 and continuing to present that wasn’t present in the data from Q1 1998 to Q4 2009. More specifically, we see that Q2 of each year represents the peak performance period (i.e., Q2 2017 just set a new 20-year performance peak) and Q4 represents the trough performance period. Any analysis and interpretation of this trend, given the limited amount of time (or data) associated with it, should be taken with caution. That said, a definite trend appears within the data and may provide a strong indication of the typical ARM firm’s peak performance periods, which, if it continues, could be compared against specific events throughout the year (i.e., tax season) to determine if these events are strong growth drivers for the industry.
Going forward, Kaulkin Ginsberg will release its index on a quarterly basis following the release of the required economic variables. Typically, this will occur about two months after the end of each quarter. Additionally, future releases of this index will place greater emphasis on the trends taking place over the last few quarters, and less emphasis on describing the index.
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