What financial modelers can learn from MoviePass when implementing CECL

If you have followed the news about MoviePass and its recent financial downfall, you may have read about declining stock prices and angry customers, and made a mental note about what not to do in business. However, there is one critical but less obvious lesson to learn from the MoviePass pandemonium – and it is one that just might keep your financial institution from going down the wrong CECL road.

When looking at MoviePass’ failure to meet its customer commitment, one has to consider that its business leaders based its subscription model and pricing plan on statistical estimates, as any good business would do. However, in this case, it seems clear that MoviePass did not accurately forecast subscriber use, which, in turn, caused the company to underestimate projected costs and losses. In simple terms, MoviePass may have based its business model and subscription product around bad statistical sampling and averages from that sample when deciding its cost/pricing.

If MoviePass assumed that the average subscriber went to three movies per month, then an estimate based on averages would simply multiply the total number of overall moviegoers in a given month by the average number of movies attended by customers in a given month. It sounds straightforward but unfortunately, not every moviegoer is the same. Millennial Mike, for instance, might attend seven movies per month while Baby Boomer Bob only goes to one or two. MoviePass’ forecast likely did not take into account user bias, whereby more millennials would purchase the subscription and take full advantage.

The lesson learned is that when it comes to forecasting, idiosyncrasies matter. In the context of CECL, a financial institution may use an “average” approach to estimate losses based on historical performance, and perhaps it makes sense if its portfolio is rather homogenous. However, it is important to keep in mind that once an institution chooses its method for calculating losses, it will need to stick with that model for years to come. It is important for institutions to consider whether the average approach will be the right approach in five years. Will your portfolio behavior change? Will the local economy change? Will an “average” of historical losses enable your institution to set aside the right amount of capital? Or, will your institution end up over or understating losses?

Next time you head to the movies, give a second thought to your CECL modeling methodology. That is, if MoviePass will let you in to the movie in the first place.

To assess whether your model will be sufficient to address nuanced portfolios, please reach out to Atul Nepal anepal@mviewfs.com.