I wrote in an earlier post about the Q1 2019 rally in eNote adoption. Wanting to investigate the adoption speed a little more, I dug deeper into ways to forecast how quickly we could see the eNote adoption take hold. This required me to draw from my mechanical engineering days and research various models and differential equations. However, I will do my best to keep the technical components brief.
I discovered that when forecasting a new product the common method to use is referred to as the Bass Diffusion Model.
The model is driven by three variables:
p: The Coefficient of Innovation: What is the influence from external factors – marketing
q: The Coefficient of Imitation: What is the influence from internal factors – word of mouth
t: The time period
Looking at previous transformative products (i.e. TV, cell phone, microwave) and the corresponding coefficients, I tried a number of variations. You can find various research papers online that provide coefficients for various products. They also provide an average for each coefficient based on historical adoption rates.
Using the average values for the coefficients based on historical adoption rates, the eNote model forecasts a 98% adoption rate for originations in 15 years – arriving in year 2034.
Source: Iron Mountain
Although there are a number of assumptions with this forecast that can be debated, it really drives home the idea that in the near future we will not have physical promissory notes circulating in the mortgage industry. Managing only electronic promissory notes will make operations easier for any entity in the lending industry.
While the near future could be 10 years or 20 years, it is never too early to begin planning for this change. As you prepare, consider the following:
- What is the impact to the industry when we have no more paper documents?
- What type of resources are required to perform data to doc validations with electronic assets?
- How will the role of an originator, servicer, or custodian change if there are no physical documents?
My prediction is artificial intelligence and machine learning will play a big role in automating the processes related to electronic documents. Optical character recognition will have limited value because the image content will already have the text available for use and the data will already be mapped and in a consumable format. Only exceptions will require monitoring by a human eye, which will continue to decrease as the system learns. Real estate and resource needs will be minimal for the future document operations shop. Are you ready for the 100% digital document world?