Predicting the Future

In case there is any doubt that people possess a powerful desire to see into the future, just look at the assortment of characters from whom folks have been willing to hear such advice in the past. Out near the highway, on the outskirts of most any American town, there stands a sign that announces the services of someone who purports to tell people what lies ahead of them in life. We wouldn’t take away any sense of comfort that people might discover there, but it is possible that the “Fortune Teller” sign is about the only thing that gets illuminated once inside.

The recent past, the study of economics shows a shift in emphasis from ideas, theories, or schools of thought about how economies operate to a focus on measurements, experiments, and observations known as economic modeling. The energy and acuity – the sheer boldness of quantifying macroeconomic factors to this extent – is admirable. Yet, we leave it to others to pronounce how well modeling has served us in averting economic crises, both large and small.

No Safe Distance

The leveling effect of aggregating data usually can be counted on to cancel glitches and offer a valid overall picture. The “40,000-foot” view of businesses and industries might be expected to weed out anomalies and offer us a somewhat truer picture. Such a view is used to speak in favor of economic modeling. On the other hand, what seems to emerge, when modeling is applied to whole economies, is a generality that can fail to predict effects that matter a great deal to any particular industry.

Because there is no safe distance from which to view the future of the economy in which we operate, we find that observing certain bellwether industries, rather than modeling the economy as a whole, offers us useful perspectives for seeing the path ahead.

The Other Household Demands

The commanding officer of a warship told me once that examining the horizon beside and behind the course of the ship was his personal focus when he was on the bridge. “Everybody else is looking dead ahead. No one is going to miss what turns up there. Besides, by the time an opponent is in front of you, it is too late.” Similarly, mortgage lending industry professionals who keep their eyes glued to housing and real estate are missing the chance to give themselves more time to prepare and respond.

Selecting your preferred industries to monitor for predicting occurrences in home finance that may be looming can be a matter of asking what other demands, what imperative expenses, compete for the income of a household. Energy, transportation, and healthcare might seem to be obvious choices. At that level, however, the answers might be too obvious or too volatile to serve well as predictors.

A Sharper Lens

I have observed that trends in the cost of medical insurance can be more predictive than healthcare as a whole. Investments in the transport of fuel – shipping and pipelines – can provide steadier forecasts than oil prices. Hospitality expenditures – dining and lodging – can say more than general measures of consumer confidence.

We are in the business of providing much-needed margins for loan origination and services, through mortgage automation that is based on substantial industry experience, as well as technology expertise. Personnel and process, I find, are unbreakably attached to innovations based on AI for valid, relevant, and useful solutions. We are always happy for the chance to serve, from this informed point of view.