MLO vs. AI

July 27, 2024: In the world of Artificial Intelligence (AI), the “frame problem” presents a significant challenge, as it pertains to determining all the relevant aspects of a scenario that must be considered in making a decision. This challenge involves recognizing and understanding all the essential details and their interactions within the given “frame” that will impact the outcome. The frame problem focuses on the importance of specific limits and constraints when analyzing a scenario to avoid overlooking relevant information needed to ensure the best decision.

In a typical mortgage scenario, the frame problem arises when a MLO needs to determine which of their client’s information is most relevant and significant. There are several factors such as income, employment status, credit score, DTI ratio, liquidity, desired loan amount, interest rates, loan terms, and other financial details, i.e. compensating factors. For example, the client may have a high income but also a high level of debt, or a low credit score and a large amount of liquid assets which could impact their ability to qualify for certain mortgages. The MLO must weigh these different factors and determine which ones are crucial for assessing the client’s eligibility for various mortgage options.

Additionally, the MLO must also consider external factors such as market conditions, interest rate fluctuations, and regulatory changes that can impact the mortgage market. The frame problem in this context involves the challenge of filtering out irrelevant information and focusing on the most critical factors that will help make informed decisions and provide their client the best mortgage solution.

Someday AI might be able to do all of this, but as of now it cannot. AI cannot empathize with the client’s situation. Empathy is a complex human trait that involves the ability to understand and share the feelings of others. While AI can be programmed to simulate empathy by recognizing patterns and making predictions based on data. AI lacks, however, emotional intelligence and intuition and cannot truly empathize with a person’s unique financial situation in the same way a human MLO can and do everyday.