The phrase Artificial Intelligence (AI) was likely first used by computer pioneer John McCarthy in 1956 at a Dartmouth College conference. And the concept of AI was even on the minds of classical philosophers as they delved into human thought processes.
Today we usually think of AI as computer systems mimicking human behaviors. But do they?
Many such computers are part of business efficiency and there is certainly a place for them. It is, however, important to understand that such systems, introduced in the name of efficiency and economy, often dehumanize the organization and the resulting service provided.
AI and API, but also y-o-u
People are unique, they respond in different ways and they are diverse. Financial advisors and other professionals must have the insight to understand that people – their client-investors and others – have strengths, struggles, biases and indeed breaking points that differ from person to person and situation to situation.
And even the smartest, most experienced advisors and clients only have so much insight, as our perceptive powers often cannot “see” or be aware of innate behaviors. Those go-to behaviors we all have and of which we may not even be aware…that surface naturally, often in times of stress or decision making.
So, just as behaviorally smart advisors understand the limitations of AI, they also understand their own limits of insight. But how to bolster human insight to best serve clients?
Whether intervention comes in the form of understanding emotional reactions to market movement, knowing when a simple call can head off a foolish decision about to be made or something else, advisors need to have significant amounts of insight into their clients in order to offer effective, consistent professional service.
But wouldn’t it be interesting to have both? A machine approach that not only gathered data and offered a range of financial insight, but also revealed human performance, emotions, bias and reactions and prompted the advisor when a client’s behavior (especially decision making) needs addressing?
A personality API (application program interface – think of a “plug in” for existing tech systems, then think of it providing personality insights) can give your data a human element, measuring behavioral insights covering virtually every human habit.
Roberta Smith on line one…
Picture this: You get a phone call from Roberta Smith, who wants to sell a significant stock. This is a big change and you don’t want her to act hastily. You need more information – and insight – regarding what’s driving this decision.
As you access her data on your system, compliments of that handy-dandy personality API, you see that she has a bias toward loss aversion. Not only that, but the behavioral data you have on your API reveals a range of different dimensions of Roberta’s natural style for making life and financial decisions, including her risk-taking behavior.
With the assist from your personality API in hand, you not only quickly access information about Roberta’s biases, but also her goals, spending patterns, risk stance and much more. Such a behavioral management tool gives you insights Roberta may not even have about herself.
Remember, your API is helping delve into innate client behavior, “farmed” when someone like Roberta takes a quick discovery at the very beginning of your initial work together. It may go without saying but is always worth repeating: AI is built on data, and part of the data populating a personality API would include Roberta’s input from her discovery tool.
Armed with client-specific human behavioral insights especially focused on finances and financial decision making, the advisor can safely continue the conversation with Roberta, knowing what’s driving today’s call. You can confidently – insights in hand – and in a tailored manner – because your insights also tell you how best to communicate with Roberta – steer her away from making decisions that will adversely impact her portfolio and life goals.
And this is no secret information, surreptitiously used. After all, you’re not manipulating Roberta, but creating a win-win. Back when a client like Roberta completed the discovery, you would have had a robust discussion around the added advantage you (and she) has by adding “behavior tech” to your other tech and tools.
Human and, not human or
There is no need to dehumanize relationships. AI has a significant place in the financial advisory business, but it must be partnered with behavioral data gathering and linked with API for instant access.
After all, AI and APIs are not replacing you. Rather, they are helping you take clients like Roberta to next-level, best-in-class advisory services.