How AI is shaping up consumer behaviour

Ian Smith writing for Financial Times:

AI, which sifts data and aims to learn like humans, is allowing insurers to produce highly individualised profiles of customer risk that evolve in real time. In parts of the market, it is being used to refine or replace the traditional model of an annual premium, creating contracts that are informed by factors including customer behaviour.

The theory with such policies is that customers end up paying a fairer price for their individual risk, and insurers are better able to predict losses. Some insurers say it also gives them more opportunity to influence behaviour and even prevent claims from happening.

The new overlords

There are many justifications to address the AI creep in healthcare- from lower insurance claims to “keeping people healthy”. Ethics, biases, constant monitoring – it will become mainstream. Should insurance dip into this? It’s an open question. Ideally, they would build profiles from the EMR, but that data is completely ring fenced. Meanwhile, the costs of healthcare are due to its excessive bureaucracy.

Here’s something from HBR article (2017)

Bureaucracy is destroying more and more value in many health care systems, but it doesn’t have to be that way. There are proven ways to fight back. They entail consciously designing your management systems to liberate the capabilities of all employees so that they can be used to address patients’ needs.

Here’s another:

Cost-efficiency is one of the necessary attributes for a high performance healthcare system. Over the years, the US health care has undergone progressive government inter-ference that has had the unintended consequence of leading to a storm of overutilization (Emanuel EJ, 2008) and increasing healthcare cost by steadily eroding the impact of free market forces in the relationship between providers of care and patient


The only way forward is to understand the root causes of “lack of efficiency” and not slap a dab of lipstick on a pig. AI is beginning to resemble this a lot.

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