Can a life insurance company look at the same data every other rival has and come up with different insights? That's the goal of Haven Life, which is using artificial intelligence to offer decisions on applications in real time.
Life insurance runs on actuarial data, which makes a guesstimate how long a person will live. This life and death data is needed so life insurers can manage risks.
To date, obtaining life insurance has been a bit of a pain because it requires a medical exam, some blood and a bevy of medical history questions. Haven Life, a unit of MassMutual, aims to streamline the process, said Mark Sayre, head of policy design at Haven Life.
"The data we use is established for this purpose. Life insurance has a unique challenge since mortality has a slow process and it's uncommon. It takes many years of experience to build our models," explained Sayre.
More on digital transformation and implementing AI and machine learning and finding the money for it
Indeed, Haven Life needs someone to live or die to verify models. In other words, Haven Life has to use MassMutual's data over the years and then use artificial intelligence and machine learning to find things in the information that humans can't see. As a result, Haven Life can offer the InstantTerm process, an innovation that means the startup can offer can underwrite a policy on behalf of MassMutual without a medical exam in minutes.
Simply put, Haven Life is using older data to spin something new. I'd argue that applying artificial intelligence and machine learning to older proprietary data is going to be a key use case in corporations. Haven Life had to take data from old applications and text to turn into structured information.
"Our models can now dig into interactions and various elements of the data," said Sayre. One example is blood and urine tests used in life insurance quotes. Say a normal value on a blood test is 45. Under the previous model, 46 would be deemed high and 43 low.
"Our model better understands how close 45 is to 46 so it's not immediately good to bad," explained Sayre. As a result of the new model and machine learning, Haven Life found that low figures are just as concerning as high ones. "The model brought something new to the medical team. If there are multiple low figures that can be bad. We have to look at the interplay of variables on lab tests," said Sayre.
Blood pressure, albumin and globulin are variables that could be worrisome if low.
In many respects, algorithmic underwriting is about creating pathways to make decisions by using various characteristics such as height, weight, cholesterol and other values.
One key note is that Haven Life's model is a work in progress and will take decades of refinement. MassMutual brings the history and mortality experience while Haven Life brings a tech focus and ability to move quickly.
What's next? Sayre said Haven Life is looking at variables such as credit data and prescription histories. The catch is that Haven Life won't know the validity of the data for life insurance for years. "We won't know because there may be no deaths for years. All of these models require an outcome. We need some death and some living people," said Sayre.
Other key points: