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InsurTech Ohio Spotlight with Scott Ham

Scott Ham is the CEO of Pinpoint Predictive, providing P&C insurers the earliest and most accurate loss predictions and risk scores to fast-track profitable growth. Scott was interviewed by Andrew Daniels, Co-Founder and President at CrashBay and Founder and Managing Director at InsurTech Ohio.

Scott, define behavioral predictors and share some tangible examples.

“When you're thinking of the term ‘behavioral predictors’, what we're talking about are the activities of individuals. Examples include purchases, activities, engagements, subscriptions, etc., but you're really looking at what equates to the day-to-day engagements of individuals with the world. That information is collected in a compliant manner, either opt-in or opt-out, and from large providers.

Consider this: As you walk down the aisles of Dick's Sporting Goods, a digital trail forms behind you, tracking not only the frequency of your visits but the products you've purchased, along with the frequency of those purchases. All of a sudden, you can start to see that you're looking at the exact behaviors of individuals.

This is the most basic example of what a behavioral predictor looks like. On the flipside, information such as social media, zip codes and protected class information like race or ethnicity, natural language items and individual credit scores would not be considered a behavioral predictor because they aren’t true indications of the individual and what they're doing. This could lead to fairness issues.”

How should carriers be approaching these predictors in order to develop strategies around distribution and underwriting?

“The benefit of using these behavioral predictors is that they're not used right now in core insurance areas. Carriers are relying on traditional methods such as using credit scores to build their predictive models. The way behavioral predictors are utilized by Pinpoint is similar to how Amazon and Google uses them. We leverage not one but thousands of data predictors on each individual. It's a much broader view of the individual, giving the models a well-rounded range of vision and allowing carriers to predict outcomes faster. 

In terms of the carriers themselves, there is the age-old dilemma: build, buy or license. To determine what’s the best approach, carriers have to analyze their core competencies as well as their resource allocation. In this circumstance, it would take years for a carrier to curate which behavioral predictors carry predictive power and how to source them. And that’s just the beginning. They would then have to collect first-party proprietary behavioral economics data, identify a deep learning platform and find an identity resolution solution, to name a few.

Rather than spending millions of dollars trying to collect this information on their own and the extended amount of time required, carriers need to jump ahead of the curve with somebody that has already dedicated years to this endeavor and made substantial investments in the process. 

My recommendation would be to partner with vendors who have experience utilizing platforms that aren't currently being used and work with them to address their pain points. You can flip a switch and deploy immediately as opposed to dealing with internal conflicting priorities. 


As credit continues to come under the microscope, carriers need to explore other avenues to get intelligence on their current customers or future prospects. I would suggest that carriers address this by reading the tea leaves with where you're headed, and in this case, I wouldn't look at a build or buy. I would look at partnering."

Can you identify one way a carrier is using a suite of behavioral predictors to improve a workflow that’s normal within the insurance industry?

“Carriers can easily use these behavioral predictions in their agency operations. Prior to sending the leads to their agents, carriers can analyze the claims frequency, severity and the actual cost of those individuals. By understanding the least and most profitable leads, carriers can create different paths and strategies for them. For instance, they could implement a lead-scoring system and direct the highest-scoring leads, aligned with their risk appetite, to the agents. This targeted approach empowers agents to achieve higher conversion or bind rates, as they're engaging with individuals selected by the carrier. 

Carriers can also implement these predictions for incentives and bonuses. Typically, bonuses are paid out by carriers on claims, and bonuses look better if the claims go down. Carriers can not only increase their profit but also build a better relationship with the agents by using behavioral predictions. 

Additionally, carriers employ risk-selection strategies when providing quotes directly to customers. For example, when a customer visits their site and inputs their name and address, a carrier can swiftly access individual loss predictions, enabling them to tailor the customer's experience accordingly. Think of it as supercharged-risk stratification, where certain individuals may seamlessly pass through underwriting, while others may require additional scrutiny or may not align with the carrier's risk appetite. Leveraging these predictions, carriers can categorize experiences into tiers based on risk, effectively optimizing the customer journey.”

How has the industry embraced this technology up to this point?

“The excitement is there, and the carriers want to explore it. The regulatory environment in insurance is also catching up with ethical AI and determining what factors should and should not be used are critical for decision-making.

With additional capital available from leveraging behavioral predictions, carriers can now invest in better customer experiences and stay in markets they would've abandoned because the rates weren't keeping up with the costs. That’s the reason why carriers are getting excited about the fact there's new intelligence available that can not only help them from a profitability standpoint but also help grow their book of business in a compliant manner.”

What does the future have in store, and how should carriers capitalize moving forward?

“I'm an insurance guy, so I'm looking at legacy and making sure we're there to protect peoples’ dreams during unforeseen circumstances. Without looking at this new intelligence, I have some concerns because we have recently seen carriers exit from states and premiums reaching even greater extreme highs due to social inflation and climate events. 

By gathering and securing this new intelligence, carriers are going to be able to provide coverage for more people because they'll be smarter about how they look at each individual. When you expand it to other product lines, it opens up a world of opportunity for carriers to shore up their books and enable them to be there for consumers when needed. 

Without this new intelligence, while I don't see an industry that will go away, it's just not going to be as strong, and consumers won't have the choice that they would have if everybody was there playing in their backyard. It also becomes more affordable because we're smarter about who we're looking at. This is the way to secure a legacy for insurance and to do what we've done, which is to protect people and contribute to the global economy. I love the business, and I think this is a way to make us even better.”


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