In insurance, insights and signal are king — and the more you have, the better. Used in every aspect of the insurance business — from customer segmentation and personalization to fraud detection to risk assessment and underwriting — this advanced level of signal helps insurers unlock profitability and reduce losses.
Since the early days of insurance, insurers have collected basic historical, behavioral and environmental data to help them make informed decisions. For example, in risk assessment and underwriting, insurers use surveys or questionnaires, a consumer's credit and claims history, and demographics to price risk and set premiums. But over the past few decades, an increasingly competitive insurance market has made it clear that more accurate risk assessment and underwriting is needed in order to truly remain profitable.
And that's where non-traditional signal and AI come into play. With these enhanced capabilities, insurers can leverage advanced predictive modeling with person-level insights to build more reliable risk profiles and set premiums in a way that better covers expected losses.
Enhancing consumer profiles, predicting risk with person-level data
While the current method of pricing risk has been effective, relying on surveys and historical data has limits. They paint only a fraction of the overall picture and are unable to take into account indicators in an insured's future choices and behaviors. Technology, however, has advanced, opening new channels of insights into future choices that could help insurers better predict risk.
Person-level intelligence and AI bring to the mix an added layer of insights about a customer, recognizing the uniqueness of individuals. Person-level insights show why a policyholder might make certain choices such as canceling a policy, and how those choices could be influenced by different factors, such as finances. When this layer of customer intelligence is added to the old method of foundational data, insurers can gain a level of insight needed for better loss-ratio performance and greater profitability.
Diving in
Unfortunately, in the case of AI initiatives somewhere between 60% and 80% fail to be deployed, according to various news sources. Insurers should start by defining the desired business outcomes and metrics and then aligning them with proof-of-concept processes, rather than developing the technology and hoping it can help somewhere down the line.
Once the business problem and desired outcomes are defined, insurers should look to a trusted partner to help shepherd them through the initiative. Aside from deep experience in AI models, the ideal partner should also understand the insurance regulatory environment. And, as bias tends to creep into predictive data, any partner must also be able to demonstrate clear policies and procedures for mitigating and managing bias.
Pinpoint Predictive: Your trusted partner
Pinpoint Predictive's risk selection platform uses AI and non-traditional variables to identify and quantify the profitability of insurers' current and prospective business earlier, faster and more accurately in order to significantly improve loss ratios.
Pinpoint is leveraged by P&C insurers throughout the insurance value chain in areas such as customer acquisition, claims, underwriting and renewal.
Pinpoint's Loss Predictions predict claims frequency, claims severity and loss cost for homeowners and personal auto. For example, when used in comparative raters, Pinpoint leverages a prospect's name and address to match to an existing footprint, which then provides a score or prediction that the insurer can use to decide whether to even return a quote. Once the prospect becomes a policyholder, insurers can leverage Pinpoint to prioritize which policies to renew and which need additional underwriting before a renewal decision is made.
Additionally, during customer acquisition, Pinpoint's Risk Scores are used to determine specific potential risks, such as likelihood of litigation or non-pay cancellation. This empowers insurers with a prospective view of the future profitability of potential customers.
With profitability on the line in a tight market, now is the time for insurers to lean into deep-learning models that can deliver the kind of personal, behavioral risk assessments that make a difference in predicting risk. The right partner with the right product can help insurers take advantage of today's enhanced capabilities in order to secure successful business outcomes tomorrow.
To learn more about Pinpoint Predictive, please visit https://pinpoint.ai/
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