NeuralMetrics CEO Prakash Vasant talks about how AI is enabling positive disruption and elevating confidence in risk-quality data from public sources for commercial underwriters.
Disruption has led to significant changes in the insurance industry. Automation, artificial intelligence, and data/analytics are just a few of the technologies making processes faster and easier for insurers, agents, and ultimately the policyholder. NeuralMetrics CEO, Prakash Vasant, participated in Authority Magazine’s “Meet the Disruptors” interview series and shared how the company is adding transparency to commercial underwriting, why he thinks disruption is a positive outcome, and the best piece of advice he has ever received.
In the excerpt below, Prakash shares how NeuralMetrics is using generative AI to transform the commercial underwriting process.
What is disruptive about the work you’re doing?
NeuralMetrics is advancing positive disruption in the insurance industry by facilitating data-driven underwriting. With just a name and address, website, or corporate email ID, agents and insurance companies can get all the information they need about a business customer to evaluate the insurance risks and get them coverage. This means policyholders no longer must fill out lengthy forms. Agents can focus on the customer’s unique needs rather than entering data. And insurers are getting far more accurate data.
We’re also disrupting underwriting analytics by making risk data validation much more transparent. Not only are we helping insurers and agents classify and assess risks, but we show them the data sources we used, so they can validate classification and risk-assessment data for themselves. We are combining data analytics, AI, and machine learning with human decision making.
Here’s an example of the way this human-machine combination works. Consider an insurance agent working with a restaurant on a new insurance policy. The agent submits the business name and address. Our solution analyzes all public data to answer the key questions that the carrier needs to assess the risk. One of those questions asks about food delivery. Let’s assume our solution says, “no delivery.” But there’s a twist. The agent is familiar with the restaurant and has ordered delivery before. On other platforms, that’s where the “black box” limitation becomes evident. The agent wouldn’t know why the solution said, “No” to this question and that would be that. They could do manual research to figure it out, adding significant time to the sale. Or they might question the accuracy of all the information because of the answer to that one question.
With NeuralMetrics, the agent can click the question and see the data sources we used to answer it. In this case, assume the agent looks at the source and realizes that the restaurant only offers delivery through a third-party provider, like Grubhub, which is why the solution said “No.” Since third party deliveries don’t impact the insurance coverage, the agent can then move forward with the policy, with much more certainty about the accuracy of the application.
This level of transparency helps gives insurers the confidence to replace some manual decision making that doesn’t add value with real time information and data, streamlining the underwriting process.
To read Prakash’s full interview with Authority Magazine, click here.