As organizations handle an increasing amount of data, using that data quickly and efficiently isn’t always easy. That’s why many are turning to AI to help with tasks such as triaging claims and providing adjustors with the right insights at the right moment to support more informed decisions.

Ann Latimer, senior vice president, head of claims operations, at Signal Mutual Indemnity Association, describes how she leveraged Gradient AI to transform their claims triage, and what it takes to get internal buy-in for an AI system.

In this episode, you’ll hear:

·         Why claims triage was a natural introduction point for the AI solution;

·         What challenges Signal Mutual Indemnity has undertaken in adoption; and

·         How Lattimer’s team measures success on the platform.

Accurate reconstruction cost estimates (RCEs) are key to building strong property insurance policies. They support dependable insurance-to-value, which inform policy limits and reliable quoting, benefiting both insurers and policyholders.

In this episode of “Filling the Gap,” Trish Hopkinson, head of 360 Value for Verisk’s Underwriting Solutions, discusses how current and accurate information is critical in avoiding underinsurance gaps, which leave all parties vulnerable in the case of a total loss. You’ll learn:

• The impact a volatile marketplace, including inflation and labor strains, has had on reconstruction trends;
• Why current claims data is critical when recalculating reconstruction cost estimates;
• The main challenges that arise when estimating personal property and contents; and,
• Key elements important to reliable replacement costs.

For insurers, collecting as much information as possible is the name of the game, as it informs any number of insurance processes and ensures accurate risk assessment. With AI and machine learning, insurers now have powerful analytic tools to turn even more sources of underwriting insights into actionable intelligence. This not only enriches the underwriting process it also introduces efficiencies across the business.

In this episode of the “Filling the Gap” podcast series, Othman Loudghiri, director of Small Commercial and Casualty Underwriting at Verisk, talks about what AI and machine learning can help small commercial underwriters achieve. You’ll learn:

• The types of data AI and ML can capture and analyze, and why this is important in small commercial underwriting;
• The specific operational and efficiency benefits insurers can expect with AI and ML;
• How these new technologies complement the human touch, empowering underwriters to focus on more client-facing, strategic endeavors; and
• Why there’s an urgent shift from AI “exploration” to “adoption” among insurers and MGAs.

Each year, carriers spend countless hours applying changes to their rating content. It’s time-intensive work requiring precious resources to load only a fraction of these changes into their own rating engine. By digitizing this content, carriers can accelerate the adoption of rating changes and bring their products to market more quickly.

In this episode of “Filling the Gap,” Mark Sheehan, vice-president of Underwriting Solutions at Verisk Analytics, reviews the benefits of RaaS and the impacts it makes on rating. You’ll learn:

• The evolution of rating, how Rating-as-a-Service works;
• How digitization of rating content is benefiting carriers;
• How Rating-as-a-Service is increasing employee engagement and productivity, while also enriching the carrier’s insurance product;
• What early adopters are saying about Rating-as-a-Service.

The commercial insurance market is no stranger to advanced technology, using it to impact workflows to meet insureds’ demands for faster turnaround times and greater accuracy. Now, AI and ML are being applied to commercial insurance underwriting, helping insurers underwrite property risks more accurately and efficiently.

In this Insurtech Center podcast, Elizabeth Casas, Verisk’s head of commercial lines, underwriting, goes deeper into how AI and ML are impacting commercial lines underwriting. You’ll learn:

• The evolution of the use of AI and ML to collect data;
• How digital technologies are helping insurers to upgrade and enhance their underwriting capabilities by mining “actionable” data; and
• How digital technologies complement, rather than replace, human intervention to enable greater efficiency and accuracy.