The 360IS Blog: AI, Insurance, and Innovation

Usage-based insurance (UBI) has rapidly moved from innovation to expectation in personal auto. Policyholders now assume their premiums will reflect how, when, and how safely they drive. For insurers, this shift unlocks more accurate risk modeling and competitive pricing. But behind the scenes, a less visible challenge is emerging—one that many carriers are underestimating: The data processing gap between telematics and claims. The Hidden Complexity of UBI Data UBI programs ge

The insurance industry is approaching a significant workforce challenge. Recent reports indicate the U.S. insurance sector could lose around 400,000 workers by 2026 , driven largely by retirements and ongoing workforce attrition. For an industry that relies heavily on experienced professionals to review claims, analyze documentation, and make complex decisions, that type of workforce reduction presents real operational risk. But the future of insurance isn’t about replacing p

Why “Who decided this and why?” Is Now a Baseline Requirement in Automated Insurance Claims Artificial intelligence is rapidly transforming automated insurance claims . From intelligent document ingestion to medical bill review and demand evaluation, carriers are adopting AI to move faster, reduce costs, and scale without adding headcount. But amid the excitement around automation, one uncomfortable question keeps surfacing: “Who decided this — and why?” For many insurers dep

Unstructured records lead to inconsistent outcomes. Structured, source-backed reviews change that. Medical review is supposed to create clarity. Too often, it does the opposite. Claims teams are handed hundreds—sometimes thousands—of pages of medical records: PDFs, faxes, handwritten notes, imaging reports, lab results, and prior reviews. The information exists, but it isn’t organized for decision-making. As a result, even experienced clinicians and adjusters arrive at differ

Insurance organizations have made meaningful progress digitizing documents and automating basic workflows. But for many claims, legal, and medical review teams, the reality is this: unstructured data still slows everything down . Medical records, police reports, demand letters, bills, and correspondence don’t fit neatly into databases. Simply extracting text is no longer enough. The next step in the unstructured data automation journey is intelligent analytics —the ability to