Essential components of insurer technology

The industry with 6x the TSR vs. the average 2–3× is… insurance. Insurers that lead with AI aren’t just keeping pace, they’re creating 6× the shareholder returns of laggards. The reason? Making bold choices about where to build, buy, or partner ... and rewiring the business, not just dabbling in pilots. Often cast as risk-averse, insurance shows the opposite here: when insurers center strategy with AI, the rewards are exponential. Leaders have created six times the shareholder returns of laggards over the past five years. My colleague Tanguy Catlin has spent years guiding insurance and financial-services clients through transformation. He and our insurance colleagues highlight that, to win, insurers can double down on four of the six rewired components: (1) Business-led roadmap: tie AI directly to value creation, not tech curiosity. (2) Operating model at scale: embed AI into how the business runs, not just in pilots. (3) Flexible AI stack: technology designed for speed, modularity, and distributed innovation. (4) Adoption & change management: because even the best AI fails without human adoption. Here’s what outcomes look like for insurers who get serious: domain-level transformation has already yielded a 10-20% lift in new agent success and sales conversion, 10-15% growth in premiums, 20-40% lower cost to onboard customers, and 3-5% improvement in claims accuracy. These aren’t incremental tweaks, they move core levers that impact the top and bottom line. Full article linked below and authored by Nick Milinkovich, Sid Kamath, Tanguy Catlin, and Violet Chung, with Pranav Jain and Ramzi Elias. https://lnkd.in/df2GXpuq

The auto insurer of the future will apply extensively AI to a constant flow of #telematics data‼️ Do you agree with our assessment of the impact? 🔴 game changer 🟢 impacted 🔵 marginal impact 🔴Product management “The design and maintenance of a telematics product that provides more frequent interaction with policyholders is completely new compared to the traditional insurance model, which uses static rating features. The days of the “one-policy-fits-all” approach to auto insurance are over.” 🔴 Marketing “As these programs become more innovative, shifting how we market the value proposition to customers will be vital. Marketing activities need to focus on customer engagement through improved communication and transparency.” 🔴Policy acquisition and servicing “Telematics data is changing the entire customer journey from issuing a quote to the policy contract, how the policy is serviced, including billing, and finally, the impact on renewals.” 🔴 Underwriting and risk management “Risk analysis, inspection, monitoring and loss control—typically core and addressed at the policy level in middle and large commercial risks—can be performed at scale on the personal auto book, applying algorithms to the telematics data” 🔴 Sales and distribution “telematics offers new ways to acquire customers, such as using the driving score at point of sale.”“Pre-existing data allows companies to offer the most accurate rating/discount upfront, replacing the need to capture driving data during the introductory period. The insight collected about policyholders and their risks has the potential to unlock further opportunities for upselling and cross-selling.” 🔴 Claims management “Claims activity is ripe for a deep redesign fueled by using telematics-based insights to detect crashes and proactively reach out to policyholders, assessing the crash dynamic and the overall anti-fraud process.” 🔴 Support functions. “From an IT, organizational and data management perspective, the amount of data received with telematics is new for most insurance companies, and the skills required will be broader than the traditional insurance skillset. Investing in the right infrastructure, data foundation and people is vital because nothing happens in telematics without data. The better a carrier is at managing this dataset throughout the customer value chain, the greater their chances of success—as this fuels the pricing models that determine if a discount is warranted, powers the customer experiences, impacts future strategies and innovations, and ultimately unlocks the larger benefits.” #iotinsobs #insurtech

The future of finance in insurance lies at the intersection of data, automation, and scalability—are you equipped for this transformation? Insurance CFOs are now at the helm of a tech-driven transformation, embracing the full power of GenAI, cloud, data, and low-code to drive strategic finance. Here’s a look at the four technology game-changers redefining the finance function: 1.⁠ ⁠GenAI & Automation – GenAI is streamlining specialized finance functions like actuarial reserving and financial hedging. By standardizing processes and eliminating redundancy, it’s improving the efficiency of core finance operations by up to 20%.    2.⁠ ⁠Data Explosion – CFOs are now architects of data lineage and governance, employing integrated data frameworks and centralized architectures (data lakes, service mesh) to unify data from internal and external sources, enabling precise decision-making and improved reporting accuracy.    3.⁠ ⁠Cloud Infrastructure – Cloud migration enables agile scalability, reducing IT complexity and ensuring finance operations can adapt in real-time to shifts in market conditions and regulatory demands, positioning finance teams for faster and more cost-effective innovation. 4.⁠ ⁠Low-Code/No-Code Solutions – Democratizing application development, these platforms allow finance teams to rapidly create customized tools for data analysis and reporting, reducing dependency on IT and increasing operational adaptability. CFOs ready to lead with these tools will create a lean, responsive finance function, capable of supporting strategic objectives and adapting to new market realities with agility. #CFO #FinanceTransformation #InsuranceTech #GenAI #CloudComputing #DataGovernance #AWS

Recent conversations with clients and analysts really illuminated the growth of insurance #data platforms - either inhouse, or within core, and core-adjacent, software providers, or via API (as we do at Fenris Digital). Adopting an AI-first approach is better when the underlying data is accurate, accessible, and injected in real time into workflows and ML algorithms. Sourcing applicable and permissible third party data bring immense lift to results, be it at quote, renewal, or while servicing the account. This purpose built approach to data and AI directly empowers carriers, brokers, and agencies to make better and more timely decisions. But it also promotes development of a data-driven culture that prepares organizations for long-term success. In all things AI, keep in mind the guiding principles of transparent, understandable, and fair, and set the course for better customer experiences. #insurtech #propertyandcasualty #earlyriskassessment #machinelearning