Insurance Technology Innovation

But what if insurance worked more like Netflix? Netflix tracks your viewing behavior and adapts recommendations instantly. If insurance products adapting the same way, premiums adjusting dynamically to fitness levels, coverage expanding with life stages, benefits rebalancing as goals evolve. McKinsey estimates AI-led personalization could lift insurer revenues by 10–15%, while lowering claims costs through early risk detection. And The technology already exists. Wearables generate 250+ daily data points per user around heart rate, sleep, activity. PwC reports 63% of consumers are willing to share health data if it results in cheaper or more personalized premiums. And Personlaized premiums is not a distant reality. It can be achieved by: 𝟏. 𝐈𝐧𝐭𝐞𝐫𝐨𝐩𝐞𝐫𝐚𝐛𝐥𝐞 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 that allow secure ingestion of health and behavioral data at scale. 𝟐. 𝐑𝐞𝐠𝐮𝐥𝐚𝐭𝐨𝐫𝐲 𝐬𝐚𝐧𝐝𝐛𝐨𝐱𝐞𝐬 that encourage innovation while protecting privacy. 𝟑. 𝐀𝐈 𝐞𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐟𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤𝐬 to ensure transparent pricing and avoid hidden bias. 𝟒. 𝐄𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦 𝐩𝐚𝐫𝐭𝐧𝐞𝐫𝐬𝐡𝐢𝐩𝐬 with health-tech, fintech, and wellness players to broaden value delivery. Insurance is likely evolve from a once-in-a-decade purchase to a living product. #DigitalIndia #Fintech #AI #technology #Fintech #AI #technology

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

It was interesting to hear recent critiques about Apple’s announcement earlier this year on integrating machine learning and generative artificial intelligence (GenAI) into their products – with many asking, ‘What took so long?’ The timing of the news and the reaction tells me that even for the most revolutionary technology companies, GenAI is moving faster than most of us can reason. The rise of GenAI is the latest signal of how technology will continue to play an outsized role in our lives and in the lives of future generations. What does that mean for insurance? “AI models can simulate future scenarios, enhance the accuracy of risk estimation and drive better pricing. They can also identify false claims more effectively,” explains this article from @KPMG. As a heavily-regulated industry responsible for protecting consumer data, we tend to be thorough when evaluating new technologies. We also recognize the pressing need to modernize and move faster. While AI isn’t new in insurance, we see leveraging machine learning and GenAI technologies as a necessity. By embracing a broader range of AI, we can aim to simplify processes, improve accuracy, and provide our customers with better value, all while maintaining high quality, personal service. Our goal is to ensure that everyone, regardless of their background or circumstances, can have access to the best possible coverage. How would you like to see machine learning and generative AI applied to your own shopping experience, daily living or to increase performance at work? Share your thoughts below! #AI #Insurance #Innovation #FutureOfInsurance #CustomerExperience

A $1.1 Trillion Opportunity 🚀 The insurance industry stands on the brink of a major transformation, driven by the immense potential of AI technologies. Industry experts estimate that AI could add up to $1.1 trillion annually in value to the sector. This monumental shift promises to reshape how insurers operate, leveraging data-driven insights to drive efficiencies and innovation across various processes. AI technologies are set to revolutionize the insurance landscape in several key areas: Enhanced Risk Modeling and Predictions: By analyzing larger and more diverse datasets, AI can refine risk assessments and predictions. This means insurers can make more accurate decisions, set better premiums, and mitigate potential risks more effectively. Automated Customer Support: AI-powered solutions can streamline customer interactions, handling everything from routine inquiries to complex support issues. This not only improves response times but also boosts overall customer satisfaction. Revolutionized Claims Management: AI has the potential to transform the entire claims process—from prevention and notification to settlements and fraud detection. By automating these processes, insurers can reduce manual effort, enhance accuracy, and detect fraudulent activities more effectively. However, as we embrace these technological advancements, it's crucial to address the associated risks: Data Protection and Confidentiality: With the increased use of AI comes the responsibility to safeguard sensitive information. Ensuring robust data protection and maintaining confidentiality are paramount. Cybersecurity Threats: The threat of cyber-attacks is ever-present. Implementing strong security measures to protect against breaches and cyber threats is essential. Ethical Concerns and Liability Exposures: Navigating the ethical implications of AI and understanding liability issues will be key to responsibly integrating these technologies into business practices. As we look to emply the true AI, balancing innovation with careful consideration of these risks will be crucial. Embracing AI can lead to unprecedented opportunities, but it’s essential to remain vigilant and proactive in managing the associated challenges. Let's embrace! 💡📊🔒

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

On average, the insurance quoting and binding process in commercial insurance can involve up to 20 back-and-forth exchanges and can take anywhere from 7 to 30 days to complete, even for routine policies. It’s a headache—so many steps, so much waiting. But at its heart, the delays are just a bunch of friction points stacking up, making it harder than it needs to be to get coverage. Let’s break it down to a simple formula: Insurance = R * D * T R = Risk evaluation - The effort needed to analyze risks or complexities in a process.         D = Documentation needs - The data and documents required, including accessibility and sharing.                                                                          T = Time invested across process steps - The time spent moving through each step, especially in handoffs. Here’s how we can optimize each of these to reduce friction: ➡️ To streamline R (Risk evaluation): ▪Use data-driven underwriting to analyze and identify risks faster ▪Automate parts of risk assessment to speed up processing ▪Apply AI to get a more accurate read on common risk factors for faster decision-making ➡️ To streamline D (Documentation needs): ▪ Digitize intake and make data easy to share between stakeholders ▪ Prepopulate routine questions with standardized data feeds to cut down on back-and-forth ▪ Set up documentation workflows that notify the right person at the right time ➡️ To streamline T (Time spent on process steps): ▪ Automate handoffs to eliminate the lag from broker to wholesaler to underwriter ▪Build shared platforms for wholesalers and underwriters to manage data in real-time ▪Use AI tools to review documents and flag issues instantly, so delays don’t build up Yes, it’s a simplified formula. But by tackling each of these elements, we can cut down the days or weeks it takes to secure a quote and bring commercial insurance closer to the 24-hour speed clients expect in other industries. What innovations have you seen—or would you like to see—that tackle these points of friction? #Insurtech #AI #FutureofInsurance

Believe it or not, one conversation is still tickling the back of my brain from November at Connected Claims USA... We're facing a critical inflection point in insurance: a mass exodus of expertise just as our workforce becomes more distributed than ever. Those invaluable "coffee machine moments" where junior adjusters learned from veterans? The overheard conversations that taught us unwritten rules of claims handling? They're vanishing in our hybrid world. But here's what excites me: innovative carriers aren't choosing between remote work and knowledge transfer – they're reimagining both. I'm seeing: - AI-powered mentorship platforms matching veterans with newcomers across time zones - Virtual reality simulations recreating complex claims scenarios - Digital "listening posts" where institutional knowledge is captured and shared - Hybrid collaboration spaces designed specifically for knowledge transfer The most successful organizations understand that technology alone isn't the answer. It's about creating intentional moments for connection, whether virtual or physical. From my conversations with industry leaders, the winners this year won't be those who simply throw technology at the problem. Success will come to organizations that thoughtfully design environments that preserve our industry's collaborative essence while embracing modern workforce demands. What innovative approaches is your organization using to bridge the knowledge-sharing gap in this evolving landscape? Share your wins (or challenges) below! #InsuranceInnovation #KnowledgeTransfer #InsurTech

🚀 AI in Insurance: Beyond Automation to Transformation 🚀 In a recent edition of The Lisa Zone, Denise Garth, Chief Strategy Officer at Majesco, emphasized that AI and GenAI are revolutionizing the insurance industry by enhancing productivity, decision-making, and operational efficiency. However, to fully capitalize on AI's potential, it must transcend basic automation to become a driver of revenue growth, a workforce enabler, and a tool for cost reduction. 💡 Key Insights: 🔑 Strategic Data Foundation: Leverage intelligent core systems, data lakes, and advanced analytics to democratize insights and enable AI-driven decision-making at scale. 🔑 Holistic AI Strategy: Move from fragmented solutions to an integrated AI ecosystem for consistency and efficiency across the organization. 🔑 Culture of Innovation: Encourage continuous learning and adaptation to stay ahead in a rapidly evolving market. 🚗 The Path Forward: ➡️ Invest in Robust Data Infrastructure: Build intelligent core systems and data lakes to support AI-driven strategies. ➡️Embrace Holistic AI Strategy: Transition from fragmented solutions to an integrated AI ecosystem for consistency and efficiency. ➡️Foster a Culture of Innovation: Encourage continuous learning and adaptation to stay ahead in a rapidly evolving market. 🔗 💬 To dive deeper into how AI serves as the foundation for operational intelligence, revisit our previous discussion: https://lnkd.in/emE63bim #AI #GenAI #InsuranceInnovation #DigitalTransformation #OperationalIntelligence

📢 Small business owners, insurers, and vendors—take note. Next Insurance is making bold moves with 𝐭𝐰𝐨 𝐦𝐚𝐣𝐨𝐫 𝐚𝐧𝐧𝐨𝐮𝐧𝐜𝐞𝐦𝐞𝐧𝐭𝐬: -𝐌𝐮𝐥𝐭𝐢-𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧 𝐖𝐨𝐫𝐤𝐞𝐫𝐬’ 𝐂𝐨𝐦𝐩𝐞𝐧𝐬𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐯𝐞𝐫𝐚𝐠𝐞 – A game-changer for restaurant chains, retail stores, and other multi-site businesses. NEXT is cutting the red tape with a fully digital, single-policy solution for all locations within a state. No more juggling multiple policies—that's awesome. -𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐑𝐢𝐬𝐤 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐰𝐢𝐭𝐡 ZestyAI – NEXT is doubling down on innovation by integrating Z-PROPERTY™ and Z-FIRE™, providing real-time, property-specific risk insights that take underwriting to the next level. I've not experienced ZestyAI's products or solutions for myself, but they promise with AI-driven analytics, they’re setting a new benchmark for precision in risk assessment. 🔥 Why You Should Care -𝐅𝐨𝐫 𝐒𝐦𝐚𝐥𝐥 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬𝐞𝐬 – Faster coverage, easier management, and better risk assessment. -𝐅𝐨𝐫 𝐓𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐈𝐧𝐬𝐮𝐫𝐞𝐫𝐬 & 𝐓𝐏𝐀𝐬 – Another wake-up call. Legacy systems and manual processes won’t cut it anymore. -𝐅𝐨𝐫 𝐕𝐞𝐧𝐝𝐨𝐫𝐬 – A golden opportunity to build digital solutions that integrate with this new wave of automation. 📊 The insurance industry is at an inflection point. NEXT’s moves signal a future where 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲, 𝐀𝐈, 𝐚𝐧𝐝 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐭𝐡𝐞 𝐬𝐭𝐚𝐧𝐝𝐚𝐫𝐝. Traditional carriers and TPAs need to evolve or risk being left behind. 💬 What do you think? Are traditional insurers ready for this level of disruption? Drop your thoughts in the comments! #InsuranceInnovation #WorkersComp #Insurtech #Workerscompensation #SmallBusinessInsurance #RiskManagement #FutureofInsurance #PropertyandCasualty #InsuranceIndustry