http://noah.makes.news/Noah News Insurance Risk Tech RSS feedhttp://www.rssboard.org/rss-specificationenSun, 03 May 2026 10:06:08 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/duck-creek-unveils-agentic-ai-platform-to-transform-underwriting-and-claims-operations<p>Duck Creek has launched an insurance-focused agentic AI platform designed to enable governed automation across the policy lifecycle, integrating AI into core systems for faster, more compliant underwriting and claims processing.</p><p>Duck Creek Technologies has unveiled an insurance-focused agentic AI platform that it says is designed to bring governed automation into underwriting and claims, as carriers race to turn artificial intelligence from a pilot-project tool into something that can operate inside core systems. The Boston-based software vendor also introduced two applications built on the platform, one for underwriting and one for first notice of loss, in a move that underscores how insurers are increasingly looking for AI that can do work rather than merely analyse it.</p> <p>According to Duck Creek, the platform is intended to let insurers deploy, coordinate and oversee AI agents across the policy lifecycle, with controls for traceability, compliance and human oversight built into the architecture. The company says the system sits inside its Intelligent Core insurance platform and can work in both embedded and headless modes, allowing carriers to add agentic capabilities without ripping out existing infrastructure. Duck Creek also describes the product as combining domain-specific insurance knowledge with neuro-symbolic reasoning, a model it says should improve context and governance.</p> <p>The new applications are aimed at some of the industry’s most operationally sensitive tasks. The Agentic Underwriting Workbench is pitched as a way to speed up submission intake, triage and enrichment, while the Agentic First Notice of Loss application is meant to help capture, validate and route claims more efficiently. Duck Creek said the FNOL product was developed with Google Cloud and uses Gemini models for functions such as coverage checks and early fraud detection at the point of intake.</p> <p>The launch reflects a wider shift in insurance technology away from isolated automation and towards coordinated decision-making across workflows. Boston Consulting Group has said AI could create substantial annual value for the US insurance market, helping explain the urgency around platforms that promise both productivity gains and stronger controls. Duck Creek has argued that the challenge for carriers is no longer simply adopting AI, but doing so in a way that preserves auditability, regulatory alignment and operational confidence.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://iireporter.com/duck-creek-launches-agentic-ai-platform-for-carriers/" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.duckcreek.com/product/agentic-ai-platform" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.prnewswire.com/news-releases/duck-creek-launches-insurance-native-agentic-ai-platform-and-unveils-new-applications-to-transform-underwriting-and-claims-302755119.html" rel="nofollow" target="_blank">[4]</a>} - Paragraph 2: ^{<a href="https://www.duckcreek.com/product/agentic-ai-platform" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.prnewswire.com/news-releases/duck-creek-launches-insurance-native-agentic-ai-platform-and-unveils-new-applications-to-transform-underwriting-and-claims-302755119.html" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.duckcreek.com/blog/formation-26-kickoff-intelligent-core-insurance/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 3: ^{<a href="https://www.duckcreek.com/product/agentic-applications/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.prnewswire.com/news-releases/duck-creek-launches-insurance-native-agentic-ai-platform-and-unveils-new-applications-to-transform-underwriting-and-claims-302755119.html" rel="nofollow" target="_blank">[4]</a>} - Paragraph 4: ^{<a href="https://iireporter.com/duck-creek-launches-agentic-ai-platform-for-carriers/" rel="nofollow" target="_blank">[1]</a>}, ^{<a href="https://fintech.global/2026/04/29/duck-creek-launches-agentic-ai-platform-to-transform-insurance-workflows/" rel="nofollow" target="_blank">[7]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62edd48754ffe1b586968Sat, 02 May 2026 17:09:23 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/marsh-risks-new-ai-powered-suite-transforms-risk-management-at-rims-riskworld-2026<p>Marsh Risk launches Risk Companion, an innovative digital platform harnessing AI to enable clients to handle complex exposures with increased speed and accuracy, marking a significant step in tech-driven risk solutions at RIMS RISKWORLD 2026.</p><p>Marsh Risk has introduced Risk Companion, a new digital suite that the broker says is designed to help clients handle increasingly complex exposures with greater speed and precision. The platform combines Marsh’s risk data, actuarial models and specialist expertise, in what the company describes as a further step in its use of artificial intelligence across client services.</p> <p>Michelle Sartain, president of Marsh Risk for the US and Canada, said organisations now need faster access to information that can help them make decisions under pressure as risks become more interconnected and volatile. The launch comes as large brokers and risk advisers push deeper into AI-enabled tools, reflecting demand for systems that can turn data into more immediate guidance rather than static reports.</p> <p>Marsh plans to showcase two components of the suite at RIMS RISKWORLD 2026 in Philadelphia, which runs from 3 to 6 May. Renewal Companion is intended to let clients test retentions, limits, deductibles and coverage options in real time, compare outcomes and generate board-ready recommendations. Captive Companion is aimed at clients using captives, offering financial metrics, automated reporting, document workflows and benchmarking tools.</p> <p>The launch also fits into a broader set of themes expected to dominate the conference, including cyber risk, supply chain disruption, geopolitical tension, AI-related threats and social inflation. RIMS says this year’s event will emphasise collaboration and practical decision-making, with Marsh among the exhibitors highlighting analytics-led approaches to risk management and resilience.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://www.insurancejournal.com/news/national/2026/04/28/867527.htm" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.marsh.com/en/about/media/marsh-risk-unveils-ai-powered-risk-companion.html" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.marsh.com/en/services/client-and-market-technologies/expertise/companion-solutions.html" rel="nofollow" target="_blank">[7]</a>} - Paragraph 2: ^{<a href="https://www.marsh.com/en/about/media/marsh-risk-unveils-ai-powered-risk-companion.html" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.marsh.com/en/insights/events/rims.html" rel="nofollow" target="_blank">[3]</a>} - Paragraph 3: ^{<a href="https://www.marsh.com/en/about/media/marsh-risk-unveils-ai-powered-risk-companion.html" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.marsh.com/en/insights/events/rims.html" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.rims.org/about-us/newsroom/news/riskworld-zeroes-in-on-risk-management-collaboration" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.rims.org/RISKWORLD" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.marsh.com/en/services/client-and-market-technologies/expertise/companion-solutions.html" rel="nofollow" target="_blank">[7]</a>} - Paragraph 4: ^{<a href="https://www.marsh.com/en/insights/events/rims.html" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.rims.org/about-us/newsroom/news/riskworld-zeroes-in-on-risk-management-collaboration" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.rims.org/RISKWORLD" rel="nofollow" target="_blank">[5]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62edf48754ffe1b586972Sat, 02 May 2026 17:09:23 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/optalitix-s-api-powered-platform-accelerates-london-market-underwriting-growth-via-h-w-kaufman-partnership<p>Optalitix teams up with H.W. Kaufman Group to transform London Market commercial property pricing through API-driven automation, boosting scalability and speed in underwriting processes.</p><p>Optalitix has struck a partnership with H.W. Kaufman Group that is designed to bring London Market commercial property pricing into a more automated, API-led workflow at Burns &amp; Wilcox, the group’s wholesale broking and underwriting arm. The move is intended to help the business scale its London Market activity without relying on the slower, manual methods that have traditionally been used to price specialist risks.</p> <p>At the centre of the arrangement is the integration of Lloyd’s syndicate-backed capacity into Burns &amp; Wilcox’s existing underwriting environment. According to Optalitix, its software turns intricate pricing rules into cloud-based services that can be accessed through APIs, allowing underwriters to work within the same Salesforce platform already used for North American business. H.W. Kaufman Group said this should make it easier to combine London Market and North American capacity inside one quoting process.</p> <p>Rich Fusinski, group CIO and senior vice-president at H.W. Kaufman Group, said the firm needed a way to bring London Market capacity into its established workflow, and described Optalitix as a bridge between complex pricing logic and a more usable digital system. The company has framed the project as part of a wider investment in technology aimed at improving speed to market, underwriting accuracy and the ability to scale globally. Optalitix added that the change should lift quote volumes and shorten the time needed to generate terms.</p> <p>The programme is also being supported by actuarial consultancy Martin &amp; Company, which is helping convert contract logic into Excel-based rating models before those models are loaded into the Optalitix platform. Matt Heilmann, chief revenue officer at Martin &amp; Company, said the approach could allow Kaufman to deploy usable rating models in weeks, with later changes completed in hours or days. That claim reflects a broader push by insurers to replace document-heavy underwriting with systems that are easier to update, audit and connect to other parts of the business.</p> <p>Burns &amp; Wilcox UK has separately described Optalitix as a way to better connect CRM, underwriting and risk-recording processes while keeping pricing models in a secure, accessible setting. Optalitix says its platform was chosen after an evaluation that looked at API capability, validation tools, scalability in complex insurance environments and experience in the Lloyd’s market, underlining how London Market digitisation is increasingly being treated as a strategic rather than merely operational issue.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://www.reinsurancene.ws/optalitix-partners-with-h-w-kaufman-to-support-london-market-scaling-through-burns-wilcox/" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.reinsurancene.ws/optalitix-partners-with-h-w-kaufman-to-support-london-market-scaling-through-burns-wilcox/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://fintech.global/2026/04/28/optalitix-partners-kaufman-to-bring-lloyds-pricing-into-api-driven-workflows/" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.burnsandwilcox.uk/about-us/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 2: ^{<a href="https://www.reinsurancene.ws/optalitix-partners-with-h-w-kaufman-to-support-london-market-scaling-through-burns-wilcox/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://fintech.global/2026/04/28/optalitix-partners-kaufman-to-bring-lloyds-pricing-into-api-driven-workflows/" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.optalitix.com/london-market" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.hwkaufman.com/about-us/" rel="nofollow" target="_blank">[7]</a>} - Paragraph 3: ^{<a href="https://www.reinsurancene.ws/optalitix-partners-with-h-w-kaufman-to-support-london-market-scaling-through-burns-wilcox/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://fintech.global/2026/04/28/optalitix-partners-kaufman-to-bring-lloyds-pricing-into-api-driven-workflows/" rel="nofollow" target="_blank">[4]</a>} - Paragraph 4: ^{<a href="https://www.reinsurancene.ws/optalitix-partners-with-h-w-kaufman-to-support-london-market-scaling-through-burns-wilcox/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.optalitix.com/insights/optalitix-partners-with-burns-and-wilcox-uk-to-deliver-industry-technology-solutions" rel="nofollow" target="_blank">[3]</a>} - Paragraph 5: ^{<a href="https://www.optalitix.com/insights/optalitix-partners-with-burns-and-wilcox-uk-to-deliver-industry-technology-solutions" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.optalitix.com/london-market" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.burnsandwilcox.uk/about-us/" rel="nofollow" target="_blank">[6]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62edd48754ffe1b586964Sat, 02 May 2026 17:09:14 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/data-governance-in-insurance-and-real-estate-shifts-from-compliance-to-strategic-advantage-amid-sector-fragmentation<p>As data volumes and complexity grow, insurance and real estate sectors are recognising that robust governance is crucial for operational resilience, competitive edge, and trust-building, with new standards pushing modernization efforts amid fragmentation and regulatory demands.</p><p>Data governance is increasingly moving from a technical housekeeping task to a strategic control point in insurance and real estate, two sectors whose businesses are built on the quality of information. In both industries, firms are trying to extract value from larger, faster and more varied data sets, yet the same expansion is exposing weaknesses in legacy systems, fragmented records and inconsistent standards. According to industry commentary from TechRadar, insurers often want to push ahead with artificial intelligence, blockchain and faster fraud detection, but progress stalls when the underlying data estate remains underdeveloped. KPMG has made a similar point, arguing that insurers are beginning to treat data less as a cost burden and more as a competitive asset.</p> <p>In insurance, the pressure is particularly acute because carriers are trying to combine old mainframe records with claims documents, telematics feeds and other real-time inputs. That makes governance essential for more than compliance: it is also what allows firms to trust their models. ZengRC says insurers need clear standards, ownership and accountability if they are to manage growing data volumes without allowing silos to harden. Swisscom has likewise argued that governance underpins reliable decisions, customer trust and security, while Solix notes that complex multi-system architectures can create lineage, retention and audit problems if controls are weak. The broader message across these reports is that AI and automation do not solve bad data; they often magnify it.</p> <p>The practical challenge is not simply collecting more information, but standardising it in ways that make it usable. TechRadar says insurers increasingly recognise that standardised formats and automated reconciliation are prerequisites for better claims handling and more efficient operations. Regulatory pressure is also helping to force the issue, with compliance requirements acting as a catalyst for modernisation rather than a box-ticking exercise. Insurers that fail to establish strong governance risk slower claims cycles, poor model performance and more difficulty explaining decisions to regulators and customers alike.</p> <p>Real estate faces a different but related problem: fragmentation. Property data is often scattered across local listing services, public registries, lease documents and private spreadsheets, creating a patchwork that is difficult to verify or compare. That matters because automated valuation models are only as credible as the information behind them. If square footage, zoning data or occupancy records are inconsistent, errors can flow directly into lending, investment and portfolio decisions. The sector is also under growing pressure to produce reliable environmental, social and governance reporting, which requires energy-use data and other building metrics to be auditable rather than aspirational.</p> <p>The convergence between the two sectors is becoming clearer as climate risk, sensor data and digital building systems affect both property values and insurance pricing. In that environment, governance is not just about tidiness; it is about resilience. Insurers need to explain how automated underwriting reaches a premium. Property owners need transparent, verifiable data if they want to support asset values and avoid accusations of greenwashing. Across both industries, the underlying lesson is the same: when data is governed well, it becomes a strategic asset; when it is not, it becomes a source of operational and financial risk.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://labs.sogeti.com/industry-deep-dive-in-data-governance-insurance-and-real-estate/" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.techradar.com/pro/why-insurance-innovation-ambitions-keep-stalling" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://kpmg.com/us/en/articles/2026/cost-center-competitive-asset.html" rel="nofollow" target="_blank">[4]</a>} - Paragraph 2: ^{<a href="https://www.zengrc.com/blog/the-importance-of-data-governance-in-the-insurance-industry/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.swisscom.ch/en/b2bmag/data-driven-technologies/data-governance-insurance/" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.solix.com/products/answers/data-governance-in-insurance-industry-managing-compliance-risks/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 3: ^{<a href="https://www.techradar.com/pro/why-insurance-innovation-ambitions-keep-stalling" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://insurtechdigital.com/insurtech/importance-data-governance-insurers" rel="nofollow" target="_blank">[7]</a>} - Paragraph 4: ^{<a href="https://labs.sogeti.com/industry-deep-dive-in-data-governance-insurance-and-real-estate/" rel="nofollow" target="_blank">[1]</a>} - Paragraph 5: ^{<a href="https://labs.sogeti.com/industry-deep-dive-in-data-governance-insurance-and-real-estate/" rel="nofollow" target="_blank">[1]</a>}, ^{<a href="https://kpmg.com/us/en/articles/2026/cost-center-competitive-asset.html" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.swisscom.ch/en/b2bmag/data-driven-technologies/data-governance-insurance/" rel="nofollow" target="_blank">[5]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62edf48754ffe1b586970Sat, 02 May 2026 17:09:11 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/verisk-analytics-signals-resilience-with-strong-subscription-growth-amid-softening-transactional-activity<p>Verisk Analytics reports a steady quarter with revenue reaching $783 million, driven by a 7% organic increase in subscription sales, as the company shifts focus towards AI-powered risk segmentation and aims for broader market growth despite softer transactional volumes.</p><p>Verisk Analytics said its first-quarter performance reflected steady demand for its core subscription products even as transactional activity softened, with revenue rising to about $783 million and subscription sales up 7% on an organic constant-currency basis. According to the company’s earnings materials and call transcript, that recurring business now accounts for 84% of total revenue, helping offset weaker volumes in weather-related and other transactional lines. </p> <p>Management said the softer quarter was shaped by a combination of unusually low weather activity, difficult comparisons with last year’s strong renewals and a temporary disruption to a federal contract, which weighed on claims and property-restoration volumes. Even so, Verisk reported organic constant-currency revenue growth of 4.7% and adjusted EBITDA growth of 5.9%, with margin expansion showing that the business continued to convert revenue into profit efficiently. </p> <p>The company is also trying to position itself for a broader shift in insurance, where executives say the market is moving from a narrow focus on underwriting discipline towards growth, helped by capital levels that remain near record highs. Verisk is centring that effort on its "Core Lines Reimagine" initiative, which uses digitised data and artificial intelligence to improve productivity and sharpen risk segmentation, while moving beyond being a data supplier to acting as a partner in clients’ own AI development. </p> <p>That strategy is already filtering into products such as Digital Media Forensics and enhanced aerial-imagery analytics, which the company says are drawing strong interest from large carriers and generating a growing pipeline of trials and proofs of concept. Verisk also reaffirmed its full-year 2026 outlook and underscored its confidence in cash returns by announcing a $1.5 billion accelerated share repurchase programme, alongside additional buybacks and a dividend increase. </p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://finance.yahoo.com/markets/stocks/articles/verisk-analytics-inc-q1-2026-165904333.html" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.marketbeat.com/instant-alerts/verisk-analytics-q1-earnings-call-highlights-2026-04-29/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.fool.com/earnings/call-transcripts/2026/04/29/verisk-vrsk-q1-2026-earnings-call-transcript/" rel="nofollow" target="_blank">[3]</a>} - Paragraph 2: ^{<a href="https://www.fool.com/earnings/call-transcripts/2026/04/29/verisk-vrsk-q1-2026-earnings-call-transcript/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.allinvestview.com/earnings/VRSK/q1-2026/" rel="nofollow" target="_blank">[4]</a>} - Paragraph 3: ^{<a href="https://www.marketbeat.com/instant-alerts/verisk-analytics-q1-earnings-call-highlights-2026-04-29/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.allinvestview.com/earnings/VRSK/q1-2026/" rel="nofollow" target="_blank">[4]</a>} - Paragraph 4: ^{<a href="https://www.marketbeat.com/instant-alerts/verisk-analytics-q1-earnings-call-highlights-2026-04-29/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.chartmill.com/news/VRSK/Chartmill-46287-Verisk-NASDAQVRSK-Q1-2026-Results-Show-Modest-Beat-on-Revenue-Reaffirms-Full-Year-Guidance" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.marketbeat.com/instant-alerts/verisk-analytics-nasdaqvrsk-posts-earnings-results-beats-estimates-by-008-eps-2026-04-29/" rel="nofollow" target="_blank">[6]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62ede48754ffe1b58696eSat, 02 May 2026 17:09:07 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/high-resolution-geospatial-data-transforms-insurance-underwriting-with-real-time-risk-monitoring<p>Advances in commercial Earth-observation imagery enable insurers to assess property risks with unprecedented precision and timeliness, potentially reshaping underwriting practices and market access strategies amid climate-related threats.</p><p>Insurers have long used location data to gauge catastrophe exposure, but the tools now available are changing what that means in practice. An opinion piece in Dig.In argues that advances in commercial Earth-observation data are allowing carriers to move beyond broad, static views of hazard and towards a more granular picture of how risk is shifting on individual properties over time. That matters as wildfire, flood, convective storm and hurricane losses continue to pressure balance sheets, and as the industry weighs whether better data will be used to broaden coverage or simply sharpen the logic of non-renewals.</p> <p>The most important change is that geospatial information is becoming far more precise. Traditional satellite products often resolved the world at a scale too coarse to assess a single home or parcel, but newer commercial imagery can support sub-metre analysis. According to the Dig.In piece, that opens the door to roof-condition scoring, debris detection and defensible-space assessment without sending someone on site. It also means underwriters can evaluate the specific characteristics of a property rather than relying only on regional hazard overlays.</p> <p>Equally significant is the shift from occasional snapshots to continuous monitoring. The article notes that many catastrophe models still depend on exposure files refreshed only once a year, if that. Daily revisit cycles from satellite constellations make it possible to track whether vegetation is closing in on a building, whether a roof is deteriorating or whether new structures have appeared. But, as the piece points out, those gains depend on consistency in lighting, angle and sensor calibration; without that, change-detection systems can mistake noise for real-world movement.</p> <p>The third advance is spectral information beyond what the eye can see. Near-infrared readings can reveal stress in vegetation that visible imagery misses, while shortwave infrared data can help distinguish soil and plants from concrete or asphalt, which is particularly useful in flood modelling. The article says these signals have existed in research datasets for years, but only recently have they become practical at the resolution and cadence needed for underwriting workflows.</p> <p>That workflow question is where many geospatial projects succeed or fail. The Dig.In piece argues that the data has to arrive in time to influence a bind decision, be embedded in the systems underwriters already use and be explainable enough to justify pricing or declination decisions. Industry vendors are already pushing in that direction: MapTrix AI says it offers auditable parcel-level reports built from sources including FEMA, NOAA, USGS and EPA data; National Flood Data focuses on API-first FEMA flood intelligence for carriers and MGAs; GIA Map promotes real-time wildfire, flood and severe-weather analytics; MSCI has positioned geospatial asset intelligence as a way to identify physical risk across portfolios; and Precisely says its address-level hazard datasets are designed to support mitigation and exposure analysis. Taken together, those offerings suggest the market is moving from simply identifying risk to operationalising it.</p> <p>At the heart of the argument is a broader question about intent. Better data can just as easily be used to refuse business as to write it more intelligently. The Dig.In article contends that the real opportunity lies in turning high-resolution risk insight into mitigation, conditional coverage and new product design, rather than using it only to narrow the insurable market. In that sense, geospatial precision may prove most valuable not when it makes underwriting stricter, but when it makes it possible to say yes more often, and with greater confidence.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://www.dig-in.com/opinion/how-geospatial-data-is-changing-underwriting" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.maptrix.ai/" rel="nofollow" target="_blank">[2]</a>} - Paragraph 2: ^{<a href="https://www.maptrix.ai/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.giamap.com/" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.precisely.com/product/precisely-risks/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 3: ^{<a href="https://www.maptrix.ai/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.msci.com/data-and-analytics/climate-solutions/geospatial-asset-intelligence/geospatial-demo" rel="nofollow" target="_blank">[5]</a>} - Paragraph 4: ^{<a href="https://www.maptrix.ai/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.nationalflooddata.com/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.giamap.com/" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.msci.com/data-and-analytics/climate-solutions/geospatial-asset-intelligence/geospatial-demo" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.precisely.com/product/precisely-risks/" rel="nofollow" target="_blank">[6]</a>}, ^{<a href="https://www.buildingmetrix.com/geospatial-risk-analysis" rel="nofollow" target="_blank">[7]</a>} - Paragraph 5: ^{<a href="https://www.maptrix.ai/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.nationalflooddata.com/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.giamap.com/" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.msci.com/data-and-analytics/climate-solutions/geospatial-asset-intelligence/geospatial-demo" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.precisely.com/product/precisely-risks/" rel="nofollow" target="_blank">[6]</a>}, ^{<a href="https://www.buildingmetrix.com/geospatial-risk-analysis" rel="nofollow" target="_blank">[7]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62ede48754ffe1b58696aSat, 02 May 2026 17:09:04 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/agentic-ai-disrupts-cyber-insurance-underwriting-and-claims-models<p>The rise of autonomous, agentic AI systems is challenging traditional cyber insurance approaches, forcing insurers to rethink underwriting, liability, and claims handling amid new unpredictability and security risks.</p><p>Agentic artificial intelligence is becoming a new headache for cyber insurers, as autonomous systems begin to make decisions, adapt in real time and connect with other digital tools in ways that are harder to predict than conventional software. Industry commentary has increasingly framed these systems as a fresh source of uncertainty for underwriting, because they can alter exposure patterns faster than traditional risk models can absorb.</p> <p>According to reporting from Insurance Business and other industry outlets, the problem is not simply that agentic AI is powerful, but that it can carry out multi-step tasks across enterprise networks with limited human oversight. That creates new pathways for error, misuse and loss, while also making it harder for insurers to judge how permissions, controls and monitoring should affect pricing and coverage terms. Traditional cyber underwriting, built around more familiar forms of malware, human error and static defences, is often seen as too blunt for these environments.</p> <p>Claims handling could also become more complicated, with analysts warning that insurers may struggle to determine causation, accountability and policy triggers when damage is caused by an autonomous system rather than a clearly identifiable person. Claims Pages reported that this could raise difficult questions around liability, especially where an AI agent acts without direct intent but still produces harmful outcomes. The broader concern is that agentic AI may compress attack timelines and amplify existing threats such as data breaches, automated intrusion attempts and system manipulation.</p> <p>In response, insurers are moving towards more specialised underwriting approaches, using advanced analytics and deeper scrutiny of governance, permissions and monitoring arrangements. At the same time, companies deploying agentic AI are being urged to strengthen oversight, set clear accountability lines and maintain continuous monitoring. The emerging view across the sector is that AI is not just changing technology stacks; it is reshaping the insurance model itself.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://bimabazaar.com/insurance-news-and-information/insurance-news/agentic-ai-creates-new-underwriting-challenges-in-cyber-insurance" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://bimabazaar.com/insurance-news-and-information/insurance-news/agentic-ai-creates-new-underwriting-challenges-in-cyber-insurance" rel="nofollow" target="_blank">[1]</a>}, ^{<a href="https://www.forbes.com/councils/forbestechcouncil/2025/12/12/how-agentic-ai-is-reshaping-cyber-risk-and-challenging-the-insurance-model/" rel="nofollow" target="_blank">[2]</a>} - Paragraph 2: ^{<a href="https://www.insurancebusinessmag.com/us/news/cyber/how-agentic-ai-raises-fresh-underwriting-challenges-in-cyber-insurance-571980.aspx" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.completeaitraining.com/news/agentic-ai-creates-new-underwriting-challenges-for-cyber/" rel="nofollow" target="_blank">[5]</a>} - Paragraph 3: ^{<a href="https://www.claimspages.com/news/agentic-ai-creates-new-cyber-insurance-risks-and-underwriting-challenges-20260416/" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://bimabazaar.com/insurance-news-and-information/insurance-news/agentic-ai-creates-new-underwriting-challenges-in-cyber-insurance" rel="nofollow" target="_blank">[1]</a>} - Paragraph 4: ^{<a href="https://bimabazaar.com/insurance-news-and-information/insurance-news/agentic-ai-creates-new-underwriting-challenges-in-cyber-insurance" rel="nofollow" target="_blank">[1]</a>}, ^{<a href="https://www.insurancebusinessmag.com/us/news/cyber/how-agentic-ai-raises-fresh-underwriting-challenges-in-cyber-insurance-571980.aspx" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.itpro.com/security/enterprises-are-adopting-agents-faster-than-they-can-secure-and-govern-them-experts-warn-its-a-disaster-waiting-to-happen" rel="nofollow" target="_blank">[6]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62edc48754ffe1b586960Sat, 02 May 2026 17:08:56 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/rmsi-recognised-as-a-star-in-geoai-market-amid-rising-demand-for-real-time-spatial-data-analytics<p>RMSI has been named a 'Star' company by MarketsandMarkets, reflecting its expanding product portfolio and strategic growth in the fast-evolving geospatial intelligence sector driven by real-time satellite, drone, and sensor data.</p><p>RMSI has been named a "Star" company in the Geospatial Intelligence, or GeoAI, market by MarketsandMarkets, a recognition that the research firm said reflects the company's product range, market reach and growth strategy. The announcement comes as vendors in the sector compete to meet rising demand for location-based analytics across industries that depend on faster operational decisions. </p> <p>The company said the award reflects its position in a market being shaped by the growth of real-time spatial data from satellite imagery, drones and connected sensors. MarketsandMarkets linked broader adoption of GeoAI to uses in infrastructure, utilities, telecoms and government, as organisations look to improve planning, risk assessment and asset management. </p> <p>RMSI also pointed to its expanded relationship with Esri, saying it moved to Gold Partner status in 2025. Esri describes the company as a provider of geospatial and software services across sectors including utilities, navigation, land information management and government, with capabilities spanning data conversion, modelling, analytics and consulting. </p> <p>The recognition sits within a wider market narrative in which geospatial vendors are trying to pair domain expertise with AI-led analytics and cloud delivery. RMSI, which says it has more than three decades of experience and works with clients in over 35 countries, has sought to position itself as a provider of end-to-end digital intelligence services rather than a niche mapping specialist. </p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://www.prnewswire.com/news-releases/rmsi-is-recognized-as-a-star-company-by-marketsandmarkets-for-geospatial-intelligence-geoai-302754109.html" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.prnewswire.com/news-releases/rmsi-is-recognized-as-a-star-company-by-marketsandmarkets-for-geospatial-intelligence-geoai-302754109.html" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://in.linkedin.com/company/marketsandmarkets" rel="nofollow" target="_blank">[6]</a>} - Paragraph 2: ^{<a href="https://www.prnewswire.com/news-releases/rmsi-is-recognized-as-a-star-company-by-marketsandmarkets-for-geospatial-intelligence-geoai-302754109.html" rel="nofollow" target="_blank">[2]</a>} - Paragraph 3: ^{<a href="https://www.rmsi.com/wp-content/uploads/2025/05/rmsi_elevates_to_esri_gold_partnership_status.pdf" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.esri.com/partners/rmsi-private-limited-a2T70000000TNd5EAG" rel="nofollow" target="_blank">[5]</a>} - Paragraph 4: ^{<a href="https://www.rmsi.com/" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://in.linkedin.com/company/marketsandmarkets" rel="nofollow" target="_blank">[6]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62edc48754ffe1b58695eSat, 02 May 2026 17:08:47 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/advanced-analytics-and-generative-ai-reshape-motor-fraud-detection-amid-growing-criminal-sophistication<p>As motor insurance fraud becomes more sophisticated, insurers turn to AI and graph analytics to identify hidden networks, combat organised crime, and prevent losses in an evolving digital landscape.</p><p>Motor insurance fraud is becoming harder to spot as claims handling shifts deeper into digital systems and criminals adapt with more sophisticated tactics. What once relied on obvious falsehoods has expanded into staged collisions, exaggerated repair invoices and entirely invented claims, forcing insurers to confront a problem that is as much about data quality and pattern recognition as it is about investigation. As claim flows grow and manual checks struggle to keep pace, the industry is increasingly treating fraud as an analytical challenge rather than a purely operational one.</p> <p>That shift is reflected in the growing use of artificial intelligence and graph analytics, which SAS says can help insurers move beyond rigid rule sets and labour-intensive reviews. In its webinar on fraud prevention in motor and life insurance, the company argued that advanced analytics can link people, vehicles, addresses and repair networks in ways that expose hidden relationships between apparently separate claims. The aim is not only to detect suspicious activity more quickly, but also to stop losses before they cascade through the claims process.</p> <p>Specialist vendors are making the same case. FraudOps, which markets AI-powered motor fraud detection tools, says insurers need platforms that combine cross-database checks, dashboards and automated analysis to deal with false claims, phantom damage and crash-for-cash schemes. The National Insurance Crime Bureau, meanwhile, describes intelligence and analytics as central to helping the property-casualty sector prevent, detect and deter fraud and vehicle theft, underscoring how collaboration and shared data remain important alongside private-sector technology.</p> <p>The threat is also changing shape. Milliman has warned that generative AI is giving fraudsters new ways to fabricate convincing accident photos, police reports and other evidence for crashes that never happened, raising the stakes for insurers that already face organised networks operating through digital channels. Other industry commentary points to fronting, ghost broking, vehicle dumping and phantom hire scams as examples of how motor fraud has diversified. Together, these trends suggest that insurers increasingly need analytical systems capable not just of confirming what looks suspicious, but of uncovering the broader networks behind the claim.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://www.analyticsinsight.net/data-analytics/the-role-of-data-analytics-in-preventing-motor-insurance-fraud" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.sas.com/sas/webinars/fraud-prevention-in-motor-life-insurance-with-ai-graph-analytics.html" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://the420.in/cracking-down-on-motor-insurance-fraud-ai-data-analytics/" rel="nofollow" target="_blank">[4]</a>} - Paragraph 2: ^{<a href="https://www.sas.com/sas/webinars/fraud-prevention-in-motor-life-insurance-with-ai-graph-analytics.html" rel="nofollow" target="_blank">[2]</a>} - Paragraph 3: ^{<a href="https://www.fraudops.ai/lines-business/motor-insurance-fraud/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.nicb.org/how-we-help/intelligence-analytics" rel="nofollow" target="_blank">[5]</a>} - Paragraph 4: ^{<a href="https://www.milliman.com/en/insight/accidents-that-never-happened-genai-motor-fraud" rel="nofollow" target="_blank">[6]</a>}, ^{<a href="https://synalogik.com/insurance/5-key-types-of-motor-insurance-fraud/" rel="nofollow" target="_blank">[7]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62edc48754ffe1b58695cSat, 02 May 2026 17:08:44 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/insurers-increasingly-harness-machine-learning-to-revolutionise-claims-underwriting-and-fraud-detection<p>The insurance industry is rapidly integrating advanced machine learning models into core operations, transforming claims handling, underwriting precision, and fraud detection with unprecedented speed and accuracy.</p><p>Machine learning is moving from the margins of insurance analytics to the centre of underwriting, claims handling and fraud control. What was once largely the preserve of actuarial tables and manually tuned rules is increasingly being augmented by models that can weigh structured policy data alongside images, medical records, telematics and other signals in near real time. In practice, that means insurers are using AI to estimate claim costs earlier, refine reserves faster and identify risks before they turn into losses.</p> <p>The shift is most visible in claims prediction and triage. According to Milliman’s claims analytics work, insurers are using advanced models to spot high-loss claims early by combining policy information with detailed medical data, helping claims teams focus resources where they matter most. LCP says its InsurSight platform can generate initial reserves in minutes and automatically flag the assumptions driving them, reflecting a broader move towards faster reserving and automated diagnostics. Mobotory, meanwhile, says its commercial insurance tools are designed to predict claim costs within 48 hours, support quicker settlements and improve premium setting.</p> <p>Underwriting is following a similar path. Rather than relying only on broad demographic or historical groupings, insurers are now layering machine learning over traditional models to sharpen risk selection and pricing. Platform providers say this can help with more accurate premium estimates, quicker decisions and better defence file preparation. Some systems are also being used to identify litigation risk, excessive medical costs and other early warning signs that may affect the eventual cost of a claim. The appeal is not just speed: it is the promise of better decisions at the point where risk is first priced or accepted.</p> <p>Fraud detection remains one of the clearest use cases. Waymore.ai and other vendors pitching AI for the insurance sector argue that machine learning can help spot unusual patterns across claims, billing and behaviour that would be hard to catch manually. By combining anomaly detection with automated review, insurers can reduce false positives, tighten controls and reserve human attention for the most suspicious cases. That matters because even modest gains in fraud detection can translate into significant savings across large books of business.</p> <p>The technology is also changing how insurers work internally. Claims adjusters often spend a large share of their time gathering and formatting information, and AI-driven tools are being marketed as a way to reduce that burden. Some systems now provide dashboards of expected outcomes via APIs, allowing teams to move from data collection to decision-making more quickly. Supporters say this can make claims handling faster and more consistent, while giving specialists more time to deal with complex or sensitive files that still require human judgement.</p> <p>Still, the push towards automation is not without limits. The industry’s own vendors and advisers emphasise that machine learning works best when it is paired with governance, explainability and human oversight. The most successful deployments appear to be those that enhance underwriting, reserving and claims operations rather than trying to replace them entirely. For insurers, the real prize is not simply automation for its own sake, but a more responsive system that can price risk more precisely, settle claims faster and react earlier to emerging losses.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://medium.com/codetodeploy/how-insurance-companies-use-machine-learning-to-predict-claims-and-assess-risk-4f1c6a50c57f?source=rss------machine_learning-5" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.mobotory.com/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://waymore.ai/industries/insurance" rel="nofollow" target="_blank">[7]</a>} - Paragraph 2: ^{<a href="https://www.rxhistories.com/nodal/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.lcp.com/insurance/insursight" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.mobotory.com/" rel="nofollow" target="_blank">[2]</a>} - Paragraph 3: ^{<a href="https://us.milliman.com/en/Services/Predictive-analytics-solutions/Claims" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.mobotory.com/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.rxhistories.com/nodal/" rel="nofollow" target="_blank">[3]</a>} - Paragraph 4: ^{<a href="https://waymore.ai/industries/insurance" rel="nofollow" target="_blank">[7]</a>}, ^{<a href="https://www.optimalexsolutions.com/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 5: ^{<a href="https://www.optimalexsolutions.com/" rel="nofollow" target="_blank">[6]</a>}, ^{<a href="https://waymore.ai/industries/insurance" rel="nofollow" target="_blank">[7]</a>} - Paragraph 6: ^{<a href="https://www.lcp.com/insurance/insursight" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.rxhistories.com/nodal/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://us.milliman.com/en/Services/Predictive-analytics-solutions/Claims" rel="nofollow" target="_blank">[5]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62edb48754ffe1b586958Sat, 02 May 2026 17:08:44 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/eagleview-launches-horizon-a-geospatial-ai-platform-redefining-rapid-property-analysis<p>Eagleview introduces Horizon, an innovative geospatial AI system designed to accelerate decision-making for insurers, construction, and property management sectors by integrating over two decades of aerial land data with artificial intelligence.</p><p>Eagleview has launched Horizon, a geospatial artificial intelligence platform that it says will help companies make faster decisions using property imagery and land data drawn from more than two decades of collection. The Bellevue, Washington-based firm is targeting insurers, construction companies, government users and property managers, positioning the tool as a way to turn aerial intelligence into operational analysis.</p> <p>According to the company, Horizon brings together Eagleview’s proprietary imagery with outside data sources and customer information, allowing users to search, filter and assess properties through automated workflows. Eagleview says the system is built to support tasks such as claims triage, risk review and infrastructure planning, particularly after severe weather or other events that require rapid property inspection.</p> <p>Chief executive Piers Dormeyer said Eagleview has spent more than 20 years assembling what it describes as the country’s most comprehensive property dataset, and argued that Horizon is designed to improve the reliability of business decisions by tying outputs back to verified imagery and data. Chief technology officer Tripp Cox said the platform is intended to do more than function as a natural-language search tool, describing it as an "agentic partner" for geospatial work.</p> <p>The launch reflects a broader push by Eagleview to fold artificial intelligence into its property intelligence products. On its insurance and real-estate pages, the company says its wider platform is already built to fit existing workflows and to support applications ranging from claims management and risk assessment to valuation and market analysis. Industry coverage of the release has also highlighted Eagleview’s efforts to make complex geospatial analysis more accessible through text-based queries and integrated data tools.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://iireporter.com/eagleview-launches-horizon-geospatial-ai-engine/" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.eagleview.com/news-announcements/eagleview-launches-eagleview-horizon/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://commercialobserver.com/2026/04/geospatial-technology-eagleview-ai/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 2: ^{<a href="https://www.eagleview.com/news-announcements/eagleview-launches-eagleview-horizon/" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.eagleview.com/insurance/platform" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.roofingcontractor.com/articles/102133-eagleview-horizon-new-ai-engine-for-property-intelligence-launches" rel="nofollow" target="_blank">[7]</a>} - Paragraph 3: ^{<a href="https://iireporter.com/eagleview-launches-horizon-geospatial-ai-engine/" rel="nofollow" target="_blank">[1]</a>}, ^{<a href="https://www.eagleview.com/news-announcements/eagleview-launches-eagleview-horizon/" rel="nofollow" target="_blank">[2]</a>} - Paragraph 4: ^{<a href="https://www.constructionowners.com/press-release/eagleview-introduces-horizon-ai-engine" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.eagleview.com/insurance/platform" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.eagleview.com/real-estate/" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://commercialobserver.com/2026/04/geospatial-technology-eagleview-ai/" rel="nofollow" target="_blank">[6]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62eda48754ffe1b586956Sat, 02 May 2026 17:08:35 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/data-quality-hurdles-threaten-to-stall-ai-adoption-in-insurance-industry<p>Insurers and reinsurers recognise AI's potential but struggle with fragmented data, legacy systems, and governance challenges that risk slowing industry transformation.</p><p>Artificial intelligence may be moving from pilot projects into mainstream insurance strategy, but the sector’s real constraint is increasingly looking like data, not software. In reinsurance especially, where underwriting, finance, risk and capital management intersect across multiple systems and jurisdictions, industry observers say the promise of AI is being held back by fragmented records, manual reconciliation and uneven governance.</p> <p>That warning is echoed beyond the reinsurance niche. TechRadar Pro reported that insurers are keen to deploy tools such as AI, blockchain and real-time fraud detection, yet many are still working around legacy infrastructure and scattered data. The publication cited research showing that 82% of insurers believe AI will shape the industry’s future, but only 14% have integrated it into financial operations, underscoring how wide the gap remains between ambition and execution.</p> <p>In reinsurance, that gap can be particularly costly. Data sets covering exposures, recoverables and financial flows must be accurate, current and auditable, but many firms still rely on spreadsheets and disconnected systems. According to risk specialist Risktec, the insurers and reinsurers getting the most value from AI are the ones investing first in data quality, common terminology and better documentation, rather than trying to automate flawed processes.</p> <p>The industry is also beginning to recognise that scale requires more than isolated use cases. AM Best said in a recent survey that nearly 60% of respondents expect AI to materially alter business models within the next one to three years, while 41% are already using AI across core functions. Even so, the same survey pointed to persistent problems around data readiness, cybersecurity and legacy integration, suggesting adoption is advancing unevenly.</p> <p>That is why cloud-native, “always-current” systems are becoming more central to the conversation. Reuters has previously reported a broader push across financial services for standardised data formats, automated reconciliation and stronger governance, themes that also run through ACORD’s work on insurance data standards. The logic is simple: AI models can only perform reliably if the information beneath them is consistent, explainable and easy to share across business lines.</p> <p>For reinsurers and carriers alike, the strategic shift is moving from asking where AI can be used to asking whether the business is ready for it. The firms that modernise data foundations first are likely to gain faster pricing decisions, better capital deployment and more responsive risk selection. Those that do not may find that the technology is not the bottleneck after all.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://www.insurtechinsights.com/reinsurance-data-foundations-seen-as-critical-to-unlocking-scalable-ai-in-insurance/" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.techradar.com/pro/why-insurance-innovation-ambitions-keep-stalling" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.insurtechinsights.com/reinsurance-data-foundations-seen-as-critical-to-unlocking-scalable-ai-in-insurance/" rel="nofollow" target="_blank">[1]</a>} - Paragraph 2: ^{<a href="https://www.techradar.com/pro/why-insurance-innovation-ambitions-keep-stalling" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.insurancethoughtleadership.com/ai-machine-learning/why-insurance-lagging-ai" rel="nofollow" target="_blank">[5]</a>} - Paragraph 3: ^{<a href="https://risktec.io/articles/2025-05-07-data-quality-first-the-foundation-of-scalable-ai-in-reinsurance" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.insurtechinsights.com/reinsurance-data-foundations-seen-as-critical-to-unlocking-scalable-ai-in-insurance/" rel="nofollow" target="_blank">[1]</a>} - Paragraph 4: ^{<a href="https://www.insurancebusinessmag.com/us/news/breaking-news/ai-ambition-outpaces-insurer-readiness-am-best-finds-573285.aspx" rel="nofollow" target="_blank">[4]</a>} - Paragraph 5: ^{<a href="https://www.reinsurancene.ws/insurance-data-standards-key-to-unlocking-ais-potential-acord/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 6: ^{<a href="https://www.insurtechinsights.com/reinsurance-data-foundations-seen-as-critical-to-unlocking-scalable-ai-in-insurance/" rel="nofollow" target="_blank">[1]</a>}, ^{<a href="https://risktec.io/articles/2025-05-07-data-quality-first-the-foundation-of-scalable-ai-in-reinsurance" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.insurancebusinessmag.com/us/news/breaking-news/ai-ambition-outpaces-insurer-readiness-am-best-finds-573285.aspx" rel="nofollow" target="_blank">[4]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62ed948754ffe1b586952Sat, 02 May 2026 17:08:25 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/ai-revolutionises-insurance-underwriting-with-faster-more-comprehensive-risk-assessment<p>AI is transforming insurance underwriting by enabling faster decisions, broader data analysis, and more efficient workflows, though challenges in governance and data quality persist as adoption accelerates into mainstream use.</p><p>Artificial intelligence is beginning to redraw one of insurance’s most labour-intensive processes: underwriting. Where traditional review can involve slow manual checks, fragmented data and lengthy back-and-forth with applicants, AI systems are being used to speed up decision-making, sharpen risk selection and make pricing more consistent. The shift is especially visible in life insurance, where a recent Pacific Life underwriting outlook found that nearly half of insurers are now using AI in some form, with some fully embedding it into daily workflows and others relying on it as a decision-support tool.</p> <p>The appeal is straightforward. Insurers are under pressure to respond faster to customers who expect near-instant quotes, while underwriting teams face persistent staffing and skills shortages. At the same time, carriers are being asked to make decisions that are both quicker and more defensible. According to industry reporting, AI adoption is moving beyond experimentation and into live operations, with many firms now seeing gains in efficiency, data use and revenue potential, even as governance and talent gaps remain a concern.</p> <p>In practice, AI underwriting systems can draw on far broader information than a conventional application review. Beyond basic forms and historical policy data, they can ingest claims histories, credit-related signals where permitted, property data, telematics, public records and even satellite imagery for certain lines of business. That wider view allows models to identify patterns that human reviewers might miss, supporting faster assessment in life, health, property and casualty, auto and fraud screening. The result, proponents say, is a more complete risk picture and fewer good applicants being slowed down by outdated manual processes.</p> <p>The technology stack behind that change usually combines machine learning, natural language processing and workflow automation. AI can triage submissions, flag anomalies, and route only complex or borderline cases to human underwriters. Platforms in the market are increasingly pitching this as an end-to-end operating model rather than a standalone tool. Insurity, for example, says its AI-first platform embeds automation across policy, claims, billing and analytics, while Otera promotes autonomous underwriting workflows that can move from submission to bound policy with consistent governance. Those claims point to a broader industry trend: underwriting is no longer being treated as a back-office function that merely scores risk, but as a data-rich process that can be continuously optimised.</p> <p>Still, the adoption story is not without friction. Data quality remains a major obstacle, because poor or incomplete inputs can lead to flawed outputs. Legacy policy systems can also make integration difficult, especially for insurers whose information is trapped in silos. Regulators, meanwhile, are likely to scrutinise any model that cannot explain how it reached a decision, making transparency and auditability essential. Gallagher’s latest AI adoption survey suggests that many large companies have already moved well beyond pilots, but it also points to persistent worries about governance, workforce capability and proving return on investment.</p> <p>For that reason, most specialists argue that AI is more likely to reshape underwriting than replace underwriters outright. Routine files can be handled faster and more consistently, while more nuanced cases still require human judgement, empathy and commercial context. The likely future, according to the companies developing these systems, is a hybrid model in which AI handles the volume and the first pass, and people focus on exceptions, oversight and broker relationships. If that balance holds, underwriting may become less of a bottleneck and more of a competitive advantage.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://www.beyondkey.com/blog/ai-in-insurance-underwriting/" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.insurancebusinessmag.com/us/news/life-insurance/ai-adoption-accelerates-in-life-insurance-underwriting-570071.aspx" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.altexsoft.com/blog/ai-insurance-underwriting/" rel="nofollow" target="_blank">[3]</a>} - Paragraph 2: ^{<a href="https://www.insurancebusinessmag.com/us/news/life-insurance/ai-adoption-accelerates-in-life-insurance-underwriting-570071.aspx" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.insurancebusinessmag.com/us/news/technology/survey-ai-goes-mainstream-but-insurers-face-skills-risk-and-coverage-gaps-566336.aspx" rel="nofollow" target="_blank">[7]</a>} - Paragraph 3: ^{<a href="https://www.altexsoft.com/blog/ai-insurance-underwriting/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.biginy.org/news/tech-news/ai-in-insurance-underwriting/" rel="nofollow" target="_blank">[5]</a>} - Paragraph 4: ^{<a href="https://www.insurity.com/ai-at-insurity" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.otera.ai/solutions/insurance-autonomous-underwriting" rel="nofollow" target="_blank">[6]</a>} - Paragraph 5: ^{<a href="https://www.insurancebusinessmag.com/us/news/life-insurance/ai-adoption-accelerates-in-life-insurance-underwriting-570071.aspx" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.altexsoft.com/blog/ai-insurance-underwriting/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.insurancebusinessmag.com/us/news/technology/survey-ai-goes-mainstream-but-insurers-face-skills-risk-and-coverage-gaps-566336.aspx" rel="nofollow" target="_blank">[7]</a>} - Paragraph 6: ^{<a href="https://www.altexsoft.com/blog/ai-insurance-underwriting/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.biginy.org/news/tech-news/ai-in-insurance-underwriting/" rel="nofollow" target="_blank">[5]</a>}, ^{<a href="https://www.otera.ai/solutions/insurance-autonomous-underwriting" rel="nofollow" target="_blank">[6]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62ed948754ffe1b586950Sat, 02 May 2026 17:08:24 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/insurance-chief-risk-officers-prioritise-cyber-and-ai-driven-resilience-amidst-shifting-risk-landscape<p>Insurance chief risk officers are increasingly focused on cyber threats, third-party risks, and integrating generative AI into risk management, signalling a strategic shift in the sector’s approach to interconnected vulnerabilities and operational resilience.</p><p>Insurance chief risk officers are increasingly fixated on cyber threats, with EY saying a majority now see cybersecurity as the issue most likely to demand their attention over the next year. The consultancy's latest survey also shows that third-party and vendor cyber exposure sits among the top five concerns for a significant share of respondents, underlining how the sector's risk picture is being shaped as much by supplier networks as by internal systems.</p> <p>EY's findings suggest insurers are responding by folding cyber, operational resilience and third-party oversight into broader, more joined-up risk frameworks. The survey says firms are expanding continuous monitoring, tightening governance and using more scenario testing, while also widening scrutiny of fourth-party relationships. That reflects a wider shift in the industry towards anticipating how disruption can travel through increasingly interconnected operations.</p> <p>The same study points to a rapid embrace of generative AI in risk teams, with chatbot and large language model integration emerging as the most common use case. EY said insurers are also investing more heavily in data, analytics and AI capabilities, even as they expect routine manual work in risk functions to decline. A separate EY report published in May 2025 said governance and controls are becoming more important as AI adoption accelerates and regulators take different approaches across jurisdictions, prompting insurers to refresh control frameworks, clarify accountability and automate monitoring where possible.</p> <p>Data quality remains a major constraint and opportunity. EY's more detailed insurance survey says many risk leaders are trying to improve access to consistent, high-quality information so they can generate faster and more useful insights, with centralised data platforms helping reduce fragmentation. The firm argues that these changes are also reshaping the risk workforce, with demand rising for people who combine digital, analytical and business skills. In EY's view, that is pushing the chief risk officer role towards a more strategic position in corporate decision-making and transformation.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://www.reinsurancene.ws/insurance-cros-flag-cybersecurity-as-top-risk-while-ai-and-data-investment-surge-ey-iif-survey-finds/" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.ey.com/en_gl/insights/insurance/documents/ey-inaugural-ey-iif-global-insurance-risk-management-survey-march23.pdf" rel="nofollow" target="_blank">[2]</a>} - Paragraph 2: ^{<a href="https://www.reinsurancene.ws/insurance-cros-flag-cybersecurity-as-top-risk-while-ai-and-data-investment-surge-ey-iif-survey-finds/" rel="nofollow" target="_blank">[1]</a>} - Paragraph 3: ^{<a href="https://www.ey.com/en_gl/insights/insurance/documents/ey-gl-risk-managements-strategic-opportunity-05-2025.pdf" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://www.ey.com/en_gl/insights/insurance/documents/ey-inaugural-ey-iif-global-insurance-risk-management-survey-march23.pdf" rel="nofollow" target="_blank">[2]</a>} - Paragraph 4: ^{<a href="https://www.ey.com/en_gl/insights/insurance/documents/ey-global-insurance-risk-survey.pdf" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://www.reinsurancene.ws/insurance-cros-flag-cybersecurity-as-top-risk-while-ai-and-data-investment-surge-ey-iif-survey-finds/" rel="nofollow" target="_blank">[1]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62eda48754ffe1b586954Sat, 02 May 2026 17:08:22 +0000http://noah.makes.news/gb/en/insurance-risk-tech/2026/05/02/ai-driven-insights-transform-property-insurance-decision-making-landscape-in-2026<p>Insurers are shifting from legacy systems to AI-powered tools integrated with Power BI, enhancing risk assessment, claims handling, and portfolio management amid rising climate and inflation pressures.</p><p>Property insurance is being reshaped less by a shortage of data than by a shortage of usable intelligence. Insurers have long held claims histories, property records, inspection notes, weather feeds and geospatial information, yet many still struggle to turn those inputs into timely underwriting, pricing and claims decisions. The result is familiar: inconsistent risk selection, slow handling of losses and missed opportunities to retain profitable business.</p> <p>That disconnect is widening as catastrophe losses rise and traditional business intelligence tools struggle to keep pace. The ISHIR article argues that legacy dashboards are largely backward-looking, showing what has already happened rather than flagging what is likely to happen next. In practice, that means underwriters and claims teams are often working with fragmented systems, manual spreadsheets and data that arrives too late to change the outcome.</p> <p>Microsoft’s financial services blog has made a similar case for insurance, saying agentic AI is beginning to connect previously siloed workflows across underwriting, claims, marketing and customer service. The company describes a shift from isolated processes to linked systems that can automate decisions, surface recommendations and reduce friction for both staff and customers. That broader industry direction helps explain why AI is increasingly being positioned not as an add-on, but as the operating layer for insurance.</p> <p>The claims function is where the change is most visible. According to OnRec, AI-driven systems are already handling a growing share of home insurance claims volume in 2026, helping insurers sort cases by severity, speed up settlement and improve accuracy. At the same time, technology-focused claims specialists say the pressure on carriers has intensified because of climate-related losses, inflation and supply chain constraints, which make efficient triage and cost control more important than ever.</p> <p>For property insurers, the appeal of combining AI with Power BI lies in the promise of a single decision environment. The ISHIR piece says that approach can bring together underwriting scores, fraud alerts, concentration-risk views and renewal insights in one interface, giving teams a more consistent picture of portfolio health. In that model, AI does the analysis, while Power BI turns the output into role-specific dashboards that claims managers, underwriters and executives can act on quickly.</p> <p>The broader case is straightforward: insurance is full of measurable decisions, and even modest gains in pricing accuracy, fraud detection or claims speed can have an outsized effect on loss ratios and retention. That is why vendors and consultancies are pushing phased adoption, usually starting with data consolidation and fraud use cases before moving into underwriting intelligence and executive reporting. The common thread is not more reporting, but better judgment, delivered faster.</p> <h3>Source Reference Map</h3> <p><strong>Inspired by headline at:</strong> ^{<a href="https://securityboulevard.com/2026/04/how-ai-and-power-bi-are-transforming-commercial-residential-property-insurance/" rel="nofollow" target="_blank">[1]</a>}</p> <p><strong>Sources by paragraph:</strong> - Paragraph 1: ^{<a href="https://www.ishir.com/blog/321023/how-ai-and-power-bi-are-transforming-commercial-residential-property-insurance.htm" rel="nofollow" target="_blank">[2]</a>} - Paragraph 2: ^{<a href="https://www.ishir.com/blog/321023/how-ai-and-power-bi-are-transforming-commercial-residential-property-insurance.htm" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://tpa.sedgwick.com/blog/how-technology-is-transforming-residential-property-claims/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 3: ^{<a href="https://www.microsoft.com/en-us/industry/blog/financial-services/2026/02/18/from-bottlenecks-to-breakthroughs-how-agentic-ai-is-reshaping-insurance/" rel="nofollow" target="_blank">[3]</a>} - Paragraph 4: ^{<a href="https://www.onrec.com/news/ai-automation/how-ai-and-automation-are-changing-home-insurance-claims-in-2026" rel="nofollow" target="_blank">[4]</a>}, ^{<a href="https://tpa.sedgwick.com/blog/how-technology-is-transforming-residential-property-claims/" rel="nofollow" target="_blank">[6]</a>} - Paragraph 5: ^{<a href="https://www.ishir.com/blog/321023/how-ai-and-power-bi-are-transforming-commercial-residential-property-insurance.htm" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.epcgroup.net/insurance-power-bi-consulting" rel="nofollow" target="_blank">[7]</a>} - Paragraph 6: ^{<a href="https://www.ishir.com/blog/321023/how-ai-and-power-bi-are-transforming-commercial-residential-property-insurance.htm" rel="nofollow" target="_blank">[2]</a>}, ^{<a href="https://www.microsoft.com/en-us/industry/blog/financial-services/2026/02/18/from-bottlenecks-to-breakthroughs-how-agentic-ai-is-reshaping-insurance/" rel="nofollow" target="_blank">[3]</a>}, ^{<a href="https://insurnest.com/blog/ai-agents-for-property-insurance/" rel="nofollow" target="_blank">[5]</a>}</p> <p>Source: <a href="https://www.noahwire.com" rel="nofollow" target="_blank">Noah Wire Services</a></p>69f62ed848754ffe1b58694eSat, 02 May 2026 17:08:15 +0000