Industry Picks

Read the article here: https://iireporter.com/exl-launches-exldata-ai-to-help-enterprises-prepare-data-for-ai/ Our Take EXL has launched EXLdata.ai, a modular suite that uses autonomous agents to unify and prepare structured and unstructured data for AI, partnering with Databricks to leverage Agent Bricks and Unity Catalog. The company frames the product as a solution to fragmented data — citing that only 30% of organisations report enterprise-wide data accessibility and that about 85% of data is unstructured. Technically, the platform automates discovery, migration, governance, annotation and operations across the data lifecycle, offers observability and compliance via Databricks integration, and can be deployed partially or fully through a central workbench. EXL promises lower costs, quicker rollouts and better model accuracy; IDC and Databricks position the approach as platform-agnostic and production-grade. Sceptical view: the announcement is heavy on marketing claims and light on independent proof points. Autonomous agents can speed work but also introduce new governance, quality and privacy risks that need explicit controls and auditability. Integration with Databricks is practical but risks ecosystem lock-in for some customers. The offering targets a real pain point — unstructured, siloed data — but buyers will need clear performance metrics, security assessments and customer case studies before treating this as a turnkey fix.

Read the article here: https://www.claimsjournal.com/news/national/2025/11/05/333914.htm Our Take Forrester predicts cyber insurance premiums will rise about 15% in 2026 as widespread AI adoption expands attack surfaces and gives criminals more sophisticated tools. The technology itself is becoming a target, and insurers cite more successful breaches as defensive capabilities lag. Moody’s and Swiss Re data underline persistent attack frequency and a cooled growth phase after the rapid expansion from 2017 to 2022, with supply‑chain and open‑source weaknesses still exposing organisations. Insurers see an opportunity to sell defence services and new underwriting for AI risks while using automation to shave expense ratios. Forrester expects a two‑percentage‑point decline among the top 50 carriers. Large firms with scale and clear AI strategies look set to pull ahead; smaller carriers face a lag in adoption and risk losing market share. The report flags practical hurdles: unclear use cases, data and governance gaps, and talent shortages that make realising AI returns difficult. That optimistic playbook has downsides. Pricing pressure and a shift towards defence services could create conflicts of interest and moral‑hazard issues if insurers underwrite their own mitigation. Concentration among big technology‑savvy firms may reduce competition and raise costs for buyers who can’t afford higher premiums. Regulators, boards and customers should treat the forecasts as a warning: AI escalates exposures faster than the market or many organisations can adapt.

Read the article here: https://iireporter.com/fintary-raises-10-million-to-automate-insurance-commission-management/ Our Take Fintary offers a straightforward fix for a persistent headache: automate commission, hierarchy and override calculations that insurers still run in spreadsheets. The platform promises real‑time visibility into revenue and agent payouts, faster reconciliation and fewer chargebacks — claims backed by customer reports and a founder’s direct experience. Investors highlighted industry know‑how, but the article doesn’t say how much was raised or give independent metrics beyond “millions processed.” The product addresses a real operational cost for life, annuity, health, employee benefits and P&C insurers. The obvious tests will be integration with legacy policy and payroll systems, handling regulatory and audit requirements, and proving ROI at scale. Migration, edge cases in commission rules and vendor lock‑in are practical risks that merit scrutiny. Overall, this looks like a useful specialist tool with plausible benefits. Its impact will depend on measurable savings, the ease of implementation, and how transparently the company reports outcomes as it expands the team and broadens its product scope.

Read the article here: https://iireporter.com/avallon-raises-4-6m-to-scale-ai-agents-for-insurance-claims-automation/ Our Take Avallon has closed a Frontline Ventures-led seed round to scale an AI-agent platform that automates claims tasks — intake, document summarisation, status tracking and exposure analysis — by integrating with CMS platforms, IVR systems and data warehouses. Funding is earmarked for hiring and product development as the start-up moves from bespoke workers’ compensation and automotive solutions to a platform aimed at all property/casualty lines and healthcare. The company points to rapid early traction — tenfold revenue growth during YC Spring 2025 and contracts with TPAs in the US and Europe, including Athens Administrators — and frames its product as a response to projected industry attrition. Frontline’s partner will join as a board observer, signalling active investor involvement and expectations of commercial returns from voice and workflow AI. There are important caveats. Integrating with legacy insurance systems and meeting healthcare and privacy regulations is operationally hard; large language models still produce errors and can misinterpret legal or medical nuance. Claims of solving staffing shortages depend on reliable, auditable performance at scale, not proof-of-concept wins. The customer base so far appears concentrated among TPAs rather than major carriers, so enterprise-grade robustness and clear ROI remain unproven. What to watch next: whether Avallon sustains accuracy and compliance in live, high-volume deployments; measurable cost or speed gains for clients; broader adoption beyond TPAs; and how the company balances automation benefits with oversight and data-protection obligations.

Read the article here: https://iireporter.com/invoicecloud-and-duck-creek-integrate-payment-systems-for-insurers/ Our Take InvoiceCloud has integrated its digital payments platform into Duck Creek’s Payments Marketplace so property/casualty insurers can offer real‑time inbound payments and outbound disbursements through Duck Creek’s core systems. The tie‑up targets higher digital payment, AutoPay and paperless take‑up to cut manual processing, delinquencies and operational cost, and promises faster implementation with no ongoing upgrade maintenance. This looks like a pragmatic product pairing that could improve policyholder payment options and speed cash flows, but the headline claims gloss over practicalities. Success depends on how deep the integration is with legacy systems, migration and implementation costs, data/security controls and vendor terms. “No maintenance” for buyers often means different support models or new fees, and customer adoption of digital channels is uneven. Useful as an incremental modernisation path, provided insurers do upfront due diligence on integration complexity, total cost of ownership, service‑level guarantees and regulatory/compliance implications before committing.

Read the article here: https://iireporter.com/cytora-integrates-fenris-predictive-intelligence-into-commercial-risk-platform/ Our Take Cytora has embedded Fenris’ predictive risk intelligence into its digital risk platform so incoming submissions are automatically enriched with firmographics, business classification, financial-health indicators and risk scores to speed triage, pre-fill applications and help underwriters align risks with appetite. Fenris’ models — trained on hundreds of variables to forecast bind propensity, exposure and conversion — are now available inside Cytora’s workflow alongside LLMs and agentic AI, intended to support triage, pricing and submission prioritisation and reduce manual review. The integration is a pragmatic move towards data-driven underwriting, but its value hinges on data coverage, model validation and explainability. Proprietary scores can mask biases, create blind spots and foster vendor dependency; insurers will need robust testing, monitoring, and clear audit trails before treating these signals as definitive.

Read the article here: https://iireporter.com/inshur-launches-period-z-insurance-through-incline-partnership/ Our Take INSHUR has added Period Z, an on‑rental policy that complements its Period X off‑rental cover, creating a single suite aimed at US carshare fleet operators. A new partnership with Incline P&C supplies underwriting capacity and nationwide reach; the combined products are pitched to cut admin, let fleets operate across multiple platforms and open new revenue lines. The move fits a growing US carshare market, but the proposition will stand or fall on pricing, claims handling, regulatory fit and whether fleets actually switch from juggling multiple insurers. The launch is strategic, not guaranteed disruption.

Read the article here: https://iireporter.com/itc-briefing-fisent-targets-automation-gaps-with-ai-that-understands-content/ Our Take Fisent is a Toronto startup that uses AI to read and interpret unstructured documents and so close the “last mile” where automation stalls in insurance workflows. Born from a KYC product in banking and refocused after generative AI arrived, its BizAI platform plugs into existing underwriting and claims systems (with Pega ties) to classify, summarise and extract meaning from emails, PDFs and images. The sales motion targets narrow “micro‑journeys” — endorsements, submissions, enrolment forms — showing quick proofs of concept that scale horizontally; the company reports $2m seed funding, about 10 enterprise customers, 500% usage growth and claims all licensed customers reach production. The pitch is pragmatic: inject intelligence via APIs rather than rebuild core systems, speed decisions, and cut workflow stops. That strategy suits insurers wary of wholesale replacement. The claims warrant scrutiny, though — a 100% production success rate from a 10‑customer base reads like marketing, and the article gives few hard metrics on accuracy, error rates, implementation effort or long‑term maintenance. The claim to “understand content we’ve never seen” needs technical detail, and competitors are numerous. Still, the production‑first, focused approach is a sensible way to address a real operational bottleneck if the platform proves robust at scale.

Read the article here: https://iireporter.com/nationwides-ai-era-cto-guru-vasudeva-on-scaling-transformation-trust-and-talent/ Our Take Nationwide has pledged $1.5bn through 2028, roughly $100m a year for AI, shifting from decade-old predictive models to generative AI and concentrating efforts into 18 flagship projects to scale impact. Key use cases promise real productivity gains: Project Rosie automates lengthy underwriting document review while keeping underwriters in control; generative tools accelerated a major code modernisation from years to months; Claims Log Notes already summarises complex claim histories for service reps. The firm pairs tools with people: a target of 90% employee AI use, a split between everyday productivity tools and business-process agents, and grassroots champions to drive adoption and attract younger tech talent. The plan is bold and measurable — aiming to lift revenue toward $100bn and allocating around 20% of IT spend — but it carries familiar risks: vendor dependence, overpromising on generative accuracy, regulatory and fairness challenges, and execution risk across dozens of systems. Strong governance (Blue/Red teams) helps, but real success will depend on rigorous validation, transparent metrics and sustained operational discipline.