The grassroots approach to AI adoption has probably gone as far as it’s going to go.

Point solutions are impressive—but rarely scale. In-house pilots generate strong early results, only for performance to deteriorate for lack of consistent data.

As for copilots, people generally appreciate tools that draft emails, summarize documents, or eliminate busywork. But enthusiasm tends to wane when the tool stops assisting and starts deciding. Handing approval authority to a model can feel indistinguishable from handing over your badge and desk.

That's not irrational. Nobody organizes a grassroots campaign to accelerate their own obsolescence.

The next big push in enterprise AI, when it comes—and I suspect it will come sooner rather than later—will come from above: top down, through the capital structure.

Trillions of dollars are being invested in the infrastructure required to power the AI economy. The institutions providing that capital aren't investing on faith. They have underwritten a thesis: that vast investments in computing, data centers, power generation, networking and models will produce vast economic returns.

For that thesis to work, somebody has to create the demand.

Consider who is financing the AI buildout. BlackRock, Blackstone, Apollo, KKR, Goldman Sachs and other institutions that manage or deploy trillions of dollars are helping finance hundreds of billions of dollars in AI infrastructure. Many of those same institutions are among the largest shareholders of America's public companies, including insurers.

At Travelers, for example, Vanguard, BlackRock, State Street and Fidelity together account for roughly one-third of the company's shares. The financial system is simultaneously financing the supply of AI infrastructure and owning the enterprises whose adoption of that infrastructure will be necessary to justify the investment.

There's an almost poetic financial loop here worth noting: Blackstone's AI infrastructure investments are partly financed with insurance capital. Blackstone now manages $290 billion in insurance capital, while its infrastructure and data-center strategy explicitly connects digital infrastructure with its insurance-capital platform.

All of this means the capital funding AI infrastructure and the capital owning the companies expected to use it increasingly overlap.

Put more plainly: the same capital on your shareholder register may also be financing the infrastructure that needs you to become an AI customer.

The pressure will run downhill. Capital markets will lean on boards. Boards will lean on CEOs. CEOs will hang targets on business units. And eventually the questions will get very specific: What percentage of your workforce is AI-enabled? What's the productivity delta? Where's the ROI? What are your competitors doing with AI that you aren't? What is stopping you from moving faster?

Delivering solid business results is, today, enough. In the near future, how those results are delivered—through what combination of human effort, automation, and AI—will increasingly factor into executive evaluation.

Insurance leaders can prepare now. That does not mean recklessly deploying AI everywhere. It means creating the conditions under which AI can produce durable, defensible business results.

Governance is part of that infrastructure. Done badly, governance becomes an institutional “no.” Done well, it becomes a mechanism for saying “maybe” or “yes,” depending on the use case, the risk, and the evidence.

There is also substantial work between an AI pilot and a legitimate business result. Enterprise information must become usable by machines that can reason and act on it. That means building ontologies, pipelines, object models, knowledge graphs and relational data stores; connecting systems never designed to work together; and establishing the controls that make machine decisions auditable.

None of that is especially glamorous. All of it takes time.

Which is why waiting for questions from investors, analysts, and boards may be the wrong strategy. By the time those questions arrive, you do not want to be explaining why you haven't started. You want to be showing what you're building, what it does, and what it's worth.

The AI infrastructure industry needs demand. Build your own AI infrastructure to create demand for theirs. Build before they ask.

There is an uncomfortable question confronting the property and casualty insurance industry:

Are we experiencing a temporary backlash, or is insurance entering a new era of fundamental distrust?

Insurance has never been an easy product to love. Consumers pay premiums for something they hope they never need, governed by contracts that can be difficult to understand and fully appreciated only when a loss occurs. The relationship can change dramatically in a single claim. But something feels different today.

Distrust is broader, louder and increasingly connected to public frustration over rising costs, corporate power, artificial intelligence, data collection, climate risk and the perceived behavior of large institutions.

For an industry whose fundamental product is a promise—we will be there when something goes wrong—trust is paramount.

A warning we wrote about before

In December 2024, Stephen Applebaum and I wrote “Broken Trust, Insurance Industry Included.” Our premise was straightforward: the public reaction following the killing of UnitedHealthcare CEO Brian Thompson was an alarm bell for the entire insurance industry, not simply the health insurance sector. We pointed to rising premiums, coverage withdrawals, privacy concerns, widening protection gaps and growing skepticism toward technology as evidence of a broader erosion of confidence.

Nearly two years later, that warning appears increasingly relevant.

The issue is no longer simply whether consumers trust their insurance company. It is whether the public increasingly distrusts the insurance system itself.

The symbol of a much larger problem

The December 2024 killing of Brian Thompson was horrifying. Yet the public reaction to the alleged perpetrator, Luigi Mangione, revealed something the insurance industry should not dismiss as simply an isolated social phenomenon.

Polling following the killing showed unusually strong sympathy for Mangione among younger Americans. The reaction was not really about one individual. It reflected anger toward a system that many people believe has become too powerful, too complicated and too disconnected from the people it serves.

UnitedHealthcare operates primarily in health insurance, not P&C. But to the public, “insurance company” can be a much more important category than the distinctions between health, auto, homeowners or commercial insurance.

That should concern every P&C executive.

Then came the claims controversies

The industry’s claim function has increasingly become the center of the conversation.

In 2025, a U.S. Senate hearing examined insurance claims practices following natural disasters, with executives from Allstate and State Farm appearing alongside policyholders, adjusters and consumer advocates. Allegations that claim evaluations had been manipulated or unfairly reduced received significant attention, although the insurers disputed them.

In June 2026, Oklahoma Attorney General Gentner Drummond filed another lawsuit against State Farm alleging that the insurer’s “Hail Focus Initiative” used undisclosed standards and other practices to reduce payments on hail and wind claims. State Farm disputes the allegations.

Just this week, Los Angeles County announced a lawsuit against State Farm over its handling of claims following the January 2025 Southern California wildfires, alleging delays, underestimation of losses and other improper claims practices. State Farm has disputed the allegations and pointed to billions of dollars in wildfire claims it has paid.

These cases have not established that the insurers acted improperly. Lawsuits contain allegations, not findings of fact. But public trust is rarely determined by the final disposition of a lawsuit – many of which are dismissed, in favor of the insurer or most often amicably settled. Either way, the narrative gets there first.

Profitability makes the narrative more difficult

The industry’s financial performance adds another complication.

P&C insurers have experienced a substantial improvement in profitability as premium growth, stronger underwriting results and investment income have combined to produce record-setting earnings.

Strong insurer profitability is not inherently evidence of consumer mistreatment, yet broad-brushing narratives paint a negative picture to make a point.

Insurance is a capital-intensive business. Insurers need adequate returns to support capital, absorb catastrophe losses, pay claims, invest in technology and remain capable of writing business through difficult cycles.

But consumers don’t necessarily see that complexity. Instead, the narrative can become:

My premium went up. My deductible went up. My claim was denied. In all cases, the insurer made more money.

Whether that conclusion is actuarially accurate is almost beside the point. It is emotionally powerful. And when consumers are already frustrated by inflation and the cost of housing, automobiles and repairs, insurance profitability becomes an easy target.

The “closed without payment” problem

A recent Wall Street Journal analysis of auto insurance claims illustrates the challenge.

The Journal reported that the percentage of certain auto liability and medical claims closed without payment had increased materially over the past decade. Analysis of NAIC data showed that 45% of such claims were closed without payment in 2025, compared with 35% in 2016. That is an important statistic.

But it is also an example of how a technically accurate statistic can create a broader impression that may not tell the whole story.

“Closed without payment” (CWP) does not equate to “wrongfully denied.” Claims can close without payment for numerous reasons, including coverage issues, duplicate claims, fraud, liability determinations or other factors. In fact, CWP rates are a singular gauge for purposes such as monitoring claim productivity and should not be isolated from average claim payments, reserve accuracy, re-open rates and other metrics to assess payments. Certainly not to accurately judge claim settlement fairness.

The industry’s response made an important distinction: the increase identified by the Journal was concentrated in liability and medical claims, while physical-damage claims were being paid at essentially the same rate as a decade ago.

A technically correct defense can still fail as a trust strategy.

If consumers hear “nearly half of claims aren’t being paid,” a subsequent explanation about claim categories, coverage triggers and statistical methodology may never overcome the initial impression.

The industry needs to communicate in a way that makes the underlying economics and claims experience understandable—not simply defensible.

Insurance has always had a trust problem

None of this is entirely new.

Insurance has several structural characteristics that make trust difficult. It is intangible, complex and often mandatory. The customer pays first and receives value later—sometimes years later. And when the customer most needs the product, the insurer must determine whether and how much it will pay, which can easily create friction.

A policyholder sees a damaged roof. An insurer sees a contract, causation, exclusions, depreciation, replacement cost, engineering evidence, estimating methodology, fraud indicators and applicable regulation. Both may believe they are acting reasonably. But one side has generally spent decades learning how the system works. That asymmetry creates distrust.

Four forces amplifying the problem

Affordability: Consumers have experienced dramatic increases in home and auto premiums in many markets. Those increases have legitimate drivers—repair costs, medical costs, litigation, catastrophe losses, reinsurance, inflation and changing risk. But consumers experience one part of the equation: the bill.

Claims: The claim is the industry’s moment of truth. Every difficult claim creates a potential advocate—or detractor. Social media can now turn an individual dispute into a national story almost instantly.

AI and data: AI can improve claims accuracy, detect fraud, accelerate settlement and reduce administrative expense. But from a consumer’s perspective, AI can also sound like: a computer decided not to pay me. The broader public debate over AI, privacy, data centers and technology companies suggests this skepticism will grow.

Distrust of institutions: Insurance is not operating in isolation. Banks, pharmaceutical companies, technology companies, healthcare organizations and other large institutions are experiencing versions of the same credibility challenge. Insurance is particularly vulnerable because its product is fundamentally built on trust.

The industry’s response

There are reasons for optimism. Some insurers recognize that restoring trust requires more than advertising.

Farmers has introduced a Coverage Review initiative designed to help consumers better understand what their policies do and don’t cover. Importantly, the service is available even to consumers insured elsewhere. This attacks the trust problem upstream by not waiting for a claim to explain the policy. Time will tell if this is simply clever marketing or possibly a new way to encourage discussions that consumers tend to avoid.

State Farm has also taken steps to return value to customers, including a $5 billion cash-back dividend for qualifying auto customers, while reducing auto rates in several markets. Progressive has returned excess profits to eligible Florida personal auto policyholders, while USAA has also reduced Florida auto rates and returned value to its members.

Rate increases are easing in several markets after several years of extraordinary increases. These actions matter. But trust is not restored by one dividend, one advertising campaign or one rate decrease. It is restored through repeated evidence that the organization behaves consistently with the promise it makes.

The ecosystem has a role to play

This is not solely a carrier problem.

Solution providers, claims technology companies, TPAs, adjusters, brokers, agents, consultants and analysts all influence the customer’s perception of insurance. Every automated decision and claims estimate. Every AI recommendation and vendor interaction. And each confusing communication. They all become part of the insurance brand.

That means the industry’s technology agenda cannot simply be about doing things faster and cheaper.

It also has to be about doing things in a way customers perceive as fair, understandable and trustworthy.

Instead of asking only, Can AI make this decision?

We should ask, Can the customer understand why this decision was made?

Instead of asking, Can we automate this claims process?

We should ask, Where does a human being add trust and judgment?

And instead of asking only, Can we reduce claims expense?

We should ask, Can we reduce expense without damaging the customer’s perception of fairness?

The uncomfortable opportunity

The industry should not respond to today’s distrust by simply defending itself more aggressively.

Some criticism is unfair, and some statistics are presented without sufficient context. Some claims disputes are considerably more complicated than the headlines suggest. And insurers are confronting genuine challenges from catastrophe risk, inflation, litigation, repair costs and capital requirements.

All of that is true. But another truth is equally important:

People don’t trust institutions simply because the institution can prove it is technically correct.

Trust comes from transparency, consistency, empathy and evidence. The industry has an opportunity to use the same technology driving transformation to address the trust problem. AI can make insurance more automated—but also more transparent.

Data can make underwriting more sophisticated—but also help consumers understand their risk.

Claims analytics can reduce leakage—but also identify where customers experience unnecessary friction.

And stronger profitability can provide the capital to invest in better products, better experiences and better claims operations.

The real question

Insurance does not need to become universally loved.

It needs to remain credible.

When someone buys homeowners insurance, auto insurance or commercial coverage, they are not really buying a policy document. They are buying confidence that when something goes wrong, someone will stand behind the promise.

That promise is the product.

The insurance industry has a trust deficit. The question is whether carriers and the broader ecosystem will treat that deficit as a public-relations problem—or recognize it as a structural business problem, a technology problem, a claims problem and ultimately a product problem.

The industry has spent enormous amounts of money making insurance more sophisticated. Perhaps the next investment should be making it easier to believe.

The policy isn’t the product. Trust is.

Sabine VanderLinden, a keen observer of venture capital in insurance, recently wrote a startling sentence: "50% of every insurtech dollar invested in the first six months of 2026 went to companies that will never sell you a policy."

That number is a far cry from what proponents expected when the insurtech wave began a decade-plus ago. At that point, predictions were rife that some Big Tech company such as Google or Amazon would do a cannonball into insurance and change the game entirely or at least that some startup would figure out a way to leapfrog incumbent carriers and make them play catch-up. 

But VanderLinden's analysis provides a guidepost about where investment in insurtechs is today and where I think it's going.

Let's have a look. 

Artificial intelligence still takes up the vast majority of the headspace for most incumbents as they try to innovate. They're spending enormous effort to look for efficiencies in processing claims, in underwriting, in sales, and so on. They're also experimenting with ways to set up autonomous agents and to coordinate their actions while staying within crucial guardrails.

VanderLinden's analysis found significant funding for AI-based insurance startups, too, but they were just the third biggest category in the first half of the year. First was: "risk data. Satellites, sensors, and driving behavior.... This is happening because proprietary risk data has become the scarcest asset in the value chain. Models are abundant. Compute is abundant. Ground truth is not. The ventures that own a persistent, hard-to-replicate view of physical risk are commanding late-stage checks."

She highlights ICEYE, which raised a $500 million Series F "to expand its radar satellite constellation for natural catastrophe monitoring," and Cambridge Mobile Telematics, which raised $350 million for its insights into driving behavior. She also mentions mea platform ($50M), Fulcrum ($25M) and Axle ($17.5M).

Her observation certainly dovetails with what I'm seeing. I've long argued that the surest insurtech winners would be what we called "arms dealers" during the early internet days. Just as Sun Microsystems made bank by selling servers to startups, whether they thrived or, more likely, crashed and burned, companies that developed important, proprietary data sources were always likely to thrive. 

And there have been impressive advances in risk data, as evidenced by any number of articles we've published recently at ITL. This interview I did with Eagleview lays out a vision for how aerial views of properties will enable continual monitoring of property risks. This piece, from Nearmap, describes how the condition of roofs and other aspects of properties can be tracked long before a claim surfaces. This describes advances in "hyperlocal" weather intelligence. This explains how catastrophe modeling is moving beyond static pictures of disasters and toward images that show how floods, wildfires, etc. develop over time. We've also published on new ways to track maintenance records of commercial properties to better understand the likelihood of a claim, to monitor for the next pandemic, and so on. 

VanderLinden says the second biggest category of venture investment was in digital-first insurers and MGAs and offers a key insight: "Not one of them is a generalist." She writes:

"Alan raised $116M for digital health in France. Corgi closed a $106M Series B insuring technology companies. Counterpart took $50M for small-business liability, Shepherd $42M for construction, Lassie $75M for pet, Zego $28M for gig drivers. Stoïk and Mitigata both raised for cyber, on two different continents.... The funded insurance provider of 2026 is specific, defensible, and priced for its niche."

Third was AI: "$216M went to AI-led claims, underwriting, and operations automation.... These ventures do not compete with insurers. They sell digital labor to them. Claims handling, prior authorizations, underwriting triage, document verification: the workflows where a human-agent ratio can shift fastest and the savings land on the P&L within quarters, not years."

The insurtechs that went after incumbents head-on -- notably Lemonade, Hippo and Root -- are still around and seem to have stabilized after years of struggle but are way down from their peaks in early 2021. Lemonade shares are off some 65%, Root is down 85%, and Hippo has fallen 90% even as the S&P 500 has nearly doubled. So I continue to believe that the sorts of "arms merchants" VanderLinden describes are the future of insurtech.

Cheers,

Paul

P.S. If you'll permit me a proud papa moment....

My older daughter made her debut in the Wall Street Journal over the weekend. She trekked the 500-mile Camino de Santiago in Spain this spring and wrote an essay [free link] about the trip that has generated some 500 comments and emails and spent some time on the "most popular" list. It's a splendid piece. I'm delighted for her.

I also love that the Carroll family is now on its third generation at what we joke is the family business. My father spent a year at the WSJ. My younger brother and I combined for 59 years. Now Shannon....

The average consumer views insurance as a reactive product. A pipe bursts. A fire starts. They file a claim, and their carrier helps them to recover and rebuild.

That captures the core of the insurance value proposition, but it overlooks a key element: the role insurers play in preventing losses before they happen. This is critically important. Few homeowners realize there are simple, effective steps they can take to protect their homes from these losses.

As customer expectations evolve and preventable losses continue to impact homeowners, insurers across the industry are beginning to rethink their role — not simply as organizations that pay covered claims but as organizations that help customers avoid losses altogether.

Recognizing this shift, we’ve expanded our portfolio of risk management tools and resources — including two smart sensors, Ting (electrical fire prevention) and LeakBot (leak detection) — to help policyholders[1] identify hidden risks and intervene before losses occur. 

“Helping customers recover after a loss will always be at the heart of what we do,” says Corey Vigliucci, AVP of sales and underwriting for Westfield Personal Lines. “But if we can help prevent that loss from happening in the first place, that’s an even better outcome. That’s why we’re investing in practical solutions that help homeowners and farm owners identify hidden risks before they become losses. It’s another way we’re helping protect what matters most.[2]”

Here’s what that looks like in action.

Ting: Preventing electrical fires

Every 10 minutes, a family in the United States is impacted by an electrical fire. The average electrical fire claim costs approximately $215,000, according to Triple-I, and that’s only the financial damage. The emotional devastation homeowners face when losing their home to a fire is immeasurable.

To help homeowners mitigate the risk of devastating electrical fires, we worked with Ting Labs to offer Ting, its electrical fire prevention system, to all its eligible personal lines and farm insurance policyholders.

Ting detects hidden electrical hazards before they escalate into fires. The system combines a smart sensor, a mobile app, an advanced signal analysis and a fire safety team that works with homeowners in real time to help identify and mitigate risks.

Simple by design, the smart sensor plugs into any standard outlet and uses advanced technology to identify electrical arcing, faulty wiring, failing outlets and other hidden hazards that homeowners might never detect.

On average, Ting sends fire hazard alerts to approximately one in 60 homeowners each year. About one in 27 of those alerts would have resulted in a fire if the hazard had remained undetected.

The value extends beyond homeowners. These tools also help equip agents to have more proactive risk management conversations with customers.

“This investment also creates meaningful value for our agents by equipping them to have more proactive risk management conversations with customers,” said Dave Ruppel, AVP of sales and underwriting for Westfield Agribusiness. “By identifying potential issues before a loss occurs, agencies can reinforce their role as trusted advisors, deepen customer relationships and help improve long-term customer retention.”

Matthew Boyert, CEO and founder of Boyert Insurance Group, experienced the benefits of Ting firsthand. One day, while meeting with a client, Boyert received a Ting alert on his phone that read, “Fire detected!” 

“I rushed home with my heart beating at 100 miles an hour,” he recalls. He immediately called the Ting support team and learned the alert was for a potential fire hazard.

When Boyert arrived home, a Ting representative helped him isolate the issue, which turned out to be an electrical outlet with loose wiring that was actively arcing.

“If I didn’t have that device, I would not have known there was arcing that could have caused a catastrophic fire,” Boyert reflects. “We could have lost our house, our memories, everything.”

Stories like this resonate with homeowners and help reinforce the importance of proactive risk management.

Matthew Mangus, president of Miller’s Insurance Agency, has seen what happens when electrical fire hazards go undetected. In the past two years, he has seen two clients lose their homes in fires caused by electrical failures.

“I’ve met with clients two days after their homes burned down,” he reflects. “Seeing their mindset as they figure out what to do next is heartbreaking.”

Since launching its Ting offering in May 2024, we’ve enrolled more than 21,000 Westfield customers in the program. During that time, we’ve identified nearly 200 potential “saves” across both electrical and utility fire hazards, including panel failures, faulty outlets and wiring issues.

LeakBot: Tackling hidden water losses

Although fire presents one of the most disastrous risks, water damage is among the most common and costly. Non-weather water damage, such as plumbing failures, appliance leaks or burst pipes, is the second leading cause of homeowners insurance claims in the U.S., accounting for approximately 23%-28% of all claims, according to Consumer Affairs.

Triple-I reports the average non-weather water damage claim is approximately $15,400, with hidden leaks behind walls or beneath floors often triggering the worst losses.

That’s where LeakBot, a smart water leak detection solution, comes in. The technology helps homeowners identify non-weather-related leaks, often before any visible signs of damage emerge. Earlier this year, we began offering LeakBot to eligible policyholders in Ohio, Indiana and Pennsylvania. In just a short time, more than 5,000 homeowners have enrolled.

When a leak is detected, homeowners gain access to a support team and specially trained plumbers who help diagnose and resolve the problem before it escalates into a major claim.

The technology’s simplicity is part of its appeal. LeakBot installs in minutes by clipping onto a home’s main water pipe, with no tools or plumbing expertise needed. Once installed, it quietly monitors the home in the background.

For agents, that simplicity is a major advantage. It makes it easier to introduce homeowners to risk prevention and demonstrate added value beyond the policy itself.

According to Consumer Affairs, fewer than 20% of homeowners take steps to avoid leaks, such as plumbing inspections or installing leak detection systems, despite approximately 65% of water damage incidents being considered preventable. By offering a simple tool like LeakBot, agents are well positioned to help change those statistics.

“I’m telling my Westfield customers about LeakBot, and there’s a lot of interest,” says Boyert. “There are not many carriers that offer one, let alone two, preventive risk management devices free of charge to their insureds. Kudos to Westfield for that.”

The agent opportunity: Moving beyond the policy

For independent agents, preemptive risk management tools like Ting and LeakBot transform the conversation from transactional to advisory, creating more frequent, meaningful touchpoints with customers, and reshape how they deliver value.

Data plays an important role in making those risks tangible. When customers understand how common and costly these losses are, prevention becomes easier to appreciate.

“Insurance is an intangible product. You’re basically selling a promise,” says Boyert. “Tools like this give us something tangible that we can offer to clients to give them additional peace of mind.”

Agencies can strengthen relationships and build trust over time by introducing solutions that actively help protect customers. By equipping agencies with carrier-backed risk management solutions, insurers are enabling agents to go beyond transactional interactions and position themselves as long-term advisors.

“It’s a great retention tool,” says Mangus. “As an agency owner, I’m always interested in two elements. Can this help our clients, and will it help with retention? With both, that’s a win-win.”

Customers who embrace risk protection often become more loyal to both the agency and the carrier. “The customers who recognize the value these solutions provide — and understand that Westfield introduced them to the concept — often become more loyal to both Westfield and, by extension, Miller’s Insurance Agency,” Mangus explains.

By equipping agents with practical risk-prevention tools and resources, we’re helping redefine the role agents play — from policy providers to trusted risk advisors. As personal lines continue to evolve, carriers that help customers prevent losses, not just recover from them, will help define the next generation of insurance value.

[1] Customers must have an eligible homeowners, WesPak®, WesPak Estate®, or farmowners policy with an owner-occupied dwelling to claim Ting. LeakBot devices are only available for homeowners policyholders in Ohio, Indiana and Pennsylvania.

[1] Please see footnote 1.

About the author:

Casey Burke is Director of Standard Lines Marketing at Westfield, where he helps shape marketing strategies that support customers, independent agents and the evolving needs of the insurance marketplace. He brings more than 20 years of marketing and sales experience, including more than a decade in the insurance industry. Throughout his career, Casey has focused on connecting customer insights, business strategy and practical solutions to drive growth, strengthen relationships and deliver meaningful value

Insurers and banks have invested significant effort in securing internal employee and customer access. Internal access now uses phishing-resistant multi-factor authentication (MFA), whereas consumer and policyholder-facing applications have shifted toward passkeys and passwordless access. It is usually the middle of this stack that is weak: MGAs, brokers, reinsurers, claims vendors, auditors, consultants, and external contractors all log into carrier and bank infrastructure under significantly less stringent conditions.

There are numerous examples of third-party access to financial services infrastructure based on outdated authentication methods, common passwords, manual user creation, and a general lack of governance controls. The exposure to that risk increases rapidly as partner ecosystems grow and cloud integration deepens, and insurance carriers, with their dense networks of agents, brokers, and claims partners, are as exposed as any bank.

That gap is becoming harder to ignore because the identity surface itself is expanding rapidly. Research from Enterprise Strategy Group (ESG), commissioned by Thales, found that 74% of BFSI organizations, spanning banking, insurance, and financial services, report third-party identities growing faster than employee identities, with third-party identity volumes projected to grow 37% over the next 12 months. At the same time, 89% say they already have a prioritized strategy to modernize identity solutions used by contractors and partners.

The question is: what standard should financial institutions adopt?

The Partner Access Model is Already Failing at Scale

The operational signals emerging from partner identity environments increasingly look like security warnings.

The 2026 Thales Digital Trust Index found that 92% of partner users experienced access issues with external partner systems during the last 12 months. Only 22% received login access immediately when starting with a new partner relationship. More concerning, 66% admitted to sharing or borrowing credentials, with 53% blaming slow official access processes.

These figures are often viewed as productivity issues. In reality, they highlight an identity control model under operational stress. Shared credentials eliminate traceability, making it difficult to distinguish between legitimate and compromised activity.

The same report found that 71% of partner users were worried about maintaining access they no longer needed, and only 19% said access changes were implemented as soon as responsibilities changed. This joiner-mover-leaver problem extends beyond the enterprise perimeter.

ESG’s BFSI research reinforces the point. Lifecycle management across disconnected systems, compliance reporting across identity boundaries, and deprovisioning identities when no longer needed were all ranked among the top third-party identity and access management (IAM) challenges by respondents.

Governance gaps are operational, structural, and currently exist at scale.

Third-Party Access Now Maps Directly to the Attack Surface

When the identity trends map to attack data, the security concerns become more evident. The 2026 Thales Data Threat Report: Financial Services Edition found that, according to 70% of those surveyed, the top emerging attack technique targeting cloud infrastructure in the financial sector is credential theft and the misuse of secrets.

Vulnerabilities originating from third parties, including external code and APIs, ranked second at 65%. Third-party vendor networks also ranked among the top attack targets for financial services organizations. Businesses are building connected SaaS ecosystems, fintech integrations, outsourced capabilities, and cloud processes even as credential-based attacks continue to skyrocket.

Yet the authentication layer protecting many of those external connections is inconsistent, which fuels risk because attackers don’t distinguish between employee and partner credentials.

The threat environment further complicates the issue. According to the Thales Bad Bot Report for 2026, the financial services sector accounted for 46% of account takeovers in 2025, even though it makes up just 24% of all bot attacks worldwide. In addition, there has been a 70% increase in account takeovers from July 2024 to July 2025.

Banks understand they need phishing-resistant authentication internally, and the same logic should apply to partner ecosystems.

Why FIDO Fits the Partner Authentication Problem

The value of fast identity online (FIDO) in partner access scenarios is not simply stronger MFA. It is the removal of the shared secret itself.

Passwords, OTPs, and reusable credentials create a transferable authentication artifact that can be stolen, replayed, borrowed, or phished. FIDO-based authentication replaces that with cryptographic key pairs tied to the user, device, and relying party domain. There is nothing to steal, share, or replay.

For banks that rarely control the identity infrastructure their partners use, FIDO's open standard design means strong authentication can extend beyond the corporate IAM perimeter without requiring partners to adopt the bank's full identity stack.

Not Every Partner Requires the Same Assurance Level

Partner authentication is not a single-tier problem. The right credential depends on what the partner can access and the consequences of a compromise.

For lower-risk external relationships, such as broad partner networks, suppliers, and fintech integrations where the priority is reducing friction and eliminating shared passwords, synced passkeys operating at AAL2 are a practical starting point. They raise the authentication bar without imposing hardware requirements across a diverse and distributed partner base.

For higher-risk access, device-bound hardware security keys at AAL3 are the appropriate standard. Auditors in controlled environments, privileged contractors, external administrators, and partners with direct access to regulated financial data are scenarios in which the bank's compliance posture is contingent on the partner's authentication holding. Synced passkeys, which can move between devices, do not provide that assurance.

Matching credential strength to access risk is not a novel principle. NIST SP 800-63B formalizes it through the AAL2 and AAL3 assurance levels that already underpin most phishing-resistant MFA frameworks.

Authentication Alone Will Not Solve the Governance Problem

Deploying FIDO in partner ecosystems without addressing lifecycle management extends the existing vulnerabilities rather than closing them. Delayed provisioning increases the likelihood of credential reuse; absent deprovisioning, access remains in place long after it is needed. The 2026 Thales Digital Trust Index found that only 19% of partner users see access changes implemented immediately after responsibilities change, and 66% retain access they no longer need.

Banks still need automated provisioning, entitlement management, and revocation across siloed systems — and the regulatory pressure to get this right is building. DORA, NIS2, and PSD2 all treat third-party access management as an institutional liability, not a partner problem. The ESG research found compliance and regulatory mandates were the primary driver of third-party identity modernization for 46% of BFSI respondents.

Choosing the Right FIDO Enrollment Model

Large-scale FIDO key enrollment typically follows one of three models.

In admin-driven enrollment, IT centrally configures and issues security keys before delivery, giving full control over credentials and setup policies. This is well-suited to large, time-sensitive deployments.

Self-service enrollment lets users configure their own key through a portal within defined policy parameters, reducing IT overhead but requiring a well-designed process and investment in user communications.

Vendor-managed enrollment goes furthest: keys are pre-registered before shipping, so recipients receive a device that is already enrolled and ready to use, with no IT involvement at the point of receipt.

A large automotive organization used this third model to deploy FIDO security keys to employees and contractors at scale. Using a centralized authenticator lifecycle management platform, it bulk-enrolled security keys into its internal identity providers before distribution, then shipped pre-registered keys directly to contractors and partners. The result was a faster rollout and a consistent authentication experience across a distributed user base, without placing the enrollment burden on internal IT teams.

The Next Step in Identity Security

FInancial institutions that treat partner authentication as a downstream problem will find it becomes an immediate one. Credential data theft, access failure rates, and the regulatory trajectory all point in the same direction. Phishing-resistant authentication is already the standard for employees. Extending it to partner ecosystems completes the strategy.

Two homes on the same street can experience completely different outcomes from the same storm. One loses its roof and siding to wind-driven hail, while another just blocks away escapes with little more than cosmetic damage. For insurers, those stark differences create one of the industry's most difficult operational challenges: determining exactly what happened at a specific property, often within hours of the storm.

Unlike hurricanes that leave broad swaths of destruction, or floods that generally follow predictable topography, severe convective storms — including tornadoes, hail, damaging straight-line winds, and severe thunderstorms — produce highly localized, rapidly evolving damage that defies broad assumptions. Every claim requires a more precise understanding of where a storm struck, how it behaved, and what conditions a particular property actually experienced.

As another active tornado season comes to a close, insurers are confronting a reality that extends well beyond this year's losses. While severe convective storm losses exceeded $20 billion for the 11th consecutive year, they remained below both the five- and 10-year averages. At the same time, states like Illinois experienced a record-breaking season, with a preliminary estimate of 220 tornadoes so far in 2026, reinforcing widespread media coverage and a heightened perception of risk among homeowners and businesses alike.

As severe convective storms become an increasingly persistent source of insured losses, competitive advantage will depend less on understanding regional weather patterns and more on translating property-level weather intelligence into faster decisions, smarter claims handling, and stronger customer trust.

From Regional Forecasts to Property-Level Intelligence

Severe convective storms often produce remarkably uneven damage, and those sharp variations complicate nearly every stage of the insurance lifecycle.

Underwriters need to evaluate risk with greater geographic precision. Claims teams must determine exactly which properties experienced effects like damaging winds, hail, or tornado impacts. Catastrophe response teams have to deploy adjusters where they're actually needed instead of relying on county-wide assumptions. Even customer communications become more nuanced when two policyholders living minutes apart experience dramatically different outcomes.

Traditional catastrophe models remain essential, but they weren't built to answer property-level questions on their own. Meeting that challenge requires a more granular view of the weather.

Advances in radar, satellite imagery, lightning detection, and high-density weather observation networks now give insurers a far more detailed picture of developing storms than was possible only a few years ago. Combined with convective-allowing models capable of forecasting storms at kilometer-scale resolution, these technologies help insurers move beyond generalized forecasts to understand how a storm is likely to affect individual communities down to the street.

This level of precision transforms insurers’ operational decision-making.

Instead of waiting on claims to arrive, carriers can identify areas most likely to experience significant hail or tornado damage, position field adjusters in advance, prepare call centers for increased demand, and communicate with policyholders before the first inspection is scheduled.

The advantage is faster, more informed action.

Why Every Minute Matters

During severe convective storm outbreaks, timing can significantly influence both operational costs and customer experience.

Receiving reliable weather intelligence just 30 minutes before a major hail event can give insurers enough time to staff call centers, mobilize claims personnel, and begin communicating with policyholders before call volumes surge.

That kind of lead time can make a meaningful difference during events like the record-breaking 6-inch hailstones that struck the heavily populated Kankakee, Ill., area on March 10, 2026, when insurers can become inundated with claim spikes and overwhelmed call queues within minutes. Near-real-time radar updates and rapidly refreshing weather observations allow operational teams to adjust as storms evolve, reducing delays and improving response times when customers need support most.

Because warnings often involve life-threatening situations, insurers appropriately rely on official warnings issued by the National Weather Service rather than issuing independent alerts. Their opportunity lies elsewhere: helping policyholders understand changing conditions in the hours leading up to severe weather and rapidly mapping paths afterward to prioritize claims response and inspection resources.

The objective isn't replacing public safety messaging. That is still very much a fundamental part of the equation. Instead, it's to deliver faster, more informed service when every minute counts.

Smarter Claims Through Better Weather Intelligence

The true value of hyperlocal weather intelligence becomes clear after the storm passes.

Historically, claims investigations often relied on manual inspections across entire affected areas. Today, combining hyperlocal weather intelligence with policyholder data allows insurers to prioritize inspections where uncertainty is highest while accelerating straightforward claims supported by high-confidence weather evidence.

This targeted approach improves efficiency without sacrificing accuracy. Instead of dispatching adjusters to every reported loss, insurers can focus experienced personnel on the most complex claims while using verified weather intelligence to streamline simpler cases. The result is faster settlements, lower operational costs, and a better experience for policyholders recovering from severe weather.

The same intelligence also strengthens claims verification and fraud detection by providing objective evidence of conditions at a specific location. When weather observations, radar signatures, and storm reports align with reported damage, insurers gain greater confidence in claims decisions. When they don't, insurers can investigate further before making unnecessary payments.

Artificial intelligence is making these insights even more actionable. Instead of relying on broad alerts, insurers can tailor communication based on individual property characteristics and prior customer interactions.

A homeowner with outdoor furniture, solar panels, or trees close enough to threaten nearby houses may receive different preparedness guidance than another policyholder nearby. By making communication more relevant, insurers can encourage risk reduction, reduce alert fatigue, and strengthen trust before severe weather strikes.

Building Trust in an Era of Localized Risk

This year's tornado season shows a broader transformation taking place across the insurance industry.

Although severe convective storm losses remained below recent averages, public attention surrounding tornado outbreaks reinforced a heightened sense of risk. That creates both a challenge and an opportunity for insurers.

Policyholders expect faster communication, quicker claims decisions, and greater transparency about how coverage decisions are made. Meeting those expectations requires more than better catastrophe models. It requires turning property-level weather intelligence into faster operations, clearer communication, and more confident decision-making.

As severe convective storms continue to reshape the insurance landscape, competitive advantage will belong to carriers that combine scientific precision with operational agility. Every storm creates thousands of property-level decisions, and the ability to make them quickly, accurately, and confidently is becoming one of the defining capabilities of modern insurance.

Key Takeaways

• Recent outbreaks of hantavirus and Ebola demonstrate that serious infectious disease events can create significant public health challenges without necessarily posing a high risk of becoming global pandemics.
• Strengthening public health systems and maintaining informed vigilance are essential to managing future infectious disease risks.
• The next global health threat may emerge from an unexpected source, making sustained investment in preparedness, surveillance, and response capabilities more important than focusing on any single pathogen.

Executive summary

Recent outbreaks of Andes hantavirus and Bundibugyo Ebola have renewed attention on pandemic risk, but neither currently appears likely to cause sustained global spread. Their main significance lies in what they reveal about pandemic preparedness: the importance of rapid detection, effective contact tracing, international coordination, and timely countermeasures.

While disease outbreak severity warrants attention, pandemic potential depends more on efficient human-to-human transmission, pre-symptomatic or respiratory spread, population immunity, and the ability of health systems to respond quickly. Therefore, these recent outbreaks are best understood not as signals of an imminent pandemic, but as important reminders to remain vigilant, balanced, and guided by the full body of evidence.

The hantavirus outbreak: A local exposure becomes an international public health exercise

The hantavirus outbreak, linked to expedition cruise ship M/V Hondius, illustrates how a rare infection can quickly become a major international containment challenge. In this event, Andes virus infection was first identified more than three weeks after the first death. Epidemiological investigation and viral sequencing suggested that the index patient likely acquired the infection during travel in South America, including areas of Argentina and Chile where the Andes virus is endemic. Because the case was detected in the context of cruise ship travel, passengers and high-risk contacts had already dispersed across multiple countries before the virus was identified.

The cruise ship setting inevitably recalled memories of the early COVID-19 outbreaks at sea, when ships became symbols of uncertainty, containment challenges, and global spread. Biologically, Andes virus is very different from SARS-CoV-2, but the echoes were familiar: delayed recognition, international passenger dispersal, and the need for rapid cross-border coordination.

This does not make Andes hantavirus a likely pandemic pathogen. Its human-to-human transmission remains limited and requires close contact with respiratory secretions. This outbreak resulted in 13 infections and three deaths, yielding an outbreak-specific case fatality rate (CFR) of approximately 23%. The 42-day follow-up period for contacts was completed with no additional secondary cases detected, and the World Health Organization (WHO) officially declared the outbreak over on July 2, 2026.

The event illustrates how global mobility can transform a small outbreak into a complex public health operation. Even when the biological risk of sustained spread is low, delayed recognition, international travel, and long monitoring periods can place substantial demands on surveillance, communication, and coordination systems.

The Ebola disease outbreak: A reminder that surveillance and rapid detection matter

The significance of the continuing Bundibugyo ebolavirus outbreak in the Democratic Republic of the Congo, with associated cases and transmission previously reported in Uganda, should not be underestimated. This outbreak has expanded at an exceptional pace and is now the second-largest on record, with a CFR of approximately 44% as of July 30, 2026. The WHO has designated the outbreak a public health emergency of international concern (PHEIC), reflecting both its severity and the need for coordinated international action. Unlike the Andes hantavirus outbreak, however, it highlights a different set of containment challenges: the consequences of limited surveillance, contact tracing, and diagnostic capacity.

The outbreak response is further complicated because it is caused by a rare species of Ebola without an approved vaccine and the epicenter is an area affected by conflict. Bundibugyo virus is a less common Ebola virus species, and many existing diagnostic tests, vaccines, and treatment strategies historically have been developed with other Ebola virus types in mind. As a result, the outbreak likely went undetected for months, delaying recognition and response.

Ebola outbreaks demand urgent attention because of their potential for substantial mortality and capacity to disrupt and overwhelm health systems. But disease severity alone does not determine pandemic potential. Ebola generally spreads through direct contact with infectious bodily fluids and is most contagious once symptoms are present, especially during severe illness. These characteristics make sustained global spread much less likely than with a respiratory virus that transmits efficiently before symptoms develop.

The primary concern is not that Ebola will become the next global pandemic but that outbreaks can expand rapidly when they occur in settings where conflict, humanitarian crises, strained healthcare infrastructure, or gaps in diagnostics, contact tracing, and countermeasures hinder early detection and control.

What these outbreaks remind us about pandemic risk

Pandemic risk is not driven by a single feature. The greatest risk arises when several factors merge: a novel pathogen, meaningful disease severity, efficient human-to-human transmission, and low population immunity. Transmissibility is especially important. A virus that spreads through respiratory droplets or aerosols, particularly before symptoms appear, is generally more difficult to contain than one that requires close contact after symptom onset.

This is why the pandemic potential of Ebola and Andes hantavirus remains low in the current context, despite their seriousness. In contrast, influenza viruses remain a more persistent pandemic concern because they can spread efficiently between people, transmit before symptoms are recognized, and evolve or reassort into new strains. Avian influenza remains a risk to monitor closely, not because it currently spreads efficiently between humans, but because adaptation could change that risk profile.

Recent evidence adds nuance to the avian influenza risk discussion. Windborne spread of H5N1 between poultry farms via virus-contaminated material from infected bird droppings cannot be ruled out, although it remains difficult to prove and does not necessarily imply efficient airborne transmission between humans. Separately, asymptomatic human H5N1 infections have been reported, albeit infrequently and often identified through enhanced surveillance or household contact investigations. These findings do not change the current assessment that sustained human-to-human transmission remains limited, but they reinforce why avian influenza requires careful surveillance, especially for changes in transmission dynamics.

https://public.flourish.studio/visualisation/29931603/

This comparison highlights why severity alone is not enough to determine pandemic potential.

The recent hantavirus and Ebola outbreaks particularly draw attention to the system-level drivers of pandemic risk, rather than viral characteristics: global connectivity, weak early detection and response, and limited countermeasures.

Global travel can move exposed individuals across borders before an outbreak is recognized. Delays in diagnosis and containment increase uncertainty and response complexity. Limited availability of pathogen-specific tests, vaccines, and treatments increases vulnerability, even when the pathogen itself has limited pandemic potential.

Three key lessons

1. Travel and ecological change continue to reshape infectious disease risk. Global travel, trade, ecotourism, agricultural expansion, and increasing human contact with wildlife all create more opportunities for zoonotic spillover and cross-border spread. Many spillover events remain dead ends, but repeated opportunities for exposure – sometimes described as viral chatter – give pathogens more chances to adapt.
2. Pathogen disease severity should not be confused with pandemic potential. A pathogen can be highly lethal but poorly suited for sustained global spread. Conversely, a pathogen with a lower CFR but efficient respiratory transmission can have far greater population impact. For risk assessment, the key question is not simply “How dangerous is this virus?” but “How easily can it spread, when does transmission occur, and what level of immunity and countermeasures exist?”
3. Preparedness is shaped by speed. The rate of detection, sequencing, reporting, contact tracing, clinical response, and countermeasure deployment can determine whether a localized outbreak remains contained or becomes a wider crisis. Even when no pandemic emerges, delayed recognition can still cause avoidable morbidity, mortality, operational strain, and public anxiety.

Conclusion: A test of preparedness, not a prelude to a pandemic

The Ebola outbreak in the Democratic Republic of the Congo and Uganda and the recent Andes hantavirus outbreak are serious public health events that deserve close attention. Yet despite their severity, neither currently exhibits the transmission characteristics typically associated with sustained global pandemic spread. While both pathogens can cause severe disease and significant mortality, their epidemiological profiles make widespread worldwide transmission unlikely in the current context.

That does not diminish their importance. These outbreaks are reminders that emerging infectious threats continue to test health systems, surveillance capacity, diagnostic readiness, and international coordination. The key takeaway is one of informed vigilance rather than alarm. Pandemic preparedness is not only about identifying the pathogen most likely to cause the next global crisis but also about strengthening the systems that allow us to detect, interpret, contain, and respond to infectious threats before they escalate.

References

1. https://www.ecdc.europa.eu/en/infectious-disease-topics/hantavirus-infection/surveillance-and-updates/questions-answers-outbreak
2. https://www.sciencedirect.com/science/article/pii/S2590170226001822
3. https://www.who.int/emergencies/disease-outbreak-news/item/2026-DON614
4. https://www.nejm.org/doi/full/10.1056/NEJMra2607216
5. https://www.sciencedirect.com/science/article/pii/S1755436523000403
6. https://www.cidrap.umn.edu/avian-influenza-bird-flu/can-avian-flu-spread-wind-cant-be-ruled-out-experts-say
7. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2840680
8. https://www.who.int/publications/m/item/covid-19-global-risk-assessment--version-10

A humanoid robot ran 100 meters in 9.39 seconds at the World Humanoid Robot Games on Saturday, bettering the human record of 9.58 seconds set by Usain Bolt. Another ran the 400 meters in 38.16 seconds, almost five seconds faster than the human best. Still another jumped almost nine-and-a-half feet into the air — nine-and-a-half-feet! The human high jump record is a hair over eight feet.

But the winner of the 100m race crashed into the padding at the end of the track, reeled backward for maybe 10 meters, then fell and snapped in the middle, sending sparks everywhere. 

That image, on top of the impressive speed, the jumping and the other abilities demonstrated at the games in Beijing, strikes me as a pretty good summary of where humanoid robots stand today. Once you sort through all the hype (from Elon Musk, among many others), you see tremendous progress in specialized functions, but you also see that humanoid robots won't show up broadly in factories or homes — or the insurance policies that cover them — for many years.

Let's have a look.

Frankly, I've never understood the need for robots to be humanoid. I mean, if you want to really go fast for 100 meters, you should put a little electric car in the lane on the track. One of those babies will get to 60mph in the first 50 meters  — forget Usain Bolt's top speed of a bit under 28mph. The whole race would take maybe three seconds. If you want a robot to set a high jump record, there are these things called rockets.

And specialized robots are already doing great work in a host of settings, as this New York Times article describes in detail:

"Autonomous carts have largely replaced forklifts for moving materials around [a Hyundai] plant. Four-legged robots that look like dogs search for flaws by peering under car bodies. Flat, wheeled robots the size of queen beds slide under Ioniq 5 or Ioniq 9 electric vehicles as they come off the assembly line, lift them from below and transport them to testing stations."

I'd also remind you of the videos we've all seen of the robot forklifts whizzing around Amazon warehouses that grab products from bins so high it would take a person a bit to climb or be lifted there, or that simply pick up bins and take them to people for easy picking and packing. Robots that look nothing like people are being developed that would flip burgers and do other routine kitchen work in fast-food restaurants. 

The Times article says auto makers have high hopes for humanoid robots that will complement the massive, one-armed machines they already use to pick up and place car parts and weld them into place, but look at the main use the Times describes: 

Hyundai plans to use humanoid robots "initially for arranging components in a specified order for humans to install in vehicles. That is the same basic task that the BMW robot, made by Figure AI, demonstrated in Spartanburg. Mercedes-Benz, which is testing robots made by Apptronik in Austin, Texas, also plans to use them for handling and sorting materials. Carmakers say they have trouble retaining workers to perform such basic tasks."

That sort of use could be very helpful, but it's hardly an example of a versatile robot that could perform an unlimited variety of tasks outside of a controlled environment like a factory.

There are two major problems to overcome first, and neither looks to be solvable any time soon, no matter how much a humanoid robot outpaced Usain Bolt. 

The first is that human hands are really, really hard to imitate. Not only are fingertips sensitive in ways that machines have trouble replicating but they manage a combination of flexibility and strength that perplexes robot designers. If they want the strength of the human hand, they need to put a powerful motor in the wrist. If designers want the dexterity, they have to put a host of tiny motors in all the joints where a hand can flex. But if you do both, you wind up with a large, clunky hand. You have to make tradeoffs, and you wind up with a hand that doesn't measure up to the human combination.

The second problem is that, to be as versatile as proponents claim humanoid robots will be, they have to be able to operate in messy environments that robots simply can't navigate at the moment. A factory is one thing, but imagine a robot in your home having to step over the toys left in the family room, not bump into the dog, sort through a whole family's laundry, handling a special item precisely as your teenager demands, and so on. Not gonna happen. 

The Wall Street Journal reports that investors are piling into companies working on so-called world models, which use video games and simulations to develop more robust "action" models about how the real world operates, to go beyond the sort of top-down, rule-by-rule, prescriptive models that robots rely on today. But even the enthusiasts say the world models are currently at about the stage where the large language models used for generative AI were with ChatGPT2. That model was released seven years ago.

You'll surely continue to hear lots about the imminent arrival of armies of AI-powered, humanoid robots. They're an enticing idea. Everybody who remembers "The Jetsons" wants their Rosie the maid. There's even a cool term for the trend: "embodied AI." Hypemeister Elon Musk will, alone, make sure that humanoid robots stay in the news, given that delivering 1 million Optimus robots (at maybe $30,000 apiece) is one of the goals he has to meet to qualify for his $1 trillion pay package. And lots of sci-fi fans will continue to resonate with images of robot servants handling our daily drudgery. 

But you can ignore the hype for at least a few more years, both in personal terms and in terms of providing workers comp coverage and insuring homes. Specialized robots will provide great value in industrial settings, but they'll continue on their current trajectory. There won't be some radical change because of a new class of robots. And nobody but the earliest adopters will be tripping over a humanoid in their kitchen any time soon. 

Cheers,

Paul

Over the past several years, I’ve spent time with business owners, brokers, and community leaders in cities like New Orleans, New York, Cleveland, and Oakland. The conversations differ by market, but they converge on the same theme: not just affordability, but uncertainty. Business owners describe paying for losses out of pocket rather than risk losing coverage. Agents describe shrinking availability and carrier appetite that shifts with little warning. The message is consistent: insurance remains essential to economic resilience, yet it is often experienced as unpredictable and hard to navigate.

That reality shaped District Cover’s Urban Risk Report. The goal wasn’t just to document what’s happening in urban insurance markets, but to understand why — and what it means for the businesses and communities that depend on stable coverage.

The Stakes Are Higher Than We Often Acknowledge

More than 85% of small businesses operate in metropolitan areas. They are not just economic units — they are anchors that create jobs, provide essential services, and define neighborhood character. When those businesses can’t access insurance, the effects ripple outward: vacant storefronts, residents forced to travel farther for basic goods, and a gradual erosion of the commercial diversity that gives a city its identity. Insurance alone can’t solve the structural challenges facing urban communities, but it remains a critical part of the solution — enabling businesses to secure leases, obtain financing, and recover after losses.

A Market That Feels Constrained—But Isn’t Always

There’s a growing perception that urban risk is becoming harder to insure, and in some ways that’s understandable. Catastrophe exposure, shifting capacity, and evolving liability trends have tightened underwriting and pushed more placements into E&S markets. Even as pricing softens elsewhere in commercial lines, that relief hasn’t reached urban corridors to the same degree — density means claims are more correlated, and social inflation has hit liability lines especially hard, so urban risk is still being priced against a liability curve that hasn’t softened the way property has.

But what we found in the Urban Risk Report is more nuanced: the constraint isn’t a lack of insurable risk. It’s a gap between how risk is distributed in urban environments and how it’s evaluated. Two businesses on the same block can carry materially different exposure based on construction, occupancy, and maintenance — yet underwriting still leans on broad geographic assumptions, often at the ZIP code level, that erase that variation. Rebuild costs compound the problem: urban labor, permitting, and older building stock routinely push replacement values 15–35% above suburban benchmarks, and traditional valuations often understate that gap.

The result is a market that feels tighter than it actually is, where viable risks get declined or mispriced not because they’re uninsurable, but because they don’t fit the model. When admitted carriers pull back rather than re-price at this level of detail, the risk doesn’t vanish — it moves. California’s FAIR Plan alone grew from roughly $153 billion in exposure in 2020 to more than $450 billion by 2024. That’s not evidence these risks are uninsurable. It’s evidence they’re being routed around rather than evaluated.

The Opportunity: Precision, Not Avoidance

The answer, we believe, is precision. Insurers now have the tools — property-level data, permit and renovation records, corridor-level foot traffic, and AI-structured local data — to underwrite at the resolution urban risk actually requires, instead of a ZIP-code average. Carriers that use them can identify well-run, well-maintained businesses inside neighborhoods labeled high-risk wholesale: viable businesses that others overlook simply because they haven’t looked closely enough.

That’s also, candidly, a business opportunity. Underserved urban corridors represent real unmet demand — business that can be profitable for carriers willing to underwrite on merit rather than geography. Timing matters here too: precision underwriting is easier to build before pricing hardens further, not after. Catastrophe costs are rising industry-wide, and the carriers positioned to expand into underserved corridors profitably are the ones doing it now, on their own terms, rather than being forced into it later by a harder market.

Reframing the Conversation

The most important takeaway from this work is simple: urban businesses aren’t becoming uninsurable. They’re being misunderstood. That distinction matters — not just for underwriting outcomes, but for the long-term resilience of the communities these businesses support. At District Cover, we believe participating in urban markets takes more than showing up during favorable cycles. It takes a long-term commitment to building stability for both businesses and the communities they serve.

This report is one contribution to that effort — an invitation to insurers, brokers, policymakers, and community leaders to think harder about how insurance markets can better support the economic resilience of America’s cities. Because insurance isn’t just risk transfer. It’s what makes it possible for businesses to open their doors, invest in their future, and stay part of the communities that depend on them.

Download the full Urban Risk Report to explore the data, trends, and insights shaping the future of urban insurance.

Running an independent agency means constantly triaging what gets your attention. Renewals, service calls, new business, and the next carrier appointment. With all of that in motion, it's easy to lose track of opportunities that could help you grow your business.

If your agency's book is built mainly on home and auto, commercial offers a real chance to diversify while picking up higher premiums along the way. It's an easy opportunity to overlook, though. Commercial quoting has traditionally been complex, and without the right technology, spotting where those opportunities live has been hard to do.

That's starting to change. Here's what's shifted, where the commercial opportunity actually lies, and why independent agents are especially well-suited to act on it.

From Three Workflows to One

Commercial quoting has traditionally meant juggling three separate systems: the application, the rater, and the carrier portal. Each handoff meant re-entering the same client information. Each one added time and room for error. A client would ask about a BOP, and the quote might sometimes take until the following week, once the risk worked its way through submission to quote. 

That's changed. Modern rating and quoting technology has consolidated those steps into a single workflow. Client information is entered once, and carrier quotes surface directly inside the submission workflow. A process that used to take the better part of an afternoon can now take a few minutes. That means commercial opportunities sitting in your book are much easier to act on.

The Cross-Sell Opportunity Already in Your Book

A good number of your personal lines clients probably also own a business. More of them than you'd guess are likely relying on you for their home and auto. For commercial coverage, though, they're going elsewhere, or nowhere at all. That's not a knock on how you've built your book. It's just what happens when there's more relationship there than there's been time to explore.

The upside is that you don't have to go find these clients. You already have them. A good management system can flag commercial cross-sell and upsell opportunities directly inside your existing client records. It connects the dots you might not have time to connect on your own. A client with a general liability policy but no commercial property coverage is a signal worth a second look. 

It's the kind of detail that's easy to miss manually scanning a file, but easy for the right system to surface automatically. Leaning on technology this way is a strong place to start with commercial. The opportunity is already sitting in your book, and the more policies a client holds with your agency, the more likely they are to stay.

Why the Independent Agent Still Closes the Deal

Finding commercial opportunities is only half the equation, though. Technology can surface them, but it won't close them. That part still comes down to relationships, and that's where independent agents have an advantage no software or national carrier can replicate. You know your clients deeply: not just their premium history, but their business, their plans, what keeps them up at night. You know the local market they operate in and the pressures specific to it. That kind of trust is exactly what turns a flagged opportunity into a signed policy.

The benefits of commercial go far beyond any individual sale. Expanding into commercial helps you build a diversified business. Personal lines and commercial lines don't always move in sync. Rate cycles, carrier appetite, and underwriting conditions in one don't necessarily track the other, so agencies with a foot in both aren't relying on a single market's conditions to carry the whole book. Writing more commercial accounts also gives you room to build real depth in a niche — restaurants, contractors, professional services, whatever fits your market. That kind of specialized knowledge makes your agency an obvious call for local business owners.

From Opportunity to Action

Taking advantage of the commercial opportunity doesn't require a big shift in how you run your agency. The friction that used to make commercial too much work to chase down has largely disappeared. Software built to spot these opportunities is now doing more of that work for you. What's left is simpler: the accounts, the trust, and the expertise you've already built are finally easy to put to work.