Simon Glairy has built a career at the intersection of risk management and emerging technology, positioning himself as a leading voice in the evolution of Insurtech. With deep expertise in how automated systems and regulatory shifts impact automobile liability, he has spent years advising platforms on the complexities of peer-to-peer sharing and the legal nuances of insurance underwriting. Our conversation centers on the sweeping changes introduced by Maryland’s House Bill 1186, which fundamentally alters the insurance playbook for car-sharing programs. We delve into the implications of carriers gaining the right to deny policies based on sharing activities, the transfer of liability for citations, and the logistical hurdles of cross-border coverage minimums.
Carriers can now make underwriting decisions based on a vehicle’s participation in peer-to-peer sharing. How will this change affect market competition, and what specific data points should insurers evaluate before choosing to deny or terminate a policy for a shared vehicle?
The repeal of the former restriction on policy denials is a seismic shift that restores a significant amount of control to traditional insurers. Previously, carriers in Maryland were somewhat handcuffed, unable to nonrenew or cancel a policy solely because a vehicle was listed on a car-sharing platform, but after October 1, 2026, that protection for owners disappears. This will likely lead to a more fragmented market where some carriers embrace the risk through specialized riders while others exit the space entirely to avoid the higher mileage and varied driver profiles associated with peer-to-peer sharing. Insurers should be looking closely at telematics data, specifically the ratio of “sharing hours” versus personal use and the geographical areas where the vehicle is most frequently parked or operated. By evaluating the frequency of different drivers behind the wheel and the specific safety ratings of the car-sharing platforms themselves, insurers can move away from blanket denials and toward a more nuanced, risk-adjusted pricing model.
Specific triggers, such as failing to cooperate with insurers or providing inadequate claim notices, now shift primary liability back to the car-sharing program. What internal compliance protocols must platforms implement to avoid these triggers, and how might this shift impact their overall operational costs?
The new Section 18.5-102.1 creates a high-stakes environment for platforms, as a simple administrative lapse can now result in the program becoming the primary security provider for a claim. To mitigate this, platforms must establish robust, automated claims-notification systems that provide instantaneous alerts to insurers the moment an incident is reported in the app. They will also need to invest heavily in legal and claims-adjustment staffing to ensure they are meeting the “cooperation” threshold, which includes sharing driver data and trip logs without delay. These internal compliance measures represent a significant uptick in operational overhead, as the cost of “prejudicing” a claim—by failing to disclose information or providing supplemental coverage—could lead to multi-million dollar exposures that were previously shielded. We are moving toward a reality where the platform is not just a facilitator of transactions but a highly regulated entity that must act with the same diligence as a traditional insurance adjuster.
Shared vehicle drivers may now use their own personal insurance policies to satisfy state coverage requirements. What are the practical challenges in verifying these policies in real-time, and how should platforms manage the legal risks if a driver’s personal policy lapses during an active trip?
While allowing a driver’s personal policy to satisfy the requirements under Section 17-103 offers more flexibility, it introduces a massive verification headache for the platforms. In a real-world scenario, a driver could provide proof of insurance at the start of a booking, only for that policy to lapse or be cancelled for non-payment hours later. Since the law mandates that the car-sharing program’s coverage must step in as primary if the driver’s policy is inadequate or lapsed, the platform effectively becomes the “insurer of last resort” for every transaction. To manage this legal risk, platforms will likely need to integrate directly with national insurance databases to confirm policy status in real-time, rather than relying on static digital cards. Without this technological bridge, the platform faces the constant threat of absorbing primary liability for accidents they assumed were covered by a third party.
The state’s insurer of last resort is no longer required to cover shared vehicle drivers unless the car is used as a temporary replacement vehicle. How does this exclusion affect high-risk drivers, and what alternative insurance products might emerge to fill the resulting gap in the marketplace?
The carve-out for the Maryland Automobile Insurance Fund (MAIF) is a clear signal that the state no longer views general car-sharing as a public necessity that requires a government-backed safety net. For high-risk drivers who cannot obtain standard coverage and rely on car-sharing for non-essential travel, the options are going to shrink rapidly. We will likely see the rise of “on-demand” or “per-trip” insurance products specifically tailored for the peer-to-peer market, where the premium is baked into the daily rental price and provided by private surplus lines insurers. These niche products will have to be carefully structured to meet Maryland’s minimums while accounting for the fact that MAIF will only step in if the vehicle is a legitimate “replacement vehicle” undergoing repair or service. It creates a vacuum that only innovative, tech-forward insurers will be able to fill, likely at a higher price point for the end user.
When an incident occurs in a state with higher minimum financial responsibility limits, the coverage must automatically match those higher requirements. How can insurers streamline the claims process for these cross-border accidents, and what are the primary actuarial risks associated with this variable liability?
Managing cross-border liability requires a dynamic adjustment engine within the insurer’s claims software that can automatically re-calculate limits based on the GPS coordinates of the accident. Because Maryland’s law now requires coverage to match the higher limits of the state where the claim arose, insurers face a “floating” liability risk that is difficult to price accurately. For example, if a car shared in Maryland is driven into a neighboring jurisdiction with significantly higher bodily injury minimums, the actuarial assumptions used at the start of the trip are immediately invalidated. The primary risk here is the “limit jump,” where a low-premium policy suddenly provides high-limit coverage due to a geographical shift. Insurers will need to set premiums based on the likelihood of the vehicle leaving the state, perhaps using geofencing technology to restrict or surcharge trips that venture into high-limit jurisdictions.
Programs can now transfer monetary liability for tolls, fines, and red-light citations directly to the driver in possession of the vehicle. What technology solutions are necessary to track these expenses accurately, and how does this change the financial relationship between the platform and the vehicle owner?
This change is a huge win for vehicle owners who, until now, often found themselves fighting citations that were clearly the fault of the guest driver. To implement this effectively, platforms will need to synchronize their trip logs with municipal tolling and law enforcement databases, using timestamped data to prove exactly who was behind the wheel at the moment of the violation. We will see an increased reliance on API integrations between platforms and entities like the E-ZPass system to facilitate the seamless transfer of these costs. This shifts the platform’s role from a simple intermediary to a quasi-enforcement agency, ensuring that owners are held harmless for the driver’s behavioral lapses. It cleans up the financial relationship significantly, as it removes the “hidden costs” of sharing a vehicle that previously discouraged many owners from participating in the ecosystem.
What is your forecast for the peer-to-peer car sharing market in Maryland?
I expect to see a period of intense consolidation and professionalization as the October 2026 deadline approaches. The days of casual, unregulated car-sharing are ending in Maryland, replaced by a framework that demands high-level technical integration and strict insurance compliance. While some smaller platforms may struggle with the increased operational costs associated with the new liability triggers, the market as a whole will become more stable and attractive to traditional insurers who were previously wary of the regulatory ambiguity. Ultimately, Maryland is setting a precedent for how states can balance the growth of the sharing economy with the need for rigorous consumer protection and clear-cut insurance accountability. My forecast is that Maryland will become a testing ground for sophisticated Insurtech solutions that bridge the gap between personal auto policies and commercial sharing risks.
