Auto Claims Under Pressure

David opened the panel by framing the core issue: both personal auto and commercial auto have been persistent profitability challenges for insurers. The question for the panel was not how to rewrite the past underwriting decision, but how claims teams can manage the book better once the business is already on the books.

Dylan Brand argued that one of the first places to look is activity inside the claim file. He pointed to days since last activity as a practical diagnostic because claims do not close unless an adjuster is actively moving the file forward. That metric can expose whether the issue sits with individual performance, training, staffing, management, system limitations, or broader operational design.

That single measure can also become a window into larger trends. If certain teams, lines of business, adjusters, subrogation units, or salvage groups have files sitting too long, the issue may not be underwriting at all. It may be claims inventory, workflow design, lack of engagement, or inadequate claims system support.

Chris Boedeker pushed the conversation toward operational visibility. Claims departments are often blamed when a book deteriorates, but the useful question is whether leaders can drill deeply enough into the data to identify the actual problem and test a real remedy.

He used his experience in mobility and sharing economy claims to explain how detailed operational metrics can reveal friction that would otherwise be missed. At Uber, for example, the important metric was not only whether a vehicle was damaged. It was how long it took a driver to get back to the next trip. A claims process that slowed that down created pain for the claimant, the platform, and the insurer.

The lesson was broader than one company or use case. Claims leaders need dashboards and operating metrics that let them test hypotheses, compare performance, and understand whether a process change is actually improving outcomes. Without that level of detail, teams risk reacting to symptoms rather than fixing the source of the problem.

Lay Ling Khoo brought the mobile technology perspective into the discussion. Modern auto claims generate more data than ever: telematics, connected vehicle information, repair data, photos, notes, vendor inputs, and device-level documentation. The problem is not always that insurers lack data. It is that adjusters may not have the right intelligence available when they need to make a decision.

She described a claims environment where adjusters move between devices, return to vehicles or home offices to finish documentation, upload notes late in the day, and spend time re-entering information across systems. Each delay creates more opportunity for information to be missed, duplicated, or weakened before it becomes useful in the claim file.

For insurers, this reframes mobility as more than a device decision. Mobile workflows can affect documentation speed, evidence quality, customer experience, and downstream decision-making. A better field process can help claims teams capture clearer information earlier and reduce the administrative drag that slows resolution.

When asked how to turn around a struggling book, Dylan was direct: there is no single magic lever. The first move is often to bring in highly capable adjusters who can attack the oldest and most problematic files. Those files may not make the short-term metrics look better immediately, but resolving them can reduce exposure to bigger downstream losses.

He also warned against the instinct to simply cut poor performers before stabilizing the team. If claims inventory remains the same while the number of adjusters shrinks, the book can enter what he called a death spiral: more claims assigned to fewer people, more burnout, slower closure, and even more files falling behind.

Reserve adequacy and settlement authority also came up repeatedly. If many claims sit just at or below an adjuster’s authority threshold, it may be a signal that reserves or authority processes are creating friction. That friction can slow settlement, distort the view of the book, and keep teams from resolving matters that should be moving.

The panel also addressed fraud, especially as AI makes it easier to create or manipulate images, documents, and claim narratives. Lay Ling was careful not to overstate the role of mobile devices. Devices do not “detect fraud” by themselves. Fraud models, investigative teams, and claims processes still carry that work.

Where mobile technology can help is at the evidence collection point. Secure field devices can support higher-quality photos and video, timestamps, location context, digital notes, and faster transmission into the claims workflow. The goal is not just to collect more data. It is to protect the quality, integrity, and timeliness of the evidence that later decisions depend on.

If the first touchpoint in the claims process is weak or unsecured, downstream decisions can inherit that weakness. For auto claims teams under pressure, the field collection process becomes part of the control environment.

An audience question asked why humans should remain central when AI agents can process more information. Dylan’s answer was that claims should absolutely use AI, but the right division of labor matters. AI can summarize large demand packages, extract information, structure data, and remove repetitive work that humans are not especially good at doing manually.

But claims still involve judgment, communication, licensing requirements, negotiation, empathy, and trust. Lay Ling echoed that point: claims remains fundamentally a human and people business. AI can help a claim professional see more and work faster, but it cannot replace the emotional connection that a customer may need during a difficult claim.

The broader operational point was simple: automation is most useful when it reduces friction for adjusters. If it adds another system, another dashboard, or another place to copy information, it can make the work worse rather than better.

At the end of the session, David asked each panelist for one operational change that could help an auto book under pressure. The answers formed a practical short list for claims leaders.

Lay Ling focused on the speed and quality of the first claim interaction. The first interaction creates the foundation for the claim: evidence, documentation, customer experience, and workflow quality. If adjusters are spending too much time on administrative tasks or re-entering information, the process starts with friction.

Chris focused on detailed operational metrics. Claims leaders need enough data to drill down into problems, talk through the numbers with claims people, and test whether a proposed remedy is actually addressing the issue.

Dylan focused on removing friction points, especially around reserves and settlement authority. If authority thresholds or reserve practices are slowing resolution, claims teams may be unable to move files efficiently even when they know what needs to happen.