Insurance Claims Process: Example and Improvement Guide

Purpose and scope

A claims process covers everything from a policyholder first reporting a loss to the claim being settled, denied, or closed. The scope here runs from first notification of loss through final settlement or closure, including any investigation, adjustment, and communication that happens along the way. This is one of the more consequential processes an insurer runs, since claims handling is often the primary point of contact a policyholder has with the insurer after purchasing a policy, and delays or errors here have a disproportionate effect on how the relationship is perceived.

Claims processes vary considerably by line of business, a straightforward auto glass claim looks nothing like a complex property claim involving multiple parties, but most share the same underlying stages: intake, triage, review, possible investigation, a decision, and settlement or denial. This example follows that general shape.

Typical roles

• Policyholder or claimant: reports the loss and provides supporting documentation and information as requested.
• Intake or first notice of loss team: records the claim, confirms policy coverage, and assigns it for handling.
• Claims adjuster or handler: reviews the claim, requests further information, coordinates any investigation, and prepares a decision.
• Special investigations unit: reviews claims flagged for potential fraud or unusual circumstances.
• Claims supervisor or manager: approves decisions above a handler's authority level and resolves escalated disputes.
• Payments or settlements team: processes approved payments to the policyholder or a third party.

Example as-is flow

Common decisions

The first meaningful decision is whether the reported loss is covered under the policy as written, which determines whether the claim proceeds at all. Triage involves deciding how complex the claim is and which adjuster or team should handle it, since a straightforward claim and a multi-party liability claim need very different levels of scrutiny. A decision about whether the claim shows any indicators warranting referral to a special investigations unit affects both timeline and outcome. During review, the adjuster decides what additional documentation or expert input, such as an independent assessment, is genuinely necessary versus what would simply add delay without changing the outcome. Finally, a decision is made on the settlement amount and whether it falls within the adjuster's own approval authority or needs to go to a supervisor.

Common exceptions and rework

Claims are exception-prone by nature, since every loss is a distinct event. A common source of rework is incomplete documentation from the policyholder, requiring the adjuster to send repeated requests before a decision can be made. Coverage questions sometimes surface midway through review that were not caught at initial triage, sending the claim back for a coverage determination that should have happened earlier. Disputes over the settlement amount lead to renegotiation, additional documentation requests, or escalation to a supervisor. Claims initially triaged as simple sometimes turn out to be more complex once documentation arrives, requiring reassignment to a more experienced handler and effectively restarting part of the review. Investigation referrals themselves can also loop back, since an investigation might raise new questions that require the original adjuster to gather further information from the policyholder.

Likely bottlenecks

Waiting on documentation from the policyholder or third parties, such as repair shops or medical providers, is frequently the single largest source of elapsed time in a claims process, and it is often outside the insurer's direct control, though the process for chasing and escalating slow responses is within its control. Investigation referrals can also become a bottleneck if the special investigations unit has limited capacity relative to the volume of claims flagged, creating a queue that holds up otherwise straightforward claims. Supervisor approval for claims above a handler's authority level can bottleneck if supervisors are managing this alongside a full caseload of their own, rather than treating approvals as a priority task. A less visible bottleneck can appear in handoffs between intake and adjusters, where claims sit unassigned for a period before anyone actively works them.

Process improvement options

Improving intake to confirm coverage and gather key documentation requirements up front reduces the number of later requests sent back to the policyholder. A clearer, more consistently applied triage standard reduces the number of claims reassigned mid-process due to misjudged complexity. Setting explicit service standards for how quickly a policyholder response is followed up, rather than leaving follow-up timing to individual adjuster discretion, shortens the documentation-waiting bottleneck. Reviewing and tightening the criteria for investigation referral can also reduce unnecessary referrals that add time without changing the outcome, while ensuring genuinely warranted referrals are not delayed by an overloaded queue.

Conventional automation opportunities

Coverage confirmation against clear policy terms, routing claims to the correct adjuster team based on line of business and value, and sending automated reminders to policyholders for outstanding documentation are all rules-based tasks well suited to conventional automation. Automatically flagging claims that exceed a value threshold for supervisor approval, rather than relying on an adjuster to remember to escalate, is another straightforward automation candidate. These steps involve clear, structured criteria that do not require interpretation.

Possible AI scenarios

Several claims tasks involve enough variability and language interpretation to be worth evaluating as AI scenarios, without assuming in advance that they will be worth implementing. One scenario is an AI agent that reviews submitted documentation and claim narratives to identify missing information before an adjuster reviews the file, reducing back-and-forth with the policyholder. Another is an AI agent that summarizes lengthy claim files, including notes, correspondence, and reports, into a concise briefing for a supervisor's approval decision. A third scenario worth testing is an AI-assisted first pass at identifying claims with fraud indicators for the special investigations unit to review, functioning as a screening aid rather than a decision-maker. Each should be modeled against the current process baseline rather than adopted on the assumption that language capability alone makes it a good fit.

Metrics to compare

How Processfix fits in

Processfix lets a claims team build an editable model of this process from a plain-language walkthrough or an existing procedure document, then run a discrete-event simulation across hundreds of representative cases to see where documentation waits, investigation queues, and approval steps actually create delay. Improve and Add AI scenarios, such as automated documentation screening or supervisor briefing summaries, can then be compared against the locked baseline on cycle time, throughput, and utilization, and the resulting comparison can be exported as a documented decision record.