The adjuster shortage has been documented extensively. Experienced claims professionals are retiring faster than they are being replaced, and the pipeline of qualified newcomers is not keeping pace with demand growth driven by rising travel volumes and expanding product complexity. The direct labour consequence is well understood. The indirect costs are less often measured, and in aggregate they tend to be larger.
When a claims operation is constrained by adjuster capacity, the costs do not appear only in labour line items. They propagate through the operation in ways that are harder to track but materially significant. The P and L sees adjuster headcount and direct compensation. It rarely captures what that headcount bottleneck costs everywhere else.
Queue cost: time-to-decision as a loss multiplier
The most visible indirect cost is claims queue length. When adjusters are backlogged, standard cases sit in queues waiting for attention. For travel claims, a policyholder who filed a delay claim three weeks ago and has heard nothing is a policyholder with a complaint. Every complaint requires handling work that is typically more labour-intensive than the original claim would have been if processed promptly.
The complaint-to-original-claim ratio in manual-heavy operations is frequently underestimated because complaints are tracked separately from claims in most systems, and the connection between queue length and complaint volume is not always mapped by operations leadership. In operations Saverio has worked in or analysed over the past eight years, the complaint handling overhead for standard travel claims on a backlogged queue runs between 40% and 80% of the original claims handling cost as an additional layer. That overhead is real adjuster time spent on avoidable re-work.
Complaints also generate regulatory exposure. An insurer handling a pattern of delayed travel claims under the Swiss Insurance Supervision Act (VAG) or equivalent EU Solvency II frameworks can attract supervisory attention that creates compliance overhead well beyond the claims themselves.
Inconsistency cost: decision variance on identical claims
A manual adjuster operation introduces decision variance. Two adjusters reviewing the same flight-delay claim against the same policy may reach different conclusions, particularly on edge cases where the delay is near a threshold or where a policy clause has an ambiguous condition. This variance has direct financial consequences: some claimants receive more than the policy provides; others receive less than they are entitled to.
The claims leakage problem (payments above entitlement) is commonly measured. The under-payment problem is less often tracked, but it generates its own cost in the form of complaints, regulatory attention, and reputational exposure. Both are expressions of the same inconsistency, driven by the same root cause: human adjuster judgment variability under volume pressure.
This is not a criticism of individual adjusters. A skilled adjuster working at a manageable pace on well-documented policies will make consistent decisions. Put the same adjuster on a backlogged queue with 200 open files and introduce policy variants they have not encountered before, and variance increases. The inconsistency is a systemic output, not an individual failure.
Training and knowledge-retention cost
A skilled claims adjuster carries significant procedural and product knowledge that is difficult to document and even harder to transfer. When that person leaves, their knowledge leaves with them. The training cost for a replacement is substantial; the ramp time before the replacement reaches full productivity is typically 6 to 12 months for travel claims portfolios that span multiple product variants and destination categories. During that ramp, error rates are higher, handling times are longer, and supervisor oversight requirements increase.
In a high-turnover environment, these training cycles overlap and create a structural drag on operational performance. The knowledge never fully accumulates; the operation is perpetually onboarding. Senior adjusters who would otherwise be handling complex cases spend a disproportionate share of their time reviewing junior work and answering process questions.
Fraud exposure under volume pressure
A less-discussed consequence of the bottleneck is elevated fraud exposure. Travel insurance fraud, particularly for flight-delay and baggage claims, relies partly on the assumption that a high-volume manual operation will not check every submission carefully. Adjusters under pressure tend to process standard-looking claims without full verification: they trust that the boarding pass image is genuine, that the flight data matches the claim, that the policy was not purchased after the delay occurred.
An automated pipeline applies the same verification steps to every claim regardless of volume. The consistency is a fraud-reduction mechanism as much as an efficiency mechanism. This benefit does not show up directly in adjuster cost metrics, but it does show up in loss ratios over time for carriers that implement it.
Scaling cost: the linear growth constraint
Manual claims operations scale roughly linearly with volume. To process twice as many claims, you need roughly twice as many adjusters. For travel insurers experiencing volume growth, this creates a structural problem: the cost of scaling is predictable and high, the timing of volume growth is not, and the lead time for hiring and training new adjusters means the operation is perpetually either over- or under-provisioned relative to actual volume.
Peak periods, travel disruption events (a weather system that grounds flights across a major hub), and seasonal spikes create acute over-capacity problems that a headcount-based operation cannot absorb. The queue that forms during a disruption event takes weeks to clear, generating complaint overhead long after the disruption itself is resolved.
The total cost of manual adjuster dependency, when these components are measured alongside direct labour, consistently exceeds what operations leadership estimates before analysis. The adjuster shortage is the visible symptom. The hidden costs are the structural argument for reducing the dependency rather than simply trying to hire into it.
