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Effect of Automated Claims Triage on Expected Claims Processing Costs

Abstract

Automated claims triage involves the use of digital systems, rules, algorithms, and predictive models to classify insurance claims according to their characteristics, complexity, urgency, and expected processing requirements. Claims triage can influence how claims are assigned to processing channels and the level of resources required for their assessment. Changes in claims processing procedures may therefore affect the costs incurred by insurers in handling and settling claims. This study will examine the effect of automated claims triage on expected claims processing costs. It will assess how the use of automated triage systems influences the resources, time, and expenses required to process insurance claims. The study will also compare expected processing costs under automated triage and conventional manual claims allocation approaches and determine the extent to which automated classification affects claims administration expenses. The study will focus on automated claims triage, claims processing costs, insurance claims management, claims classification, automated decision systems, claims complexity, processing time, administrative expenses, claims handling, and actuarial cost analysis. Statistical and actuarial techniques will be used to estimate expected processing costs based on claim characteristics, processing requirements, staff involvement, handling time, and the allocation of claims to different processing channels. A quantitative research approach will be adopted for the study. Historical claims records, processing times, staff resource usage, administrative expenses, claim characteristics, and settlement information will be analysed using descriptive statistics, cost analysis, comparative analysis, regression analysis, sensitivity analysis, and actuarial modelling. Expected claims processing costs under automated and manual triage scenarios will be estimated and compared to determine the financial effect of automated claims classification. The study is expected to reveal that automated claims triage may have a significant effect on expected claims processing costs. Automated classification may reduce processing time and administrative resource requirements for suitable claims, while complex or exceptional claims may continue to require additional human assessment and specialised resources. The magnitude of the effect may depend on system accuracy, claim volume, claim complexity, processing time, staffing requirements, and the proportion of claims successfully handled through automated channels. The study will be useful to actuaries, insurance companies, claims managers, financial analysts, information technology professionals, regulators, and researchers. It may provide useful information for evaluating the financial implications of automated claims management, improving resource allocation, controlling administrative expenses, and strengthening claims processing efficiency. The findings may also assist insurers in assessing expected processing costs when considering investments in automated claims triage systems. The study concludes that automated claims triage can influence expected claims processing costs by changing the manner in which claims are classified, allocated, and handled. It is therefore recommended that insurers evaluate the cost implications of automated triage alongside system accuracy, processing requirements, and claim complexity, while maintaining appropriate controls for claims requiring detailed human assessment.

Keywords: Automated claims triage, claims processing costs, insurance claims management, automated claims classification, claims handling, administrative expenses, claims processing time, claims complexity, resource allocation, actuarial cost analysis, automated decision systems, claims administration, insurance technology, claims efficiency, actuarial modelling.