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🧠 '''Anchoring bias''' is a cognitive bias in which decision-makers rely disproportionately on an initial piece of information — the "anchor" — when making subsequent judgments, even when that anchor is arbitrary or outdated. In the insurance industry, this bias surfaces across the full value chain: [[Definition:Underwriter | underwriters]] may anchor on prior-year [[Definition:Premium | pricing]] when setting renewal rates, [[Definition:Claims adjuster | claims adjusters]] may anchor on initial reserve estimates when evaluating developing losses, and [[Definition:Actuary | actuaries]] may anchor on historical [[Definition:Loss ratio | loss ratios]] when projecting future experience. The result is systematic mispricing, reserve inadequacy, or flawed strategic decisions that deviate from what current data would support.

🔍 The mechanics of anchoring bias are deceptively simple. An underwriter reviewing a [[Definition:Renewal | renewal]] account sees last year's premium of $500,000 and unconsciously treats it as a starting reference, adjusting only incrementally despite evidence that [[Definition:Loss experience | loss experience]], [[Definition:Exposure | exposure]], or market conditions warrant a materially different figure. Similarly, in [[Definition:Reserving | reserving]], an initial case estimate established at first notice of loss can persist through development cycles because successive reviewers adjust insufficiently from that starting point. Research in behavioral economics — notably by Kahneman and Tversky — has demonstrated the pervasiveness of anchoring across all types of estimation tasks, and [[Definition:Insurance regulation | regulators]] and rating agencies have increasingly flagged its potential to distort [[Definition:Technical pricing | technical pricing]] and [[Definition:Reserve adequacy | reserve adequacy]] across the industry.

💡 Recognizing and mitigating anchoring bias has become a practical priority for insurance organizations worldwide. Leading [[Definition:Insurance carrier | carriers]] and [[Definition:Reinsurance | reinsurers]] now embed de-biasing techniques into their workflows: blind [[Definition:Peer review | peer reviews]] where second-opinion underwriters do not see the incumbent price, structured [[Definition:Actuarial analysis | actuarial frameworks]] that require ground-up recalculation rather than simple trend adjustments, and [[Definition:Artificial intelligence (AI) | AI-assisted]] pricing models that generate independent benchmarks against which human judgment is tested. The [[Definition:Lloyd's of London | Lloyd's]] market, for example, has invested in behavioral science programs aimed at improving underwriting discipline. In an industry where judgment under uncertainty is the core product, understanding anchoring bias is not merely an academic exercise — it directly affects profitability, [[Definition:Solvency | solvency]], and the accuracy of the promises insurers make to [[Definition:Policyholder | policyholders]].

'''Related concepts:'''
{{Div col|colwidth=20em}}
* [[Definition:Cognitive bias]]
* [[Definition:Technical pricing]]
* [[Definition:Reserve adequacy]]
* [[Definition:Behavioral economics in insurance]]
* [[Definition:Underwriting discipline]]
* [[Definition:Availability bias]]
{{Div col end}}

Definition:Anchoring bias - Revision history

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