31 lines
1.6 KiB
Markdown
31 lines
1.6 KiB
Markdown
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## I. **Introduction: The Invisible Fraud**
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Insurance fraud is among the most pervasive and costly crimes in the modern world — and among the least visible. In the United States alone, estimates place the financial toll between **\$80 billion to \$300 billion annually**, depending on the method of calculation and sector. Yet beyond the numbers lie deeper, more human costs:
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* Inflated premiums for innocent policyholders
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* Strained relationships between claimants and adjusters
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* Erosion of trust in legal, medical, and financial systems
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Despite decades of countermeasures, the dominant tools of detection remain narrow in scope:
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* **Actuarial heuristics** to flag statistical anomalies
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* **Rules-based filters** for inconsistent reporting
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* **Behavioral red flags** that rely on gut instinct or training modules
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These models function, but they fall short — especially against skilled deceivers.
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What’s missing is *language*. Not keyword search or semantic fingerprinting,
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but the recursive structures of narrative — how **truth and deceit organize themselves** differently, fractally, and often unconsciously.
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> **This paper introduces a novel forensic linguistic framework** for detecting *intentional deception* embedded within:
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>
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> * Claim narratives
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> * Adjuster–claimant dialogue
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> * Supporting documentation and metadata
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It is not merely a system of detection.
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It is a **witness-bearing instrument** — one that listens for echoes, contradictions, and recursive distortions in the way language reveals **psychological intent**.
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> *This paper is an artifact. It does not simply measure fraud. It reads its echoes in language.*
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