Methodology

Benford's Law Analysis Suite

Comprehensive digit frequency analysis applying established forensic accounting methodology. Naturally occurring financial data follows predictable mathematical distributions first documented by Newcomb (1881) and formalised by Benford (1938). Fabricated or manipulated data consistently deviates from these patterns.

• First Digit Test (D1) - Primary fraud indicator; expected distribution: 30.1% begin with 1, decreasing logarithmically to 4.6% for 9
• Second Digit Test (D2) - Detects sophisticated manipulation; expected range 11.97% (digit 0) to 8.50% (digit 9)
• First-Two Digits Test (D1D2) - 90 possible combinations; highest sensitivity to artificial data; detects threshold avoidance
• First-Three Digits Test (D1D2D3) - 899 combinations; identifies specific fabricated values in large datasets
• Last-Two Digits Test - Uniform distribution expected; detects rounding manipulation and preference patterns

Statistical Significance Testing

Multiple independent tests quantify the probability that observed patterns occurred by chance. Results expressed as confidence levels admissible in court proceedings with full methodology documentation.

• Chi-Square Test - Goodness-of-fit test comparing observed vs expected frequencies; p-value indicates manipulation probability
• Z-Test (Per-Digit) - Tests individual digit deviation; identifies which specific values show suspicious frequency
• Mean Absolute Deviation (MAD) - Nigrini's preferred metric; thresholds: Close (<0.006), Acceptable (<0.012), Marginal (<0.015), Nonconformity (>0.015)
• Distortion Factor - Measures systematic bias direction; positive indicates upward manipulation, negative indicates suppression
• Kolmogorov-Smirnov Test - Non-parametric distribution comparison; detects subtle deviations across entire dataset
• Anderson-Darling Test - Enhanced sensitivity at distribution tails; detects manipulation in extreme values

Conformity Classification

Results classified per Dr. Mark Nigrini's established forensic accounting standards, widely accepted in fraud litigation. Each dataset receives a conformity rating with supporting statistical evidence.

• Close Conformity - MAD < 0.006: Data consistent with natural occurrence; no statistical indicators of manipulation
• Acceptable Conformity - MAD 0.006-0.012: Minor deviations within normal variation; insufficient for adverse inference
• Marginal Conformity - MAD 0.012-0.015: Borderline results; warrants further investigation of flagged transactions
• Nonconformity - MAD > 0.015: Statistically significant deviation; strong indicator of estimation, fabrication, or manipulation

Outlier Detection Methods

Multi-method anomaly identification using complementary statistical approaches. Flagged values cross-referenced against case documentation to assess legitimacy.

• Z-Score Analysis - Standard deviation method; flags values exceeding 2.5-3.0 standard deviations from mean
• Modified Z-Score (MAD-Based) - Robust to outliers in source data; uses median absolute deviation for baseline
• Interquartile Range (IQR) - Distribution-agnostic method; flags values below Q1-1.5*IQR or above Q3+1.5*IQR
• Composite Anomaly Scoring - Weighted combination of all methods; produces 0-100 fraud probability score per transaction

Fraud Pattern Detection

Targeted analysis for common manipulation techniques documented in forensic accounting literature. Each pattern tested independently with statistical significance assessment.

• Round Number Bias - Excessive clustering at round values (00, 50, 000); indicates estimation rather than documented transactions
• Threshold Avoidance - Suspicious clustering below approval limits, reporting thresholds, or tax boundaries (e.g., values at 9,900-9,999 avoiding 10,000 threshold)
• Duplicate Detection - Exact and near-duplicate identification; cross-references dates, amounts, and descriptions for billing fraud patterns
• Sequence Analysis - Invoice/reference number gaps, arithmetic progressions, and pattern detection in sequential identifiers
• VAT Calculation Verification - Mathematical testing of claimed tax calculations; identifies computational errors and false tax figures
• Temporal Pattern Analysis - Transaction timing distribution; flags unusual clustering in dates, times, or reporting periods

Output: Quantified Results

Every statistical analysis produces court-ready documentation with full methodology transparency. Results designed for expert witness presentation and cross-examination resilience.

• Conformity Score - Overall dataset rating with confidence interval and supporting test results
• Flagged Transactions - Itemised list of anomalous entries with individual probability scores and flag reasons
• Visualisation Package - Digit distribution charts, deviation graphs, and comparison exhibits for court presentation
• Methodology Documentation - Complete description of tests applied, thresholds used, and academic citations for each method
• Limitation Statement - Clear disclosure of sample size constraints, test applicability, and confidence boundaries

Forensic Stylometry (Court-Accepted)

Authorship attribution using quantitative computational linguistics. Admissible under Daubert with documented methodology and known error rates. Key precedents: Unabomber case (FBI), David Hodgson case (UK, 2008).

• Burrows' Delta Analysis - Statistical measure of stylistic similarity; scores below 1.0 indicate common authorship, above 1.5 indicate different authors
• Writing Style Fingerprinting - Quantitative analysis of vocabulary, sentence structure, punctuation patterns unique to individual authors
• Function Word Analysis - Frequency distribution of function words (the, and, of) - unconscious patterns resistant to deliberate disguise
• N-gram Distribution - Character and word sequence patterns providing additional authorship markers
• Vocabulary Richness - Lexical diversity measurements (type-token ratio, hapax legomena frequency)
• Output: Quantitative Scores - Similarity metrics with confidence intervals and methodology documentation suitable for expert testimony

Linguistic Consistency Analysis (Court-Accepted)

Objective comparison of multiple statements identifying contradictions and inconsistencies. Framed as factual comparison - determination of significance reserved for finder of fact.

• Cross-Statement Comparison - Systematic identification of claims that differ between Statement A and Statement B with source citations
• Claim Evolution Tracking - Documentation of how specific claims change across multiple statements over time
• Temporal Consistency Review - Identification of chronological conflicts (claimed event at 3pm in Statement A, 5pm in Statement B)
• Detail Variance Assessment - Documentation of details present in one statement but absent in another
• Documentary Corroboration - Cross-referencing statement claims against documentary evidence to identify confirmations or conflicts
• Output: Factual Reports - "Statement A asserts X. Statement B asserts Y. These assertions are inconsistent regarding Z."

Verifiability Assessment (Research-Backed)

Analysis of checkable vs uncheckable detail ratios. Research indicates accounts of experienced events contain higher proportions of verifiable details. Used to identify areas warranting further investigation.

• Verifiable Details - Specific names, places, times, witnesses that can be independently confirmed or refuted
• Unverifiable Details - Internal states, private conversations, subjective experiences that cannot be independently checked
• Ratio Calculation - Proportion of verifiable to total details compared against baseline expectations
• Specificity Assessment - Degree of precision in claims (exact amounts vs "around" or "approximately")
• Investigative Value - Identification of verifiable claims that should be checked against independent evidence
• Output: Areas of Inquiry - "The following specific claims warrant verification: [list with source citations]"

Court-Ready Intelligence

We deliver Daubert-compliant evidence packages designed to survive cross-examination. Documented methodology. Quantified confidence levels. Precise source citations. Everything a litigation team needs to dominate discovery and depositions.

• Admissible Indicators - Forensic findings framed to court-accepted standards, ready for expert testimony
• Investigation Roadmaps - Identified contradictions, areas of concern, and verification targets that focus your case strategy
• Cross-Examination Ammunition - Every inconsistency documented with page, paragraph, and line citations
• Methodology Transparency - Complete documentation of analytical methods, peer-reviewed foundations, and known error rates
• Expert Witness Ready - Output structured for testimony under Daubert/Frye standards across jurisdictions
• Deposition Preparation - Targeted question frameworks built from documented statement inconsistencies

Exhaustive Cross-Reference

Every claim compared against every other claim. A 500-page case file contains 124,750 potential claim pairs. We cross-reference every one. Manual review teams pick samples - we examine everything.

Zero Fatigue Degradation

Human accuracy drops after 2-3 hours. Our systems maintain consistent analytical precision across 10,000+ pages. We never tire. We never lose focus. We never miss a pattern because we're on page 847 and it's late.

Pattern Recognition at Scale

Statistical patterns - Benford's Law violations, rounding bias, threshold clustering, behavioral markers - require analysis of entire datasets. Human spot-checking cannot detect patterns distributed across thousands of data points. We see the patterns invisible to sequential reading.

Perfect Recall

Every indexed claim retrievable instantly. Precise citation to document, page, and paragraph. When a witness says something that contradicts page 412 of Exhibit C, we find it. Every time.

Analyst Verification

AI-powered systems generate findings. Trained analysts verify, contextualise, and apply judgment. Every analysis undergoes quality review before delivery. We identify what exists in the documentary record - trained analysts determine what it means for the case.

Standard Deliverables

• Executive Summary - Overview of key findings, significance assessment, and recommended areas for further inquiry
• Detailed Analysis Report - Complete findings with methodology documentation, source citations, and supporting analysis
• Inconsistency Schedule - Indexed catalogue of identified inconsistencies with citations, significance ratings, and cross-references
• Timeline Documentation - Chronological mapping of events with source documentation and identified sequence issues
• Statistical Analysis Report - Quantitative findings with methodology explanation, significance testing, and interpretive guidance
• Cross-Examination Reference - Organised reference document keyed to specific documentary inconsistencies for deposition and trial use
• Exhibit Package - Court-ready visual materials: timelines, comparison charts, and summary tables formatted for presentation
• Source Index - Complete index of analysed documents with citation key for reference throughout proceedings