Scoring Methodology

TACIS™ Scoring Engine

Total Axis Condition Intelligence Score

Deterministic, decomposable, volatility-adjusted. Four-axis scoring architecture designed for transparency, arbitration defensibility, and institutional-grade transaction intelligence.

Axis Architecture

TACIS™ Axes — SI / MS / CC / DP

Every TACIS score decomposes into four independent axes. Each axis represents a distinct dimension of vehicle condition with its own weight reflecting transactional significance.

SI

Structural Integrity

Weight: 35%

Frame integrity, unibody condition, structural welds, crash repair detection, corrosion mapping, paint depth measurements. Highest weighting reflects the irreversibility and safety impact of structural compromise.

MS

Mechanical Systems

Weight: 30%

Powertrain health, drivetrain condition, brake systems, suspension, steering, electrical, HVAC, exhaust, cooling, and fuel systems. Second-highest weighting reflects safety and functional significance.

CC

Cosmetic Condition

Weight: 20%

Exterior paint quality, panel condition, glass, trim, wheels and tires, interior surfaces, seats, headliner, cargo area, and odor assessment. Lower weighting reflects reversibility and lower transactional risk.

DP

Documentation & Provenance

Weight: 15%

Title status, lien records, service history availability, maintenance patterns, warranty claims, accident records, ownership chain integrity, and institutional audit requirements.

Computation Pipeline

Solve Order

Every TACIS score follows this exact computation sequence. Each step is deterministic and produces auditable intermediate values.

1

Execute 147-Point CVP evidence collection

Inspector completes the Condition Verification Protocol. Each of the 147 checkpoints is graded on a 0–5 severity scale with supporting photographic evidence.

2

Compute axis scores (SI, MS, CC, DP)

Checklist findings are classified into four condition axes. Each axis score is computed as a normalized value (0–100) from category-level severity aggregation.

3

Calculate Base Score (weighted composite)

Base Score = SI × 0.35 + MS × 0.30 + CC × 0.20 + DP × 0.15. The weighting reflects the relative transactional significance of each condition dimension.

4

Calculate CVM (cross-axis volatility)

CVM measures the average absolute dispersion across all axis pairs. High CVM indicates condition asymmetry — strong in one area, weak in another.

5

Apply CVM volatility penalty

Adjusted = Base Score − (CVM × 0.08). The penalty prevents misleadingly high averages from masking localized condition failures.

6

Apply ANC age normalization

ANC Factor: >10yr = 0.95, 5–10yr = 0.97, <5yr = 1.0. Ensures fair comparison across vehicle age cohorts by adjusting expectations.

7

Enforce Red Flag Cap

IF red_flags ≥ 3 AND score > 69, THEN score = 69 (VERIFIED RISK). This non-negotiable cap prevents math from hiding critical safety issues.

8

Assign Classification Band + Confidence Grade

Band assigned from 5-tier system (PRIME through CRITICAL). Confidence Grade assigned from evidence coverage depth (HIGH / MODERATE / LIMITED).

Core Architecture

Score Computation

Base Score Formula

Base = SI × 0.35 + MS × 0.30 + CC × 0.20 + DP × 0.15

CVM — Condition Volatility Measure

Cross-axis dispersion penalty

CVM = avg(|SI-MS|, |SI-CC|, |SI-DP|, |MS-CC|, |MS-DP|, |CC-DP|)

Measures the average absolute dispersion between all axis pairs. High CVM means the vehicle has significant condition asymmetry — strong in one area, weak in another. Penalty = CVM × 0.08.

ANC — Age Normalization Coefficient

Vehicle age calibration

Vehicle Age > 10 years×0.95
Vehicle Age 5–10 years×0.97
Vehicle Age < 5 years×1.00

Adjusts expectations based on vehicle age cohort. Newer vehicles are held to higher standards. A 15-year-old vehicle with minor wear scores differently than a 2-year-old with the same findings.

Red Flag Cap Rule

IF red_flags ≥ 3 AND score > 69 THEN score = 69

If a vehicle has 3 or more severity-5 red flags and the computed score exceeds 69, the final score is capped at 69 (VERIFIED RISK). This non-negotiable cap prevents mathematically high scores from masking critical safety or structural issues.

Classification Bands

90–100

VERIFIED PRIME

80–89

VERIFIED SOLID

70–79

VERIFIED WATCH

60–69

VERIFIED RISK

<60

VERIFIED CRITICAL

Interactive

TACIS™ Score Simulator

Adjust axis scores to observe how the deterministic composite, CVM penalty, ANC adjustment, and red flag cap interact in real time. Same computation used in every bureau assessment.

SIStructural Integrity (35%)88
MSMechanical Systems (30%)82
CCCosmetic Condition (20%)90
DPDocumentation & Provenance (15%)75

Red Flags

1

Age (yr)

4

Coverage

88%

84

VERIFIED SOLID

HIGH Confidence
Base Score (weighted)85
CVM (avg cross-axis dispersion)8.5
CVM Penalty-0.7
ANC Factor×1

Evidence Framework

Evidence Coverage & Confidence Grade™

Every assessment produces a Confidence Grade based on evidence coverage depth and access constraints. Confidence governs how much institutional weight participants should assign to the score.

HIGH Confidence

≥85% coverage

Full protocol completion with comprehensive photographic evidence. Institutional-grade reliability for all transaction types.

MODERATE Confidence

60–84% coverage

Partial protocol completion. Score is directionally reliable but may not capture full condition spectrum. Access constraints documented.

LIMITED Confidence

<60% coverage

Significant access limitations. Score should be treated as preliminary. Additional assessment recommended before institutional decisions.

Volatility Intelligence

Condition Volatility & Asymmetry

A vehicle can score 92 on Mechanical Systems and 55 on Structural Integrity. The simple average suggests a decent vehicle. The reality is a structurally compromised asset with good mechanicals — a fundamentally different risk profile.

CVM exists to quantify this asymmetry. It measures the average absolute dispersion across all axis pairs and applies a proportional penalty to the composite score. The higher the CVM, the more volatile the condition profile, and the larger the scoring penalty.

This is analogous to how financial risk models treat variance — two portfolios with the same expected return but different volatilities represent fundamentally different risk propositions. CVM ensures TACIS reflects total condition risk, not just average condition quality.

Example Comparison

Low Volatility Vehicle

SI: 84 · MS: 82 · CC: 80 · DP: 79

Consistent condition across all axes

High Volatility Vehicle

SI: 55 · MS: 92 · CC: 88 · DP: 70

Severe condition asymmetry — structural risk

Every score is decomposable. Every finding is evidenced.

Access the national condition bureau. Evidence first.