The basis of the Oracle

The AIOOJ Litigation Outcome Model is a structured probability engine built specifically for Harrison v Aegon / Transamerica Entities in the NSW Supreme Court Commercial List. It answers a single practical question: given everything known about the facts, the law, the defendant's conduct, and the judicial environment — what is the realistic probability distribution of outcomes, and what does that distribution mean for litigation strategy, settlement positioning, and counsel briefing?

The model is not a legal opinion. It does not predict what a court will decide. It translates legal analysis into structured probability estimates and produces a distribution of possible outcomes ranging from nil recovery to full recovery of the $100,743,642 claim. The output is a planning tool, not a guarantee.

The model has been developed through nine versions incorporating successive layers of empirical data, benchmark calibration, and architectural improvements. Version 9.1 is the current production version.

The model's most important structural feature is that the plaintiff's claim operates across three independent recovery streams. Total defeat — a nil outcome — requires the defendant to defeat all three simultaneously. The plaintiff needs only one to succeed.

The combined failure probability — all three streams failing simultaneously at base values — is less than 0.007%. This is not optimism. It is the mathematically correct result of three high-probability independent streams operating under OR-gate logic.

Nine probability variables drive the model. Each represents a discrete legal issue assigned a Low / Base / High value. The Base value is the central estimate derived from case law analysis, the empirical dataset, and the specific facts of this proceeding.

P9 is isolated from the core merits simulation. It operates exclusively on the settlement band calculations and costs-adjusted recovery figures. This prevents double-counting — the conduct facts are already embedded in P4 and the environmental scoring.

The seven outcome paths are derived from the nine inputs through defined Boolean logic. The overall win function combines all three streams under an OR gate — any one succeeding produces a material recovery.

Note that L8 (Route C) is correctly wired as an independent OR gate in the Contract stream's limitation layer alongside L4 and L5. This was corrected in v9.1 — the original v9 Shapley sheet showed L8 at zero marginal contribution because it was absent from the win function gates despite being scored in the simulation inputs.

The model draws on two categories of data: case-specific data derived from the facts, law, and conduct of this proceeding; and environmental data reflecting the external context. Understanding the difference is essential to reading the outputs correctly.

18 cases from the HCA, NSWCA, and NSWSC were manually scored for relevance across five dimensions: claim construction (CDG), accounting/withholding (AWV), contract interpretation (CI), limitation/accrual (LAC), and early disposition (SJE). Key authorities include:

• Jones v Dunkel (1959) 101 CLR 298 — adverse inference from document withholding. Directly applicable: defendant withheld premium data through negotiations and the formal Clause 6.7 demand period.
• Chaplin v Hicks [1911] 2 KB 786 — a defendant cannot defeat a damages claim by relying on uncertainty of quantum where that uncertainty was caused by the defendant's own conduct.
• Wardley Australia Ltd v Western Australia (1992) 175 CLR 514 — demand-based accrual supporting the s.63 rebuttal.
• Mount Bruce Mining v Wright Prospecting [2015] HCA 37 and Electricity Generation Corp v Woodside Energy [2014] HCA 7 — commercial construction authorities supporting P3 and P6.
• Price v Spoor [2021] HCA 20 — limitation defence may be affected by agreement; limitation bars remedy rather than jurisdiction. Primary real anchor for P4.
• RHG Mortgage Ltd v Ianni [2015] NSWCA 56 — Jones v Dunkel inference applied to document withholding; confirmed inference can be outcome-determinative.

14 verified real anchor cases from official HCA/NSWCA sources are used in calibration, each weighted at 1.0. 86 structured comparator rows (synthetic range-fills) are retained for reference only and carry zero weight in the v9 calibration engine. The Bootstrap_Calibration sheet derives 95% confidence intervals using only the 14 real anchors — this produces deliberately wider intervals that honestly reflect the limited real-case sample available.

NSW Supreme Court Provisional Statistics 2024 inform time-to-trial assumptions. FCA empirical data (2023–24 and 2024–25 annual reports; 5-year longitudinal study across 19,483 cases) anchors the 1.5-year base and the three-branch disposition model: Summary Judgment 30% / 7 months; Negotiated 55% / 9 months; Full Trial 15% / 22 months.

Two scored indices apply uplifts to the base probability inputs. Both use a compression formula to prevent artificial inflation:

Hard caps prevent any input exceeding its judicial caution ceiling regardless of uplift stacking: P2 Deed caps at 0.92; P4 s.55 caps at 0.82; P3 EA caps at 0.88. P9 (costs factor) receives SAI uplift only — EFI uplift is excluded to prevent double-counting with the conduct facts already embedded in EFI scoring.

A model with multiple positive reinforcing factors carries a serious risk of counting the same advantage multiple times. Eight deliberate score reductions were applied during development. Near-certainty of overall recovery persisted through all testing — confirming it is structural, not inflated.

1. SAI transmission weight halved: from ×0.002 (early version) to ×0.001. Early version added +8.4% per input from SAI alone.
2. EFI transmission weight halved again: from ×0.001 to ×0.0005. Environmental factors are supporting not primary.
3. Compression formula applied: SAI 91.25 compresses to 78.9 (reduces uplift from +4.1% to +2.8%). Reflects judicial caution at high structural scores.
4. P2 Deed hard-capped at 0.92. Spencer v Commonwealth SJ caution; corporate succession chain uncertainty.
5. P4 s.55 hard-capped at 0.82. Courts apply s.55 cautiously; active obstruction ≠ guaranteed success; Briginshaw standard applies.
6. P4 base reduced 0.82→0.80 per 100-case dataset: Limitation/Timing weighted mean = 0.624 across all cases.
7. 60/40 calibration blend on every input: 60% case-specific legal analysis + 40% empirical dataset signal.
8. EBI double-count prevention: EBI (Stage 1 environmental base rate) documented only — not separately added since it is already contained within EFI.

P10 — the absolute worst case input: A tenth analytical input (P10) sits below the main model. It contains six event sliders (E1–E6) representing the individual failure probabilities of the six legal positions that must all fail simultaneously for the worst case to materialise. At defaults the joint failure probability is 0.027% (~1 in 3,700). The 12-year floor quantum is approximately $35m. The P10 stress tab on the heat map shows this worst case applied across all P2/P4 stress combinations simultaneously. The floor of $35m represents the defendant’s minimum rational exposure regardless of how every other argument is decided.

The model produces near-certain overall win probability (~99%+) at base inputs. This is the correct structural result, not an artefact of modelling. Three independent recovery streams each with high individual probability make simultaneous total defeat near-impossible. The genuine uncertainty is concentrated not in whether the plaintiff recovers, but in where in the recovery distribution the outcome lands.

• The exact probability of any specific outcome — the model produces distributions, not point predictions.
• The response of any individual judge — JAR is a directional adjustment, not a prediction.
• The effect of the Two Sets of Books reserve evidence (TAB_38_3), which is not currently reflected in the inputs.
• The defendant's internal settlement calculus — EFI models structural settlement pressure, not Aegon's board position.
• Post-judgment appellate risk — the model is calibrated for first-instance outcomes only.

Version 9.1 applied three targeted fixes identified in a post-v9 audit. None alters the core probability inputs, scenario weights, or recovery values.

1. L8 Shapley zero-contribution defect corrected. Route C (L8) was scored in the simulation inputs but absent from the Boolean win function OR gates. The Shapley sheet therefore showed L8 contributing zero — a formula defect, not a legal conclusion. L8 is now correctly wired as an independent OR gate in the Contract stream's limitation layer (alongside L4 and L5), consistent with its legal role as an independent limitation extension under Route C / s.249K Crimes Act 1900 (NSW).
2. Two-way sensitivity table replaced: P4×P5 → P2×P4. The original P4×P5 table was analytically flat — the OR-gate dominance of P2 at 0.89 suppressed all sensitivity to P4 and P5. The revised P2×P4 table tests simultaneous Deed underperformance and limitation failure — the genuine stress diagonal. Even at maximum joint stress (P2=0.60, P4=0.55), material recovery persists via Korea and demand accrual.
3. Settlement resistance floor surfaced on Dashboard; Stress_Floor sheet added. The Quantum_Distribution P10 floor is now a named KPI on the Dashboard. The new Stress_Floor sheet provides Scenario A (stressed inputs, OR gates preserved) and Scenario B (correlated collapse, AND gate — extreme lower bound) adversarial analysis.

The following are acknowledged gaps in the empirical foundation. They are documented here in the interest of full transparency for counsel review.

• NSW Commercial List plaintiff vs defendant success rates at trial — courts do not publish outcome statistics by party type; calibration is inferred from case benchmarking.
• Quantitative Jones v Dunkel application rates — no systematic dataset tracks how frequently the inference proves decisive; calibration relies on doctrinal analysis.
• s.55 success rates specifically — concealment extension cases are not separately categorised in court statistics.
• Insurance industry commission dispute precedent — no reported NSW cases are directly analogous to the commission underpayment structure in this proceeding.
• The copula correlation matrix (Copula_Correlation sheet) provides analytical bounds on the true EV but is not yet implemented as a live Monte Carlo correlation engine — a full Gaussian copula simulation would require Python/R.