System and method for cryptographically verified actuarial risk signal generation from heterogeneous artificial intelligence governance telemetry

Abstract

A computer-implemented system and method are provided for generating cryptographically verified actuarial risk signals from heterogeneous artificial intelligence governance telemetry. Heterogeneous telemetry is received via a telemetry acquisition interface and canonicalised under a unified risk data schema using Unicode NFC normalisation, lexicographic key sorting, and hardware-attested timestamp synchronisation within a trusted execution environment. A governance-conditioned variance modulation engine, an oversight conduct degradation coefficient calculator, and a cryptographic anomaly correlation index calculator operate on the canonicalised records using fixed-point arithmetic producing verifier-independent results. Calculated coefficients and a configuration version identifier are anchored into a SHA-256 hash chain aggregated under a Merkle tree structure. A cryptographic actuarial signal gateway generates cryptographically signed signals and transmits them via a defined exchange protocol to remote insurer reserve-allocation systems, producing signed receipt acknowledgements. 20 26 20 37 36 14 M ay 2 02 6 2 0 2 6 2 0 3 7 3 6 1 4 M a y 2 0 2 6 2 0 2 6 2 0 3 7 3 6 1 4 M a y 2 0 2 6

Description

Applicant: John Richard Cosstick Inventor: John Richard Cosstick The following statement is a full description of this invention, including the best method of performing it known to me: 2026203736   14 May 2026 TECHNICAL FIELD

[0001] The present invention relates to computer-implemented systems for cryptographically verified signal generation from heterogeneous machine-readable telemetry streams, and more particularly to systems and methods configured to transform machine-readable artificial intelligence governance telemetry into cryptographically signed actuarial risk signals transmissible to remote underwriting, reserve allocation, and operational resilience systems.

[0002] The invention further relates to: cryptographic normalisation of heterogeneous governance telemetry into canonicalised governance-state records; computer-implemented quantification of human oversight conduct using cryptographically anchored evidence chains; governance-conditioned variance modulation over longitudinal records; oversight conduct degradation analysis using secure-enclave attested timestamps; cryptographic anomaly correlation across multiple workflows and enterprise entities; and machine-verifiable transmission of resulting risk signals to remote actuarial reserve-allocation engines via a defined cryptographic exchange protocol. BACKGROUND OF THE INVENTION

[0003] Artificial intelligence systems are increasingly deployed within professional services, legal systems, accounting, financial advice, healthcare, insurance, autonomous orchestration systems, infrastructure operations, and agentic computational workflows. Their deployment has produced a category of operational signals—machine-readable records of human and machine governance conduct—that did not previously exist at scale.

[0004] The present invention addresses a specific technical problem that arises in this environment. Heterogeneous, mutually untrusted governance telemetry sources produce records in incompatible formats, on uncoordinated time bases, and without cryptographic anchoring. Downstream actuarial, underwriting, and reserve allocation systems require deterministic, cryptographically verifiable input signals to perform automated risk calculations. The technical gap between 2026203736   14 May 2026 governance telemetry as produced and actuarial signals as required is the problem the present invention is configured to solve.

[0005] Existing systems address adjacent problems but do not solve this one. Observability platforms associated with conventional machine learning operations tooling monitor prompts, token consumption, latency, and model traces for the purpose of system performance optimisation; they do not generate cryptographically verifiable signals suitable for use by remote actuarial systems. Compliance audit systems produce narrative documentation but do not produce machine-readable signals capable of triggering automated reserve allocation. Runtime governance enforcement systems arrest execution at policy breach but do not perform the longitudinal variance modulation, anomaly correlation, or signed-signal transmission required for actuarial use.

[0006] Three specific technical sub-problems arise. First, heterogeneous telemetry sources serialise records in incompatible representations, with non-canonicalised key ordering, mixed character encodings, and uncoordinated timestamping. Second, longitudinal calculations performed on such records by different verifiers will produce non-deterministic results unless a verifierindependent arithmetic discipline is enforced. Third, even where signals are generated, they must be transmitted to remote insurer systems with cryptographic provenance sufficient for those systems to act upon them without independent verification of the upstream telemetry source.

[0007] There exists, accordingly, a need for a computer-implemented system configured to: (a) canonicalise heterogeneous governance telemetry into a deterministic schema; (b) calculate governance-conditioned variance and anomaly correlation metrics over the canonicalised records using verifier-independent arithmetic anchored to secure-enclave attested timestamps; (c) cryptographically chain the resulting metrics into an evidence registry; and (d) transmit cryptographically signed actuarial signals via a defined exchange protocol to remote insurer, reinsurer, or reserve-allocation systems.

[0008] The reference to any prior art in this specification is not, and should not be taken as, an acknowledgement or any form of suggestion that the prior art forms part of the common general knowledge in Australia or any other jurisdiction, or that 2026203736   14 May 2026 it could reasonably be expected to be ascertained, understood, and regarded as relevant by a person skilled in the relevant art. SUMMARY OF THE INVENTION

[0009] In a first aspect, the invention provides a computer-implemented system (100) for cryptographically verified actuarial risk signal generation from heterogeneous artificial intelligence governance telemetry. The system (100) comprises one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to receive heterogeneous machine-readable governance telemetry via a telemetry acquisition interface (110); canonicalise the received telemetry via a semantic harmonisation and canonicalisation plane (120) into governance-state records under a unified risk data schema (130); derive, via a quantified oversight module (140), a cognitive engagement score from input governance evidence associated with each governance-state record; calculate, via a governance-conditioned variance modulation engine (160), a governance stability coefficient over a longitudinal sliding window of the governance-state records; calculate, via an oversight conduct degradation coefficient calculator (170), a coefficient representing longitudinal degradation in human oversight conduct; calculate, via a cryptographic anomaly correlation index calculator (180), a correlation index across cryptographically chained anomaly signatures from a plurality of workflows; anchor the calculated coefficients into a cryptographic governance evidence registry (190); and transmit, via a cryptographic actuarial signal gateway (200), cryptographically signed actuarial signals to one or more remote insurer reserveallocation systems (240).

[0010] In certain embodiments, the canonicalisation operation comprises Unicode Normalisation Form C normalisation, lexicographic key sorting, and timestamp synchronisation against a hardware-attested timing source within a trusted execution environment. In further embodiments, longitudinal calculations performed by the engine and the calculators use a fixed-point arithmetic discipline configured to produce verifier-independent results. 2026203736   14 May 2026

[0011] In further embodiments, the system additionally generates an Automation Risk Score output, an Affirmative Coverage Eligibility Classification, an Insurance Cliff threshold breach indicator emitted on joint exceedance of stored oversight conduct degradation coefficient and cryptographic anomaly correlation index thresholds within a defined temporal window, and a federation benchmark output transmitted via a multi-entity governance federation interface.

[0012] In a second aspect, the invention provides a corresponding computer-implemented method. In a third aspect, the invention provides a non-transitory computer-readable medium storing instructions for performing the method.

[0013] The invention thereby converts heterogeneous, uncoordinated, and cryptographically unanchored AI governance telemetry into deterministic, cryptographically verifiable, machine-transmissible actuarial signals suitable for automated processing by remote insurer reserve-allocation systems, operational resilience systems, and capital allocation architectures. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which:

[0015] FIG. 1 is a schematic block diagram of an overall architecture of a cryptographically verified actuarial risk signal generation system according to an embodiment of the invention.

[0016] FIG. 2 is a schematic block diagram of a semantic harmonisation and canonicalisation plane according to an embodiment, illustrating Unicode NFC normalisation and lexicographic key sorting.

[0017] FIG. 3 is a schematic representation of a unified risk data schema and a secure-enclave hardware-attested timestamp synchronisation workflow.

[0018] FIG. 4 is a schematic block diagram of a governance-conditioned variance modulation engine, illustrating a longitudinal sliding-window variance calculation under a fixed-point arithmetic discipline. 2026203736   14 May 2026

[0019] FIG. 5 is a schematic flow diagram of an oversight conduct degradation coefficient calculation process.

[0020] FIG. 6 is a schematic block diagram of a quantified oversight module, illustrating cognitive engagement score derivation from input governance evidence.

[0021] FIG. 7 is a schematic representation of a cryptographic governance evidence registry comprising a SHA-256 hash chain and a Merkle tree aggregation structure with hardware-attested timestamp insertion.

[0022] FIG. 8 is a schematic block diagram of a cryptographic actuarial signal gateway and an exchange protocol transmission to a remote insurer reserveallocation system.

[0023] FIG. 9 is a schematic representation of a cryptographic anomaly correlation index calculator showing chained anomaly signatures across multiple workflows.

[0024] FIG. 10 is a schematic block diagram of a multi-entity governance federation architecture and a cross-entity benchmark exchange. DETAILED DESCRIPTION OF THE INVENTION

[0025] Referring to FIG. 1, a computer-implemented system (100) for cryptographically verified actuarial risk signal generation comprises a telemetry acquisition interface (110), a semantic harmonisation and canonicalisation plane (120), a quantified oversight module (140), a governance-conditioned variance modulation engine (160), an oversight conduct degradation coefficient calculator (170), a cryptographic anomaly correlation index calculator (180), a cryptographic governance evidence registry (190), and a cryptographic actuarial signal gateway (200). The system (100) is configured to communicate, via the gateway (200), with one or more remote insurer reserve-allocation systems (240).

[0026] The telemetry acquisition interface receives governance telemetry from one or more external governance systems. Telemetry sources may include AI workflow systems; runtime governance systems; agentic orchestration systems; human review systems; governance artifact systems; enterprise workflow systems; 2026203736   14 May 2026 forensic replay systems; operational resilience systems; or insurer telemetry systems.

[0027] The present invention is not directed to telemetry interception mechanics themselves. Telemetry is received as machine-readable input for cryptographic verification, canonicalisation, longitudinal calculation, and signed-signal transmission. The novelty of the present invention resides in the verification, calculation, and transmission pipeline, not in the means by which the input telemetry is captured at source.

[0028] Input telemetry may include: reviewer identifiers; review timestamps; Edit Delta records derived from a Levenshtein-based cognitive engagement calculation performed by an upstream Verifiable Human Contribution system; review duration telemetry; escalation telemetry; execution interruption telemetry; governance silence events derived from an upstream telemetry-absence detection system; policy verification states; dissemination authorisation states; and cryptographic governance records derived from an upstream cryptographic governance state verification system.

[0029] Referring to FIG. 2 and FIG. 3, the semantic harmonisation and canonicalisation plane (120) transforms heterogeneous input telemetry into governance-state records under a unified risk data schema (130). The plane (120) performs a canonicalisation operation that produces byte-identical records from semantically equivalent inputs originating from heterogeneous source systems, such that downstream cryptographic operations produce deterministic, verifierindependent results.

[0030] The canonicalisation operation comprises Unicode Normalisation Form C (NFC) normalisation performed by a normaliser (121) of all string fields; lexicographic key sorting performed by a key sorter (122) within nested object structures; deterministic serialisation of numeric values; explicit type tagging; and timestamp synchronisation against a secure-enclave hardware-attested timing source provided by a trusted execution environment (123) and a hardware-attested timestamp generator (124). The output is a unified risk data schema record (130). 2026203736   14 May 2026

[0031] In certain embodiments, the trusted execution environment (123) performs remote attestation using hardware attestation primitives, including but not limited to trusted-platform-module or equivalent secure-enclave standards. The trusted execution environment (123) produces a hardware-bound timestamp signature that is appended to each unified risk data schema record (130). The timestamp signature, when later verified, defeats retroactive governance record fabrication: a record lacking a verifiable hardware-attested timestamp signature is treated as non-canonical and excluded from downstream calculations.

[0032] In further embodiments, the canonicalisation plane assigns a record-type classification to each unified risk data schema record, drawn from a defined ontology of governance-state types including verification records, authorisation records, anomaly records, escalation records, silence records, dissemination records, and other defined categories. Classification is performed by a deterministic rule-based classifier, the rules of which are themselves recorded under a versioned identifier in the evidence registry, such that classification decisions are reproducible by independent verifiers.

[0033] Referring to FIG. 6, the quantified oversight module (140) derives a cognitive engagement score (141) from input governance evidence. In a preferred embodiment, the cognitive engagement score (141) is derived from a normalised Levenshtein distance between a machine-generated output and a human-finalised output. The Levenshtein-based calculation may be performed within the module (140) from raw input pairs, or may be received as a pre-calculated Edit Delta value from an upstream Verifiable Human Contribution system.

[0034] Where the calculation is performed within the module, the cognitive engagement score is calculated as: AE = 1 - AL (O_AI, O_H) / max( / O_AI / , / OH / )

[0035] Where A_L denotes the Levenshtein distance between the machinegenerated output O_AI and the human-finalised output O_H; and |-| denotes character length. The result A_E is bounded in the closed interval from zero to one.

[0036] The quantified oversight module (140) may enforce minimum cognitive engagement thresholds prior to admitting a record for further processing. Where 2026203736   14 May 2026 △_E falls below a configured threshold, the record may be flagged as a passivereview anomaly and routed to an anomaly signature chain (181). The cognitive engagement score, once derived or admitted, is bound to the unified risk data schema record (130) by SHA-256 hash incorporation into the record's cryptographic envelope. The bound score becomes an input to the governance-conditioned variance modulation engine (160) and the oversight conduct degradation coefficient calculator (170).

[0037] In embodiments operable with upstream Verifiable Human Contribution systems, the system (100) receives a five-stage session log (150) per AI-assisted output, comprising Create, Edit, Review, Approve, and Disseminate stages. Each stage carries a timestamped cryptographic signature and a hash-linked record element. The five-stage session log (150) is treated as input governance evidence and is not the inventive subject matter of the present application.

[0038] Referring to FIG. 4, the governance-conditioned variance modulation engine (160) calculates a governance stability coefficient (163) over a longitudinal sliding window (161) of unified risk data schema records (130). The governance stability coefficient (163) is the central output of the engine (160) and is an input to the cryptographic actuarial signal gateway (200) for actuarial signal generation.

[0039] In a preferred embodiment, the governance stability coefficient (163) is calculated as a variance-modulation function of (i) the longitudinal series of cognitive engagement scores bound to unified risk data schema records within the window (161); (ii) the longitudinal series of authorisation compliance indicators; and (iii) the longitudinal series of dissemination authorisation states. The function is computed by a fixed-point arithmetic unit (162) using Q16.16 fixed-point arithmetic, such that any verifier independently performing the same calculation on the same record series will obtain a byte-identical coefficient value.

[0040] The use of fixed-point arithmetic in this calculation is a deliberate engineering choice with a particular technical effect. Floating-point operations across heterogeneous hardware produce small but non-zero differences in leastsignificant bits, which would prevent independent verifiers from reproducing the coefficient value bit-exactly. Q16.16 fixed-point arithmetic eliminates this divergence and is one of the technical means by which the present invention 2026203736   14 May 2026 produces deterministic, cryptographically signable output signals from non-deterministic input streams.

[0041] The governance stability coefficient (163) may be decomposed into subcoefficients including a governance entropy metric calculated as a normalised Shannon entropy over the categorical distribution of governance-state record types in the window; a longitudinal consistency coefficient; and a hardware-attested timestamp continuity coefficient. Each sub-coefficient is bound to the window (161) by cryptographic hash incorporation.

[0042] Referring to FIG. 5, the oversight conduct degradation coefficient calculator (170) computes a coefficient representing longitudinal degradation in human oversight conduct across the unified risk data schema record stream (130). The coefficient computed by the calculator (170) is explicitly directed to degradation in human oversight conduct, and is distinguished from any metric that measures behavioural deviation of an artificial intelligence agent from a baseline.

[0043] Indicators of oversight conduct degradation incorporated into the coefficient may include: a declining trend in cognitive engagement scores within a use-case category over a sliding longitudinal window; a declining trend in review duration; an increase in the rate of cognitive engagement scores below a configured threshold; an increase in governance silence events as recorded by an upstream telemetry-absence detection system; escalation suppression patterns; and an increase in autonomous execution frequency unaccompanied by oversight records.

[0044] Each indicator is calculated using the fixed-point arithmetic discipline performed by the fixed-point arithmetic unit (162) and is bound to the unified risk data schema window (161) by SHA-256 hash incorporation. The coefficient is then derived as a weighted aggregation of the indicators, the weights themselves being recorded under a versioned identifier in the evidence registry (190) such that the calculation is reproducible by independent verifiers.

[0045] Where the oversight conduct degradation coefficient (170) exceeds a stored configuration threshold, the cryptographic actuarial signal gateway (200) may emit a coverage capacity restriction signal, an underwriting reassessment signal, or an operational resilience escalation signal. The emitted signal includes 2026203736   14 May 2026 the coefficient value, the unified risk data schema window identifier, and a cryptographic signature over the combined payload.

[0046] Governance silence—the absence of expected governance telemetry over a defined interval, as recorded by an upstream telemetry-absence detection system—is incorporated as a primary input to the oversight conduct degradation coefficient. The treatment of telemetry silence as a positive risk signal is consistent with the inversion-logic governance approach of related portfolio applications and is incorporated into the present invention via input integration only; the silencedetection mechanism itself is not the inventive subject matter of the present application.

[0047] Referring to FIG. 9, the cryptographic anomaly correlation index calculator (180) computes a correlation index across cryptographically chained anomaly signatures from a plurality of workflows. The index computed by the calculator (180) is distinct from any metric that measures volume of AI-assisted outputs over a time window. The index measures the cryptographic correlation of anomaly signatures, not the volume of outputs.

[0048] An anomaly signature, in the present invention, is a SHA-256 hash computed over a defined tuple of fields drawn from an anomaly-classified unified risk data schema record. Anomaly signatures are appended to a per-workflow anomaly chain (181), the chain head being incorporated into the cryptographic governance evidence registry (190). Correlation across workflows is computed by detecting common signature prefixes, common feature-tuple values within signatures, and temporal proximity of anomaly chain extensions across workflow chains.

[0049] In a preferred embodiment, the index is calculated as a normalised count of cross-workflow signature correlations within a longitudinal window (161), weighted by the cryptographic confidence of the correlation, the weighting reflecting whether the correlation derives from identical signatures, prefix-matched signatures, or feature-tuple-matched signatures. Calculation uses the fixed-point arithmetic unit (162) to produce verifier-independent results.

[0050] Where the index exceeds a stored configuration threshold, the system (100) identifies a candidate systemic anomaly event and emits a signal to the 2026203736   14 May 2026 cryptographic actuarial signal gateway (200). The signal includes the index value, the set of correlated workflow identifiers, the matched signature prefixes, and a cryptographic signature over the combined payload. The receiving insurer reserveallocation system (240), on receipt of the signal, may perform automated reserve adjustment in respect of the correlated workflow set.

[0051] The cryptographic anomaly correlation index (180) is operationally complementary to the oversight conduct degradation coefficient (170). The coefficient (170) measures longitudinal degradation within a workflow or entity; the index (180) measures correlated anomaly behaviour across workflows or entities. Joint exceedance—both the coefficient (170) and the index (180) exceeding their respective thresholds within a defined temporal window—triggers an Insurance Cliff threshold breach indicator.

[0052] Referring to FIG. 7, the cryptographic governance evidence registry (190) stores all unified risk data schema records, derived coefficients, anomaly signatures, signal certificates, and configuration version identifiers used in the operation of the system (100). The registry (190) is append-only and tamper-evident.

[0053] Each entry in the registry (190) is anchored by a SHA-256 hash chain (191) and aggregated under a Merkle tree aggregator (192). Periodic Merkle root hashes are emitted to a trusted publication channel at configured time intervals, such that the integrity of the registry (190) is independently verifiable without disclosure of registry contents.

[0054] Configuration version identifiers—covering classifier rules, weighting schemes, threshold values, and arithmetic disciplines—are themselves recorded in the registry (190) and hash-bound to the unified risk data schema records they govern. This binding enables independent verifiers to reproduce all derived calculations bit-exactly from the registry contents and the configuration version identifier alone.

[0055] Referring to FIG. 8, the cryptographic actuarial signal gateway (200) generates signed actuarial signals from the governance stability coefficient (163), the oversight conduct degradation coefficient (170), and the cryptographic anomaly correlation index (180) outputs, and transmits them via a defined 2026203736   14 May 2026 exchange protocol (220) to remote actuarial, underwriting, reserve allocation, or operational resilience systems (240).

[0056] Each signal comprises: a unified risk data schema window identifier; a configuration version identifier; one or more of the coefficient values and derived classifications; a hardware-attested timestamp; and a cryptographic signature over the foregoing payload.

[0057] The cryptographic signature is generated by a signing module (210) using a private signing key bound to the issuing system within a secure enclave. The corresponding public key is published by the issuing system via a transparency channel, such that any receiving insurer system (240) may independently verify the signature without out-of-band coordination with the issuer.

[0058] Transmission uses the defined governance-risk exchange protocol (220). In a preferred embodiment, the protocol (220) comprises a structured requestresponse interaction over a secure transport channel using mutually authenticated transport layer security, with request payloads conforming to a published schema and responses returning a receipt acknowledgement signed by the receiving system. A receipt acknowledgement handler (230) records the signed receipt acknowledgement in the cryptographic governance evidence registry (190) prior to recording successful transmission. The protocol (220) is differentiated from generic application programming interface transmission by the cryptographic signing, configuration version binding, and receipt-acknowledgement requirements.

[0059] The cryptographic actuarial signal gateway is thereby the technical mechanism by which deterministic, cryptographically verifiable signals produced from heterogeneous AI governance telemetry are made available to remote insurer reserve-allocation systems. The gateway is not itself an actuarial calculation engine; the actuarial calculation remains the function of the receiving insurer system. The gateway produces the cryptographically verifiable input the receiving system requires in order to perform that calculation with deterministic provenance.

[0060] Signal outputs that may be generated by the cryptographic actuarial signal gateway include the following. An Automation Risk Score output, derived from the 2026203736   14 May 2026 governance stability coefficient, the oversight conduct degradation coefficient, and the cryptographic anomaly correlation index via a defined aggregation function, the aggregation function itself being recorded under a versioned identifier in the evidence registry. An Affirmative Coverage Eligibility Classification, comprising a categorical classification such as eligible, conditional, or ineligible, generated by a deterministic rule applied to the coefficient and index values against stored configuration thresholds. An Insurance Cliff threshold breach indicator, comprising a binary signal emitted on joint exceedance of stored oversight conduct degradation coefficient and cryptographic anomaly correlation index thresholds within a defined temporal window. A reserve allocation recommendation, comprising a structured recommendation payload comprising target reserve adjustment direction and a confidence measure derived from the variance modulation calculation. An underwriting reassessment trigger, indicating that one or more configured underwriting parameters should be re-evaluated by the receiving insurer system. An operational resilience escalation signal, indicating that operational resilience monitoring should be intensified in respect of the unified risk data schema window source.

[0061] Referring to FIG. 10, in federated embodiments a plurality of instances of the system (100), each operating in respect of a distinct enterprise entity, may exchange anonymised benchmark outputs via a multi-entity governance federation interface (300) in communication with a federation aggregator (310). The federation architecture is configured to enable cross-entity benchmark calculation without disclosure of underlying governance telemetry, unified risk data schema records, configuration version identifiers, or signal payloads.

[0062] Each participating instance contributes to the federation aggregator (310): (i) a periodic anonymised summary statistic over its governance stability coefficient, oversight conduct degradation coefficient, and cryptographic anomaly correlation index outputs; (ii) a cryptographic commitment to the underlying unified risk data schema window; and (iii) a participation signature. The federation aggregator (310) computes cross-entity benchmark statistics over the contributed summary statistics and returns the resulting benchmark to participating instances. The aggregator (310) does not have access to underlying records, configuration 2026203736   14 May 2026 version identifiers, or signal payloads, and so cannot reconstruct entity-specific governance conduct from the federation output.

[0063] Federation benchmarks may be used by participating instances as inputs to the Affirmative Coverage Eligibility Classification and may be transmitted via the cryptographic actuarial signal gateway (200) to receiving insurer systems (240) as cross-entity context.

[0064] Throughout this specification, the word "comprise", and variations such as "comprises" and "comprising", will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps.

[0065] It will be understood by those skilled in the art that the invention is not restricted to the details of the foregoing embodiments. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

Claims

1. A computer-implemented system for cryptographically verified actuarial risk signal generation from heterogeneous artificial intelligence governance telemetry, the system comprising one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to:(a) receive, via a telemetry acquisition interface, heterogeneous machine-readable governance telemetry from a plurality of source systems associated with one or more artificial intelligence workflows;(b) canonicalise, via a semantic harmonisation and canonicalisation plane, the received telemetry into governance-state records under a unified risk data schema, the canonicalisation comprising Unicode Normalisation Form C normalisation, lexicographic key sorting, and timestamp synchronisation against a hardware-attested timing source within a trusted execution environment, the resulting governance-state records each being bound to a hardware-attested timestamp signature;(c) derive, via a quantified oversight module, a cognitive engagement score from input governance evidence associated with each governance-state record, and bind the cognitive engagement score to the respective governance-state record by cryptographic hash incorporation;(d) calculate, via a governance-conditioned variance modulation engine, a governance stability coefficient over a longitudinal sliding window of the governance-state records, the longitudinal sliding window having a longitudinal window identifier, the calculation being performed by a fixed-point arithmetic unit using a Q16.16 fixed-point arithmetic discipline, the calculation producing a byte-identical governance stability coefficient value when independently performed on the same governance-state record series;(e) calculate, via an oversight conduct degradation coefficient calculator, a coefficient representing longitudinal degradation in human oversight conduct across the governancestate records, the coefficient being calculated using the Q16.16 fixed-point arithmetic discipline and bound to the longitudinal window by cryptographic hash incorporation;(f) calculate, via a cryptographic anomaly correlation index calculator, a correlation index across cryptographically chained anomaly signatures derived from anomaly-classified governance-state records originating from a plurality of workflows, the correlation index being calculated using the Q16.16 fixed-point arithmetic discipline;(g) anchor the governance stability coefficient, the oversight conduct degradation coefficient and the cryptographic anomaly correlation index (collectively, calculated coefficients), the anomaly signatures, and a configuration version identifier into a cryptographic governance evidence registry comprising a SHA-256 hash chain aggregated under a Merkle tree structure, the cryptographic governance evidence registry being append-only and tamper-evident and being configured to emit periodic Merkle root hashes to a trusted publication channel such that integrity of the cryptographic governance evidence registry is independently verifiable without disclosure of registry contents; and(h) generate and transmit, via a cryptographic actuarial signal gateway, one or more cryptographically signed actuarial signals to one or more remote insurer reserve-allocation systems, each signal comprising the longitudinal window identifier, the configuration version identifier, one or more of the calculated coefficients or derived classifications, a hardware-attested timestamp, and a cryptographic signature over the foregoing payload, transmitted via a defined exchange protocol producing a signed receipt acknowledgement.2026203736   26 Aug 20262. The system of claim 1, wherein the cognitive engagement score is derived from a normalised Levenshtein distance between a machine-generated output and a human-finalised output.

3. The system of claim 1, wherein the trusted execution environment performs remote attestation prior to issuing a hardware-attested timestamp signature, and wherein governancestate records lacking a verifiable hardware-attested timestamp signature are excluded from downstream calculations.

4. The system of claim 1, wherein the governance stability coefficient is decomposed into at least a governance entropy sub-coefficient calculated as a normalised Shannon entropy over a categorical distribution of governance-state record types within the longitudinal window.

5. The system of claim 1, wherein indicators incorporated into the oversight conduct degradation coefficient include a governance silence indicator derived from absence of expected telemetry over a defined interval as recorded by an upstream telemetry-absence detection system.

6. The system of claim 1, wherein the cryptographic anomaly correlation index is calculated by detecting cross-workflow correlations comprising at least one of: identical anomaly signature matches; signature prefix matches; and feature-tuple matches within signatures, weighted by cryptographic confidence.

7. The system of claim 1, wherein the cryptographic actuarial signal gateway is configured to generate an Insurance Cliff threshold breach indicator when the oversight conduct degradation coefficient exceeds a stored capacity-restriction value concurrently with a cryptographic anomaly correlation index exceedance within a defined temporal window.

8. The system of claim 1, wherein the cryptographic actuarial signal gateway is configured to generate an Automation Risk Score output derived from the governance stability coefficient, the oversight conduct degradation coefficient, and the cryptographic anomaly correlation index via a versioned aggregation function recorded in the cryptographic governance evidence registry.

9. The system of claim 1, wherein the cryptographic actuarial signal gateway transmits signals via a mutually authenticated transport channel and requires a cryptographically signed receipt acknowledgement from the receiving system prior to recording successful transmission in the cryptographic governance evidence registry.

10. The system of claim 1, further comprising a multi-entity governance federation interface configured to contribute anonymised summary statistics derived from the calculated coefficients to a federation aggregator and to receive cross-entity benchmark outputs in return, without disclosure of underlying governance-state records, configuration version identifiers, or signal payloads to the aggregator.

11. The system of claim 1, wherein the cognitive engagement score is received as a precalculated input from an upstream Verifiable Human Contribution system implementing a five-stage session log structure comprising create, edit, review, approve, and disseminate stages.2026203736   26 Aug 202612. A computer-implemented method for cryptographically verified actuarial risk signal generation from heterogeneous artificial intelligence governance telemetry, the method comprising:(a) receiving heterogeneous machine-readable governance telemetry from a plurality of source systems associated with one or more artificial intelligence workflows;(b) canonicalising the received telemetry into governance-state records under a unified risk data schema using Unicode Normalisation Form C normalisation, lexicographic key sorting, and timestamp synchronisation against a hardware-attested timing source within a trusted execution environment, the resulting governance-state records each being bound to a hardware-attested timestamp signature;(c) deriving and binding a cognitive engagement score to each governance-state record by cryptographic hash incorporation;(d) calculating, by a fixed-point arithmetic unit using a Q16.16 fixed-point arithmetic discipline, a governance stability coefficient, an oversight conduct degradation coefficient, and a cryptographic anomaly correlation index (collectively, calculated coefficients) over a longitudinal sliding window of the governance-state records, the longitudinal sliding window having a longitudinal window identifier, the calculation producing a byteidentical governance stability coefficient value when independently performed on the same governance-state record series;(e) anchoring the calculated coefficients and a configuration version identifier into a SHA-256 hash chain aggregated under a Merkle tree structure of an append-only, tamper-evident cryptographic governance evidence registry, and emitting periodic Merkle root hashes to a trusted publication channel such that integrity of the cryptographic governance evidence registry is independently verifiable without disclosure of registry contents; and(f) generating and transmitting one or more cryptographically signed actuarial signals to one or more remote insurer reserve-allocation systems via a defined exchange protocol producing a signed receipt acknowledgement, wherein each of the one or more cryptographically signed actuarial signals comprises the longitudinal window identifier, the configuration version identifier, one or more of the calculated coefficients, a hardware-attested timestamp, and a cryptographic signature over the foregoing payload.

13. The method of claim 12, wherein the calculating step further comprises generating an Insurance Cliff threshold breach indicator on joint exceedance of stored oversight conduct degradation coefficient and cryptographic anomaly correlation index thresholds within a defined temporal window.

14. A non-transitory computer-readable medium storing instructions which, when executed by one or more processors, cause the processors to perform the method of claim 12.

Images