Managing risk for portfolios that combine physical assets with digital assets requires reconciling distinct threat profiles, valuation methods, custody arrangements, and regulatory regimes. Effective risk modelling blends statistical methods with operational assessment: scenario analysis for systemic shocks, probabilistic loss distributions for market and cyber events, and control testing for custody and governance. Underwriting and pricing must reflect these combined exposures so protection and coverage remain robust across possible loss scenarios while maintaining auditability and regulatory compliance.

How do protection and coverage apply to mixed assets?

Protection and coverage language should explicitly address the different triggers and loss types for physical versus digital assets. Physical items are exposed to theft, damage, and natural perils; digital assets face cyber-theft, smart-contract vulnerabilities, and protocol failures. Policies need clear definitions for custody requirements, covered events, and sublimits that prevent duplication or unintended gaps. Scenario-based stress tests help identify tail risks where both asset classes are affected simultaneously—for example, a cyber event that disrupts logistics—so coverage structures can be designed to avoid coverage cliffs.

How are claims and underwriting affected?

Claims processes differ materially between asset types. For digital assets, forensic evidence often relies on immutable ledger records, transaction histories, and forensic analysis of key management. For physical assets, loss assessment depends on appraisals, surveys, and physical inspections. Underwriting therefore requires richer data: custody practices, key-holding policies, multisig setups, provenance records, maintenance logs, and security controls. Integrating these inputs into underwriting models improves loss frequency and severity estimates and reduces disputes at claims time.

How are premiums and liability modelled?

Premium-setting blends actuarial inputs for traditional perils with stochastic modelling for cyber and market volatility of digital assets. Liability assessments must include third-party exposures, platform counterparty risk, and compliance-related fines. Combined stress testing—such as simultaneous market drops and cyber incidents—helps quantify aggregate capital needs and informs premium loadings. Premium models should also capture governance quality and operational resilience, applying surcharges or discounts based on control maturity and documented custody practices.

How is custody and valuation handled?

Custody differs for physical and digital holdings. Physical custody concerns warehousing, transport security, and chain-of-custody documentation. Digital custody involves private key management, hardware security modules, multisig arrangements, and custodial service counterparty risk. Valuation must account for digital asset price volatility, market fragmentation, and liquidity depth, while physical asset valuation focuses on replacement, repair, and provenance. Reliable valuation frameworks combine market feeds, independent appraisals, and liquidity-adjusted pricing to support reserves and claims settlement.

How do compliance and regulation influence models?

Compliance and regulation affect permissible custody structures, reporting requirements, and liability allocation across jurisdictions. Cross-border holdings introduce additional complexity: differing legal treatment of digital assets, tax rules, and disclosure obligations can change risk exposures. Models should incorporate regulatory scenarios, capital requirement impacts, and potential changes in custody law. Embedding regulatory checkpoints in model governance ensures that compliance shifts are reflected in underwriting criteria, coverage definitions, and reserve calculations.

How are governance and auditability ensured for mixed holdings?

Governance frameworks must cover lifecycle controls for both physical and digital assets: procurement, custody handoffs, transaction authorization, incident response, and recordkeeping. Auditability relies on immutable transaction logs for digital assets and chain-of-custody records for physical items. Risk management processes should be transparent with versioned models, validation routines, and documented assumptions to enable internal and external audits. Strong governance reduces dispute risk and supports more accurate pricing by demonstrating the controls that materially lower the probability of loss.

Conclusion Risk modelling for mixed physical and digital asset exposure requires a hybrid approach that integrates actuarial techniques, cyber risk modelling, operational control assessment, and regulatory scenario planning. Clear policy language for protection and coverage, disciplined underwriting informed by custody and valuation practices, and governance that ensures auditability and compliance together enable insurers and asset holders to quantify and manage combined exposures effectively.