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SS2/25: Prudential considerations for insurance and reinsurance undertakings when transferring risk to Special Purpose Vehicles

Supervisory statement 2/25

AI Analysis

Supervisory Statement SS2/25 from the Prudential Regulation Authority (PRA) provides guidance on prudential considerations for UK insurance and reinsurance undertakings transferring risk to Special Purpose Vehicles (SPVs). It clarifies expectations for ensuring such transfers comply with Solvency II requirements, focusing on risk transfer validity, capital relief recognition, and supervisory approval processes. This matters because it aims to enhance transparency and risk management in reinsurance arrangements, reducing potential regulatory arbitrage while supporting efficient risk mitigation for insurers amid evolving market dynamics. #

Insurance

SS5/25 โ€“ Enhancing banksโ€™ and insurersโ€™ approaches to managing climate-related risks

Supervisory statement 5/25

AI Analysis

SS5/25 is the PRA's updated supervisory statement, published on 3 December 2025, replacing SS3/19 and setting enhanced expectations for banks and insurers to manage climate-related risks through governance, risk management, scenario analysis, data quality, and disclosures. It matters because it represents a step change from awareness-raising to embedding robust, proportionate practices that integrate climate risks into core prudential processes like ICAAP, ILAAP, ORSA, and capital planning, aligning with the PRA's objectives for firm safety and soundness amid evolving physical and transition risks. #

BankInsurance

The PRA holds model risk management roundtable on artificial intelligence and machine learning technologies

The PRA held roundtable meetings on artificial intelligence and machine learning (AI and ML) in the context of Supervisory Statement (SS)1/23 โ€˜Model risk management principles for banksโ€™

AI Analysis

The Prudential Regulation Authority (PRA) held roundtable sessions on 20 and 22 October 2025 with 21 regulated firms to discuss AI and machine learning (AI/ML) adoption under Supervisory Statement SS1/23 on model risk management (MRM) principles for banks. This matters because it highlights PRA's strategic supervisory focus on AI/ML model risks, urging firms to enhance governance, risk appetite, monitoring, and validation to mitigate opacity, overfitting, and rapid performance degradation in these models. https://www.bankofengland.co.uk/prudential-regulation/publication/2025/november/pra-holds-model-risk-management-roundtable-on-ai | https://www.bankofengland.co.uk/-/media/boe/files/prudential-regulation/publication/2025/november/ai-roundtable-oct-2025.pdf #

BankAll Firms

SS31/15 - The Internal Capital Adequacy Assessment Process (ICAAP) and the Supervisory Review and Evaluation Process (SREP)

Supervisory statement 31/15

AI Analysis

SS31/15 is the PRA's foundational supervisory statement establishing expectations for how UK-regulated banks and large investment firms must conduct their Internal Capital Adequacy Assessment Process (ICAAP) and how the PRA will evaluate these assessments through its Supervisory Review and Evaluation Process (SREP). This guidance is critical because it directly determines the capital requirements firms must maintain and establishes the supervisory framework through which the PRA assesses whether firms hold sufficient capital to cover material risks.

BankBroker Dealer

SS15/16 โ€“ Solvency II: Monitoring model drift and standard formula SCR reporting for firms with permission to use an internal model

Supervisory Statement 15/16

AI Analysis

SS15/16 establishes the PRA's expectations for UK insurance firms using approved internal models to calculate their Solvency Capital Requirement (SCR), requiring them to maintain the ability to calculate SCR using the standard formula and submit standard formula SCR calculations for regulatory monitoring purposes. This guidance is critical because it ensures capital requirements remain reflective of actual firm risks and protects policyholder security by preventing model driftโ€”where internal models diverge from underlying risk realities over time.

Insurance