2024 SOA Seoul Seminar

Actuarial Model Validation, Governance, and Control

On September 26, 2024, I had the privilege of speaking at the SOA Seoul Seminar, where I shared my insights on a topic that has moved from the back office to the boardroom: Actuarial Model Validation, Governance, and Control.

In the current regulatory landscape, particularly with the full implementation of IFRS 17 and K-ICS (Korea-Insurance Capital Standard), the actuarial model is no longer just a calculation engine—it is the heartbeat of an insurance company’s financial reporting and solvency management.

The Shifting Paradigm: Why Governance Matters Now

Historically, model governance was often viewed as a compliance “check-the-box” exercise. However, the complexity introduced by IFRS 17 and K-ICS has fundamentally changed the stakes. These frameworks demand high-frequency, granular projections and sophisticated stochastic modeling, leaving zero room for “black box” processes.

Effective governance today serves three critical functions:

1. Risk Mitigation and Accuracy: In a world of market-consistent valuations, a minor error in a discount rate curve or a mortality assumption can lead to massive volatility in the Contractual Service Margin (CSM) or available capital. Robust governance provides the guardrails to prevent these fiscal shocks.
2. Operational Efficiency: As models become more complex, they also become more resource-intensive. Streamlined governance—incorporating automated testing and clear version control—reduces the manual burden on actuarial teams, allowing them to focus on analysis rather than troubleshooting.
3. Strategic Decision-Making: Models are the primary tools for steering a company’s product strategy and asset-liability management. If the leadership cannot trust the model output due to weak governance, the entire strategic direction of the firm is at risk.

The Pillars of a Robust Governance Framework

During the seminar, we explored what “robustness” looks like in practice. It isn’t just about more documentation; it’s about a holistic ecosystem:

• Inventory & Documentation: Maintaining a comprehensive “Model Map” that tracks every model’s purpose, owner, and dependencies.
• Change Management: Strict protocols for when and how model logic is updated, ensuring every change is peer-reviewed and impact-tested.
• Validation & Peer Review: Independent validation (internal or external) to challenge the underlying assumptions and methodology.
• Data Integrity: Ensuring that the “garbage in, garbage out” rule is addressed at the source through rigorous data ETL (Extract, Transform, Load) controls.