Balanced for Growth

Note: This article uses Ping An Life Insurance Company, referred to as “the company,” for analysis. The practices described may differ from those of other life insurance companies and are intended solely for industry discussion.

In recent years, asset-liability management (ALM) has gradually become a central concern in the insurance industry. Over the past few years, China’s sustained interest rate declines have brought pressure to the life insurance sector. In response, insurance companies have been striving to enhance their ALM capabilities to respond to challenges in a changing market and support sustainable long-term growth.

INSURERS AND THE NEED FOR STRONG ALM

At present, the asset side of the insurance industry faces considerable pressure. Macroeconomic conditions and falling market interest rates have continued to depress yields on new investments, posing a challenge to industry development.

At the same time, under regulatory guidance, the liability side is undergoing a series of structural adjustments. The industry is entering a new landscape for optimizing liability structures and controlling costs.

Regulatory guidance has played a pivotal role in optimizing the industry’s cost structure and improving operational efficiency. In recent years, the gradual reduction of pricing interest rates and the establishment of a dynamic adjustment mechanism have effectively lowered industry liability costs.¹

Following the implementation of the requirements that insurers’ actual practices align with their regulatory filings, insurance pricing has become significantly more refined, the overall expense structure has continued to improve, and the actual risk level borne by the liability side has declined accordingly. Regulatory guidance on participating product dividend rates and universal life crediting interest rates has also yielded tangible results in driving industry cost control. These changes have improved liability quality and strengthened overall risk resilience. Therefore, in the current environment, strengthening liability-side product management has become a key component of sound industry operations.²

Historical data indicate that prior to 2023, mainstream insurance products were predominantly traditional; most products carried an assumed pricing interest rate of 3.5%.³ Combined with pressure on new investment yields due to declining market interest rates, some companies experienced negative interest spreads. After 2023, the 750-day moving average interest rate (of a particular government-bond yield) continued to decline. The liability, or duration cycle, for traditional long-term policies underwritten between 2013 and 2023 is expected to extend to 2033, with an overall duration of up to 20 years. Products priced at 3.5% in the past have created fixed, long-term pressure on liability costs.

Against this backdrop, ALM is of critical importance to corporate strategic planning and long-term development. Differences in investment yields among companies are reflected not only in financial statements but also in deeper disparities in ALM and risk-pricing capabilities. From an operational standpoint, coordination among business lines on the asset and liability sides—namely, the investment center and product center—has been further strengthened, ensuring more effective asset-liability matching. The fact that new investment yields remain above the new business breakeven yield reflects more disciplined management and stronger cross-functional coordination.

At an operational level, ALM focuses on strengthening duration matching, cost-benefit matching, and cash flow matching. Its core objective, however, is to balance the company’s long-term interests while meeting solvency requirements, achieving a dynamic equilibrium between short-term stability and long-term sustainable development. This is not only a comprehensive test of a company’s technical and managerial capabilities but also a thorough examination of its strategic resolve and risk awareness.

AN ALM GOVERNANCE FRAMEWORK

The effective implementation of ALM first relies on sound top-level design. This system encompasses the establishment of organizational structures, the development of quantitative models, the setting of indicator systems and the coordination mechanisms for multi-departmental collaboration.

Currently, regulators and various industry parties are actively studying relevant measures to move ALM from concept to practice. In this process, the company has organized several special seminars with core functional departments such as investment, product, actuarial, and risk management, and is actively exploring an operating model under third-party coordination. Entrusting ALM responsibilities to an independent department or a third-party coordinator helps achieve balance across business lines and avoid path dependency and interest bias that can result from domination by a single asset- or liability-side department. This mode may serve as a reference for the next phase of organizational optimization and functional adjustment within companies.

In practical professional consulting, the focus is typically on analyzing core financial indicators and developing related system capabilities. Their mature methodologies and extensive experience are key to enhancing the industry’s ALM capabilities. Under the current implementation framework, the asset side has established a relatively mature asset allocation system, while the liability side and product design side have gradually built corresponding management mechanisms. The overall architecture remains consistent with the asset allocation system’s management logic.

On the liability side, the company has established a three-tier product strategy mechanism. Drawing reference from the asset allocation system, and through the construction of the company three-tier framework of TOP SAA → SAA → TAA (where TOP SAA denotes Product Strategy Meeting; SAA denotes Product Strategic Meeting; and TAA denotes Product Tactical Meeting—these terms are referenced from the asset allocation system, in which SAA stands for Strategic Asset Allocation and TAA for Tactical Asset Allocation) as well as the upgrading of product R&D mechanisms, the company, starting from long-term sound operations, focuses on the current year’s product strategy. It dynamically formulates period-specific product strategies and optimization directions by integrating market conditions, sales channel capabilities and market outlook. This process is characterized by high flexibility and continuous iteration.

At the same time, ALM must be implemented through the refined management of core elements. By focusing on key control points of each core indicator and implementing targeted measures for different dimensions, management effectiveness can be enhanced. For example, Contractual Service Margin (CSM) should serve as a core lever for liability management, requiring the decomposition of key variables by different channels and the implementation of differentiated strategies.

The construction of the ALM system not only reflects a comprehensive consideration of risk and return but also demonstrates a company’s capabilities in strategic planning, resource allocation and refined operations. It is an important support system for promoting high-quality development.

BUILDING AND REFINING THE ALM MODEL

The construction and optimization of the ALM model are shared priorities across the industry. Various companies have explored a range of approaches in model building, accumulated extensive implementation experience, and provided useful models and lessons for the industry.

Taking the company as an example, prior to 2004–2005, it had already built an ALM model for the domestic market. However, due to the model’s structural complexity, it took professional actuaries a year to gain a preliminary understanding and operational proficiency. Subsequently, owing to the heavy burden of day-to-day management work and technical failures encountered during model operations, the model was phased out. This experience highlights a core tension in model building: how to strike an effective balance between technical sophistication and operational usability.

Efforts to localize software and reduce reliance on external technologies put the industry in a strong position to reconsider the design principles and future direction of ALM models. Approaches vary across markets. Because Hong Kong’s insurance product structure resembles that of mainland China, its relatively comprehensive ALM model may offer useful practical guidance. Some developed markets emphasize capital efficiency, orienting their models toward Solvency II or economic capital management. Other institutions center their models on profit forecasting, which may not fully support integrated asset and liability decision-making.

Therefore, during model construction, it is essential to strike an optimal balance between “actuarial precision” and “computational efficiency” and to determine the model’s functional boundaries and the level of detail needed for management decisions, given the company’s development stage, product complexity and data foundation. This is also a key issue that requires focused attention and continuous optimization in practice.

Another challenge currently facing the industry stems from the rapid development of artificial intelligence. If the ALM model cannot achieve dynamic optimization and respond promptly to market changes and business adjustments, it may raise doubts among management about the model’s practicality. In this context, model validation becomes particularly important. It is necessary to establish a regular variance analysis process, promptly correct deviations between model assumptions and actual outcomes, fully incorporate feedback from frontline business units and management, and ensure that the model clearly reflects trend fluctuations rather than merely capturing short-term opportunities or fitting historical data. This is also an area that requires continuous exploration in the model iteration process.

From a management perspective, ALM is a systemic endeavor. It encompasses long-term goal setting, short-term strategy formulation, model operation and simulation, optimization and selection of asset-liability plans, and extends to data support and system implementation, which ideally forms an integrated management cycle with a regular feedback loop. Specifically, based on clearly defined long-term operating objectives, core variables such as business, investment, and product strategies should be incorporated into the model framework.

When combined with liability-side cash flow projections and asset-side yield curves, the model outputs key indicators across different scenarios. By comparing alternative plans, the optimal strategy combination is determined and ultimately integrated into operational decisions. Within this closed loop, the linkage effect of account management for float-return products (participating and universal life insurance) is relatively significant and technically more demanding. Ping An Life has a relatively high proportion of traditional business, while its new business is predominantly participating products. Participating products inherently involve close interdependence between asset and liability decisions. Changes in asset-side investment returns drive adjustments in dividend strategies, and liability changes in turn guide asset allocation optimization. This forms a dynamic cyclical system of “benchmark interest rate → asset allocation → liability adjustment → asset adjustment → model optimization.” (This topic is extensive; this article provides a brief overview and does not elaborate further.)

At present, the company has completed a systematic review of its existing assets, with model coverage exceeding 90% of assets. Asset categories include equities, fixed income, alternative investments, and other asset classes, and the product structure is also highly complex. Through multi-scenario simulations using the ALM model, it is possible to output core indicators under different product strategies and interest rate environments, such as profit at CAS 25 (Accounting Standards for Enterprises No. 25, Original Insurance Contracts), operating variance, CSM, and duration gap, clearly presenting the risk-return characteristics of different strategy combinations and providing a quantitative basis for strategy optimization.

Taking the company’s early implementation experience as an example, it has focused its model stress testing on interest rate scenarios, business strategies, and investment strategies, conducting sensitivity analyses on changes in indicators such as CSM release and initial CSM (contractual service margin from new business, CSMNB) under different scenarios. The core objective is to identify the optimal strategy range while keeping risks under control, so as to achieve dynamic asset-liability balance. This is precisely the core value of the ALM model.

LIABILITY-MANAGEMENT PRIORITIES FOR LONG-TERM GROWTH

Drawing on the company’s practical experience, this final section offers two observations on liability-side management to draw broader lessons for the industry.

1. Liability-side management should focus on controlling liability costs. Establishing a robust management system and strictly complying with relevant regulatory requirements is the foundation of liability-side management. Since the implementation of relevant regulatory documents in 2009, the company has accumulated extensive experience in controlling liability costs. It has continuously reduced the liability discount rate (for insurance reserves) and spread in response to market interest rates, while maintaining sufficient prudence in morbidity assumptions, to reduce future liability costs, alleviate pressure on the long-term required investment return rate, and build operational resilience to weather economic cycles.
2. It’s important to formulate differentiated management strategies for profit sources. Refining liability-side management requires a clear understanding of profit sources. It is essential to identify profit drivers across multiple dimensions—investment returns, claims levels, persistency, expenses, etc.—and to develop targeted management strategies accordingly. Only by clarifying each factor’s contribution can management prioritize actions by profit driver and achieve clear priorities and category-based management, avoiding broad-brush, one-size-fits-all approaches and improving overall operational efficiency and risk management capabilities.

In summary, the core objective of liability management is to consider all relevant factors affecting liability costs and determine the most effective approach to managing them. This requires not only solid actuarial expertise but also a deep understanding of corporate development strategy and operational logic. Only in this way can the insurer remain financially resilient in a complex and ever-changing market environment and lay a firm foundation for a company’s long-term sustainable development.

Statements of fact and opinions expressed herein are those of the individual authors and are not necessarily those of the Society of Actuaries or the respective authors’ employers.

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