Adam Koursaris explains the principles behind a modern approach to portfolio management
The best insurance investment managers today are going beyond traditional portfolio management. They are creating an integrated investment value-chain to create optimal portfolios in the context of their company's liabilities, capital, regulatory regime, and planning objectives. This approach enhances value and increases risk-adjusted return on capital for shareholders.
Driven by new regulations, valuation methodologies, accounting standards and global emerging best practice, actuaries and risk managers have made significant advances in the way they work. For the most part, these developments have introduced more economically based approaches and promoted improved valuation and risk measurement techniques. This movement is exemplified by Europe's Solvency II but is developing in many other territories too, including International Capital Standards, China Risk Oriented Solvency System (C-ROSS), Life Insurance Capital Adequacy Test (LICAT) in Canada, and United States Own Risk and Solvency Assessment (ORSA).
The new economic principles and market-based approach to the management of insurance businesses relate closely to the approaches, beliefs, and capabilities of most asset managers. So this modern transformation provides an opportunity to manage insurance assets in a way that is more integrated, holistic, and consistent. At the same time, demoting many older, conflicting metrics should reduce many of the contradictions and inconsistencies that have frustrated sound investment decisions in the past.
Integrating asset management into the insurance business
Asset managers who are adding the most value to insurers are enhancing the management of insurance assets by designing portfolios that reflect the liabilities of the insurer, cognizant of the capital
regime under which they operate and the objectives and constraints of the insurer. This is achieved by deepening the capabilities of the ALM team and working more closely with the asset management function.
The ALM team acts as a bridge between the insurer and the asset manager. It collects and amalgamates a variety of information and requirements from finance, risk, actuarial, product, and investment teams; leveraging the data and models used across the business and integrating them into management decision-making. When this relationship works well, the asset manager acquires the tools to make better investment decisions, positioning the investment portfolio to achieve the best outcomes in the context of the insurer's constraints and planning objectives. In the process all parties benefit from a more richly informed dialogue.
An integrated asset manager is able to bring together many different considerations in the investment framework. They can contemplate the capital treatment of the assets, the liquidity offered and demanded by the liabilities, the interaction and feedback between assets and liabilities, the impact of transaction costs, and the way these elements combine with market and credit risk to create opportunities and risks.
They are able to do these things quickly, to take advantage of market opportunities, integrate their own proprietary economic views and effectively capture the insurer's objectives and salient metrics in their analysis, to enhance risk-adjusted return on capital.
In an insurance company, the risk, finance, actuarial, and investment teams all contribute in some way to the investment process. But for many insurance groups, these teams operate in siloes: different data, systems, models, and processes mean that it can be difficult to communicate the requirements, share data and align the interests and priorities of the different teams. It is challenging for a business to produce and use the all the analytics they would like.
Even with organizational desire and leadership, there are technical and operational challenges. The underlying actuarial and risk models are usually not built with ALM and asset management functions and activities in mind. Driven by the needs of the actuarial function, such as reporting and valuation, they will often operate at a level of detail that is highly granular ("bottom up"). For example, a single capital calculation can take a month to complete, considering the whole end-to- end process and the need to reconfigure models to generate the required runs. For making investment decisions, several different alternative portfolios, rebalancing strategies and runs are need. These different strategies will need to be run over a large number of economic scenarios. The effort and timescales therefore limit the usefulness of these tools for real-time decision making.
While a "brute-force" integration of these tools might be conceptually simple, it is unlikely to be feasible in practice. The challenge is to identify ways that robust, accurate, and timely information can be harvested and used to deliver insight to the asset manager and senior management.