The LDI crisis that struck the life and pension business about a year ago, as well as the recent failures in the banking sector, came to remind us of the importance of Asset and Liability Management (ALM) for financial institutions. In the insurance industry, in particular, ALM is not just about compliance or risk management—it is a strategic necessity. In today's volatile financial environment, effective ALM can make the difference between a thriving firm and one that struggles to maintain its footing.
SS&C Algorithmics was recognized at the forefront of this area with the recent win of “Life and pensions ALM system of the year” at the Risk Technology Awards 2023. Algorithmics provides a comprehensive solution that bridges the gap between risk management analytics (market and credit), active monitoring of mismatch and strategic asset allocation functions, ultimately supporting a risk-aware decision-making process.
The framework combines advanced asset modeling, liability proxying techniques, scenario generation, portfolio aggregation and optimization methodologies with workflow management, production processes and interactive reporting tools to deliver a consistent view of risk and ALM analytics at any level of the organization.
More specifically, Algorithmics addresses the main challenges of insurance ALM, including the following:
Extremely long run times of actuarial projection tools, make on-demand reruns prohibitive.
Algorithmics calibrates precise loss functions and replicating portfolios to liability cash-flows for fast recalculations.
Oversimplified asset valuation, often incapable of capturing optionalities and complex securities.
Algorithmics models assets by terms and conditions, generating precise cash-flow projections, of a wide range of asset types, including derivatives, structured products and alternatives.
Discrepancy between data and assumptions used for assets and liabilities.
Algorithmics integrates assets and liabilities, ensuring consistency of data, scenarios, curves, etc.
Insurers need to promptly respond to market events, even when it requires performing millions of recalculations to project both sides of the balance sheet over time and risk scenarios. Algorithmics developed high-performance engines and cloud computing infrastructures via remote repositories, containerized images, Kubernetes and PostgreSQL to help support such needs.
Users can leverage this computing power through intuitive web interfaces, allowing to accurately report mismatches and risk indicators, run real-time what-if analyses and stress tests, or perform ad-hoc stochastic sensitivity runs. Portfolio optimization is seamlessly enabled on investment portfolios, e.g., to maximize returns against liability benchmarks while enforcing the firm’s risk appetite framework.