Buy-side ALM product of the year: Ortec Finance

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Key points Summary

• Dynamic ALM is increasingly crucial for institutional investors amid rising inflation and interest rate changes.
• Ortec Finance’s GLASS platform allows clients to model more than 700 economic variables for robust portfolio management and strategic planning.
• Recent enhancements include improved liquidity risk modelling and machine learning for portfolio optimisation, addressing new challenges from private assets.
• The platform’s ClimateMAPS capability integrates climate risks into ALM processes, reflecting the shift from compliance to strategic decision-making.

These summaries are generated by an LLM, but edited by humans.

The past year has underscored the value of dynamic asset-liability management (ALM) for institutional investors. Persistent inflation, shifting interest rate regimes and rising exposure to illiquid private assets have tested the ability of pension funds, insurers and asset managers to keep their balance sheets resilient. Founded more than four decades ago and rooted in academic research, Ortec Finance has built its response around GLASS: a stochastic modelling platform that helps institutions manage balance sheet risk over the long term through data-driven scenario analysis.

Increasing requirements

Martijn Vos, Ortec Finance

“ALM has become far more multidimensional,” says Martijn Vos, chief operating officer at Ortec Finance. “Clients are dealing with higher inflation uncertainty, divergent monetary policy paths and a structural rise in private market exposure. That demands tools that connect liquidity, solvency and climate considerations in one framework.”

Market volatility and capital market assumptions

GLASS’s Economic Scenario Generator models more than 700 variables across 20 national economies and regions, allowing clients to test how their portfolios behave under different market conditions. It captures the interplay between inflation, yield curves, exchange rates and returns on assets, providing a robust foundation for strategic planning. Ortec Finance updates these scenarios monthly, incorporating new market data and expert insights to ensure clients’ assumptions reflect evolving macroeconomic conditions. This proved particularly valuable during the volatility of early 2025, when the firm was able to ‘quick release’ a ‘trade war’ stress scenario that helped clients assess and hedge exposures amid geopolitical uncertainty.

The importance of liquidity

Over the past year, Ortec Finance has added new capabilities to GLASS, particularly in liquidity risk modelling and machine learning for portfolio optimisation. As private assets play a larger role in institutional portfolios, investors face new challenges in forecasting cashflows and liquidity coverage. The enhanced liquidity module combines stochastic asset returns with dynamic modelling of capital calls, distributions and future commitments. “Liquidity has become one of the biggest blind spots for investors,” Vos says. “Our new module lets them test commitments and distributions under different market regimes, so they can plan pacing and buffers with far greater confidence.”

Artificial intelligence techniques in portfolio optimisation

At the same time, the firm has introduced machine learning into its scenario models to improve portfolio optimisation. The technique combines stochastic analysis with AI methods to tackle complex investment challenges more efficiently. Ortec Finance has applied it across ALM, extending optimisation to solvency, liquidity and environmental, social and governance goals while increasing both speed and analytical depth. “Machine learning here isn’t a black box,” Vos explains. “It learns within our economic scenarios, so results stay transparent and explainable – something boards and regulators value highly.”

Integration, flexibility and automation

Ortec Finance has also invested in tighter integration and usability. Enhanced application programming interface functionality allows clients to automate key workflows, while a redesigned web dashboard enables teams to visualise results and share insights across investment and governance functions. “Automation is becoming essential,” Vos notes. “Large pension and insurance clients want seamless data pipelines that reduce manual steps and let them focus on decisions, not data wrangling.”

Underpinning these technical advances is Ortec Finance’s partnership model. The company acts as both a software provider and adviser, helping clients calibrate assumptions, interpret scenario results and align investment strategies with long-term funding goals.

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Support for multiple regulatory frameworks

GLASS’s versatility has made it a valuable tool for a wide range of institutions. Pension funds use it to align asset allocation with liabilities and funding objectives; insurers apply it to capital assessments; endowments and foundations integrate it into spending-policy analysis; and asset managers and consultants use it across the business to run hundreds of discrete ALM programmes.

Across these varied use cases, the platform’s common architecture promotes consistency and efficiency, while its flexible settings cover local and international regulatory frameworks, and allow clients to set their own assumptions and create tailored reports.

Climate risk in decision-making

Climate integration is another area in which Ortec Finance has sought to extend the boundaries of ALM modelling. Through its ClimateMAPS capability, GLASS incorporates physical, transition and market risks in line with global climate frameworks. “Climate risk has moved from compliance to strategy,” Vos says. “Institutions now want to understand how different climate pathways affect long-term funding resilience and investment returns, and to integrate that directly into their core ALM process.”

Looking ahead, Vos expects the evolution of ALM technology to be gradual but deep. “The next wave won’t be about a single breakthrough,” he says. “It’s about connecting the pieces – richer climate and macro pathways, smarter liquidity modelling for private assets and more automated, explainable workflows that help boards make faster, better decisions.”

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