What were the defining trends in structured finance markets in 2025?
Structured finance markets were characterised by strong new issuance, diversification and a reach for yield. Private credit continued to expand, with lenders increasingly entering areas historically dominated by banks. This momentum was supported by strong demand from traditional investors as well as the emerging retail segment, where platforms and product innovation broadened market access. Heading into 2026, credit performance will remain a deciding factor as to which asset classes outperform. Investors will continue to prioritise attractive income opportunities while balancing pricing and credit parameters with robust security and portfolio analytics. This disciplined approach is critical for successfully navigating the complexities of today’s market cycles.
How do you expect the macro environment to shape structured finance issuance and performance in 2026?
Political headwinds include potential debate on implementing mortgage portability, the introduction of a 50-year mortgage product and potential discussions around privatising Freddie Mac and Fannie Mae. Any of these will introduce uncertainty into the housing market finance ecosystem, increasing the need for adaptable analytics that can model new loan structures and borrower incentives.
The politicisation of the Federal Reserve could add a layer of uncertainty to rate expectations. Although a more dovish Fed stance and an easing of monetary policy may ultimately lead structured finance investors to more heavily weigh both strategic model portfolio and tactical investment decisions. Rate cuts and a steepening yield curve could pull investors out of cash and short-duration investments into longer-duration securitised assets, underscoring the importance of tools that evaluate curve risk, carry dynamics and convexity across scenarios.
The mortgage market will present its own structural shifts. With rates likely to decline and the digitisation of the mortgage servicing business model, refinancing activity may increase. However, digitisation among servicers is already driving refinancing at historically narrower spreads, reshaping prepayment behaviour and risk models. Elsewhere in securitised products, the large volume of loans maturing in 2026 across CMBS could signal pockets of stress, requiring deeper credit analysis and resulting differentiation supported by loan-level surveillance and scenario-driven cash flow tools.
Innovation will remain a defining theme. AI and large language models are transforming analytics and loan-level insights, while tokenisation of bonds at issuance may enhance liquidity and broaden investor access. Together, these forces point to a market rich with opportunity, demanding firms be equipped with precise analytics and active risk management.
How are analytics and technology evolving to support more complex structured products in a shifting risk environment?
As structured products become more complex, investors are demanding analytics that provide a comprehensive, multi-perspective view of risk and return. Platforms that support full fixed-income analytics—capturing investment objectives including return targets, risk limits and regulatory considerations—are increasingly in demand.
Investors are looking to integrate asset-liability management , scenario-based return modelling, quantitative risk analytics including VaR and model portfolio ingestion with full P&L attribution. This fosters closer alignment between portfolio construction and ongoing performance evaluation.
To address the increased complexity, analytics must move beyond curve dynamics to capture behavioural and structural drivers of cash flow. This requires flexible technology that can incorporate granular scenarios, streamline model updates and scale with expanding data demands—ensuring structured finance participants can evaluate risk with confidence even as market complexity increases.
How are investor preferences evolving across CLOs, ABS, RMBS, CMBS, and structured notes?
A stronger reach for yield and heightened credit selectivity means that as spreads tighten in higher-quality tranches, investors are moving further down the capital structure to enhance carry, while demanding granular transparency into collateral performance. For investors, this dynamic will continue to drive the need for loan-level analytics and scenario-based modelling, particularly in RMBS and consumer ABS where borrower behaviour can significantly influence cash flows.
Technology is accelerating this evolution. AI and large language models enable faster data processing, behavioural pattern detection, and automated scenario generation. This helps analyse borrower behaviour, credit dispersion and identify stress points across portfolios. Ultimately, these tools support proactive risk management and provide a competitive edge in relative-value decision-making.
With the Fed expected to ease interest rates, a steepening yield curve may encourage rotation out of cash and short-duration corporates into longer tenored structured products. As allocators aim to outperform model portfolios, carry generation and credit differentiation will remain key drivers of demand. Integrating granular analytics with portfolio-level insights will be essential for identifying attractive relative value opportunities across the securitised products landscape.
