Fixed income valuation has reached a turning point. According to LSEG Data & Analytics, it is no longer enough for firms to show that a price is defensible. They must now be able to explain why it is defensible, setting out the inputs, assumptions and rationale behind it.
LSEG Data & Analytics notes that regulators, risk teams, valuation committees and clients are all asking harder questions, especially where liquidity is fragmented or instruments are complex. Access to data alone no longer satisfies them. They expect trusted inputs, transparent methodologies, clear lineage and human oversight, and those expectations are rising as AI becomes more embedded in pricing and analytics.
The pressure is greatest where observable prices are scarce. Private credit, securitised products, structured notes and fragmented secondary markets often lack frequent trading, and the information needed to interpret them is spread across multiple sources, systems and workflows. In these markets, LSEG Data & Analytics argues, a valuation endpoint is not sufficient. Firms need evidence of how that endpoint was reached, which is why transparency fields covering inputs, assumptions and expert rationale are becoming a practical requirement for evaluated pricing.
Research cited by LSEG Data & Analytics, from a survey conducted by the A-Team, shows broadly high confidence in auditability, with important caveats. A quarter of respondents said they were extremely confident and faced zero operational friction during audits or regulatory enquiries. A further 60% were very confident, with lineage tools covering the vast majority of their fixed income book. However, 15% were only somewhat confident, identifying complex and structured products as audit blind spots. That gap matters, because the hardest assets to value are typically those where explainability counts most.
Cash flow assumptions, redemption behaviour, loan-level data, collateral characteristics and market proxies all need to be understood in context. If a firm cannot trace how these inputs shaped a valuation, defending it under challenge becomes difficult. In the view of LSEG Data & Analytics, valuation data is becoming evidence rather than simply an output.
AI adds a further layer of risk, as it can accelerate both insight and error. The survey found firms divided between active human sign-off and passive post-trade review for AI-assisted valuations, with only 10% comfortable allowing fully autonomous AI-assisted valuations. While no single governance standard has emerged, there is consensus that AI cannot be detached from accountability.
LSEG Data & Analytics highlights that the human role is evolving rather than disappearing. Experts are increasingly used more deliberately, reviewing exceptions, challenging assumptions, monitoring drift and providing final judgement in stressed markets. Regulation is reinforcing the trend, with DORA raising expectations around resilience and stability in data delivery.
The conclusion from LSEG Data & Analytics is clear. Explainability must be designed into the valuation process, not bolted on at the point of review. The market is moving from a world where trust was implied by the provider to one where it must be demonstrated through data, governance and evidence. Firms that cannot show their workings may find themselves exposed, even when their valuations appear accurate.
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