The digital asset market grew sharply in 2023, with market capitalisation rising from around $830 billion to $1.6 trillion. This growth has pushed crypto firms and fintechs to rely more heavily on models for risk management, fraud detection, and financial crime prevention. Yet many firms still struggle to apply the right level of governance to these models, especially as digital\u2011asset behaviours shift faster than traditional financial markets.<\/p>\n
A key challenge is that digital\u2011asset models often rely on data that is volatile, incomplete, or difficult to verify. This makes it harder to understand how a model behaves over time or whether it remains reliable as market conditions change. Firms frequently ask how to validate models when historical data is limited, when behaviours shift rapidly, or when blockchain\u2011native features introduce new risks. These are practical issues that traditional validation frameworks don\u2019t always address.<\/p>\n
Our whitepaper tackles these questions directly. It explains the specific risks that arise in digital\u2011asset modelling, outlines common failure points we see across the industry, and provides practical steps firms can take to strengthen governance. This includes approaches for testing models with limited data, assessing model drift in fast\u2011moving markets, and aligning governance with emerging regulatory expectations.<\/p>\n