Can we predict settlement delays and failures? Transaction-level evidence on liquidity and operational frictions

This paper examines settlement failures and delays using transaction-level post-trade securities data. We investigate whether settlement frictions can be predicted ex ante and whether the timing of settlement completion reflects systematic liquidity and operational risk patterns. Using a logistic regression framework, we show that ontime settlement failures are predictable using observable transaction characteristics and historical account-level settlement behavior. The model achieves meaningful out-of-sample performance, with an area under the receiver operating characteristic curve of 0.764 and strong risk stratification across predicted-risk deciles. Using a Cox proportional hazards model, we further show that settlement timing varies systematically across transaction types, currencies and historical settlement behavior. Delivery-versus-payment mechanisms are associated with faster settlement completion, while certain transaction types and accounts with prior settlement frictions exhibit reduced settlement intensity. Robustness checks using gradient boosting and a Weibull duration model confirm the stability of the main findings. Overall, the results suggest that settlement failures and delays are not purely random back-office events but contain economically meaningful information about post-trade liquidity stress, operational persistence and financial market infrastructure resilience.