The purpose of this paper is to examine whether, and under what conditions, the expansion of anti-money-laundering (AML) compliance requirements can reduce effective enforcement against trade-based money laundering (TBML) through investigative capacity constraints, evidential decay and strategic adversarial adaptation.
A reduced-form theoretical model is developed using an M/G/m queueing framework with exponential evidential decay, endogenous threshold-based triage and strategic laundering behaviour. Comparative statics analyse the sensitivity of the results to evidential decay, splitting costs, attention dilution and cognitive capacity.
Increasing compliance intensity raises alert volume without proportionate capacity growth, generating congestion that degrades evidential quality and forces institutions into predictable triage. Rational launderers exploit these boundaries through splitting and bunching. The perverse effect is strongest when evidence decays rapidly, splitting is cheap and compliance expansion is extensive rather than informativeness-enhancing.
The model is intentionally stylised, abstracts from institutional heterogeneity and cross-border coordination and does not attempt empirical calibration. Results describe short- to medium-run dynamics in which capacity adjustment lags regulatory expansion.
Results support shifting supervisory metrics from alert volume to time-to-action and confirmation rates, reducing the predictability of escalation thresholds, prioritising evidence preservation over scenario expansion and increasing per-transaction laundering costs through documentation requirements.
This paper formalises a mechanism – regulatory overload as a laundering enabler – widely observed in AML practice but not previously modelled. This study connects TBML to enforcement economics and queueing theory, identifying conditions under which compliance expansion becomes self-defeating.
