The anti-money laundering risk assessment: A probabilistic approach
研究专家和新手在反洗钱风险评估中的过度自信效应，发现两者均存在偏差且专家更明显，新手正确率略高，建议引入反馈机制改善判断。
Since the 1980s, researchers and practitioners examining the vulnerabilities of financial institutions to money laundering risk have offered some insights on how experts conduct anti-money laundering risk assessments. A common theme in the risk assessment literature is the emphasis on box-ticking rather than exercising judgment case-by-case, which has influenced our consideration of whether experts in this domain are immune to cognitive biases that novices can be vulnerable to during risk assessment. We found that both experts and novices were overconfident about their distribution judgments and this effect was slightly more pronounced in the expert group. One manifestation of the overconfidence effect in both groups was the preference for false-positive over false-negative errors. Notably, novice participants slightly outperformed expert participants in the proportion of correct outcomes. A feedback mechanism that is effective at alleviating biases, improving processes, and resultant judgment accuracy may be valuable to experts in this domain.