Purpose

This paper aims to introduce a framework for optimizing rule-based anti-money laundering systems with a clear economic interpretation, and the authors introduce the integral representation method.

Design/methodology/approach

By using a microeconomic model, the authors reformulate the threshold optimization problem as a decision problem to gain insights from economics regarding the main properties of the optimum. The authors used algorithmic considerations to find an efficient implementation by using a kind of weak mode estimate of the distribution and the authors extend this approach to classes of alerts or cases.

Findings

The method provides a new and efficient alternative for the sampling method or the multidimensional optimization technique described in the literature to decrease the bias emanating from multiple alerts by smoothing the number of alerts across classes in the optimum and decrease the overlapping between scenarios at the case level. Using the method for real bank data, the authors were able to decrease the number of false positives cases by about 18% while retaining almost 98% of the true-positive cases.

Research limitations/implications

The model assumes that alerts from different scenarios are indifferent to the bank. To include scenario-specific preferences or constraints demands further research.

Originality/value

The new framework presented in the paper is a flexible extension of the usual above-the-line method, which makes it possible to include bank preferences and use the parallelization capabilities of modern processors.

中文翻译：

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基于积分表示法的反洗钱高效规则优化框架

目的

本文旨在介绍一种具有明确经济解释的基于规则的反洗钱系统优化框架，并介绍了积分表示法。

设计/方法/方法

通过使用微观经济模型，作者将阈值优化问题重新表述为决策问题，以从经济学中获得关于最优值的主要属性的见解。作者使用算法考虑通过使用一种分布的弱模式估计来找到有效的实现，并将这种方法扩展到警报或案例的类别。

发现

该方法为文献中描述的抽样方法或多维优化技术提供了一种新的有效替代方案，通过在最优中平滑跨类的警报数量并减少案例级别的场景之间的重叠来减少来自多个警报的偏差. 使用真实银行数据的方法，作者能够将假阳性病例的数量减少约 18%，同时保留近 98% 的真阳性病例。

研究限制/影响

该模型假设来自不同场景的警报对银行无关紧要。要包括特定场景的偏好或约束，需要进一步研究。

原创性/价值

论文中提出的新框架是通常线上方法的灵活扩展，它可以包含银行偏好并使用现代处理器的并行化能力。