0000000000538196
AUTHOR
Elena Badal-valero
Combining Benford's Law and machine learning to detect money laundering. An actual Spanish court case.
Abstract Objectives This paper is based on the analysis of the database of operations from a macro-case on money laundering orchestrated between a core company and a group of its suppliers, 26 of which had already been identified by the police as fraudulent companies. In the face of a well-founded suspicion that more companies have perpetrated criminal acts and in order to make better use of what are very limited police resources, we aim to construct a tool to detect money laundering criminals. Methods We combine Benford’s Law and machine learning algorithms (logistic regression, decision trees, neural networks, and random forests) to find patterns of money laundering criminals in the conte…
Fire risk sub-module assessment under solvency II. Calculating the highest risk exposure
The European Directive 2009/138 of Solvency II requires adopting a new approach based on risk, applying a standard formula as a market proxy in which the risk profile of insurers is fundamental. This study focuses on the fire risk sub-module, framed within the man-made catastrophe risk module, for which the regulations require the calculation of the highest concentration of risks that make up the portfolio of an insurance company within a radius of 200 m. However, the regulations do not indicate a specific methodology. This study proposes a procedure consisting of calculating the cluster with the highest risk and identifying this on a map. The results can be applied immediately by any insur…
Detección de fraude financiero mediante redes neuronales de clasificación en un caso real español
espanolEste analisis supone una primera aproximacion a la implementacion de modelos de redes neuronales al trabajo pericial para la deteccion de operaciones de fraude. Los datos analizados provienen de un caso real de blanqueo de capitales en el que se esta colaborando con la Policia Nacional Espanola. En ellos se cuenta con informacion de operaciones contables individuales entre las que se cuenta con una proporcion de operaciones bien identificadas como fraudulentas con la que es posible entrenar un modelo de clasificacion. En este trabajo, tras describir brevemente la metodologia utilizada y la estrategia de ajuste se obtiene un modelo con una capacidad predictiva resenable, incluso con d…