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.. date: 2013/07/03 09:16:24
.. title: Anomaly detection in the Brazilian public health system
.. slug: renato_assuncao

**Renato Assunção**

*DCC - UFMG*

Anomaly detection is a common problem common in many applications 
areas such as fraud detection in financial transactions as 
the patterns on credit card purchases by customers. Other 
applications include the detection of anomalous behaviors of 
mobile users, and anomalies in user data in health plans. 
Data mining methods have been developed to deal with the 
aspects common to all theseapplications, as well as the 
specific aspects of each. Among the common axes that run through 
all the techniques, the main ones are: visualization as a tool
for exploring hypotheses, multivariate analysis, and robustness 
as the way to ensure that the presence of abnormalities do not mask 
the overall statistics and prevent their detection. 

In this presentation, we present the ongoing experience 
of a group from the Departamento de Ciencia da Computacao da UFMG 
to develop an anomaly detection system, called INFOSAS, to the 
Brazilian Health Ministry. In paryicular, we are interested 
in detecting frauds. We discuss some of the mahor fraud schemes 
and the techniques used to address them. Some of the generic 
conclusions we have reached at this point is the need to use 
simple and understandable models, visual tools, and a flexible 
environment that gives data management its pivoltal value. 
We also emphasize the need to build interactively this system 
with human intervention and heavy help from public health experts.