Identifying Anomalies in Parliamentary Expenditures of Brazilian Chamber of Deputies with Deep Autoencoders

Each Brazilian Deputy receives a quota of money quota to cover the politician activity expenses, besides their salary. The amount of money reserved for that quota can sum up to almost 1 billion of Brazilian currency (approximately 300 million US Dollars) in a 4 year legislature. Civic society is using that data to perform independent auditing to verify expenses that are against the rules. This article presents the application of deep Autoencoders to identify anomalies in that data. The anomalies found indicate new suspicious expenses and several data quality problems in the data opened to the society.