Implementation of fraud detection algorithms using Big Data technology and graph database to increase the effectiveness of anti-fraud indicators.
Development of detection algorithms based on Pregels graphs implementation and study of existing algorithms for possible adaptation in anti-fraud processes. Generation of indicators using the Spark GraphX module.
The solution provided, improved fraud detection rates and it favored an increase in tax revenues during the regulatory stages.
Thanks to collection of monitoring indicators, it was improved and optimize the performance of processes.