Beymani consists of set of Hadoop and storm based tools for outlier and anamoly detection, which can be used for fraud detection.
- Simple to use
- Input output in CSV format
- Metadata defined in simple JSON file
- Extremely configurable with tons of configuration knobs
The following blogs of mine are good source of details of beymani
- http://pkghosh.wordpress.com/2012/01/02/fraudsters-outliers-and-big-data-2/
- http://pkghosh.wordpress.com/2012/02/18/fraudsters-are-not-model-citizens/
- http://pkghosh.wordpress.com/2012/06/18/its-a-lonely-life-for-outliers/
- http://pkghosh.wordpress.com/2012/10/18/relative-density-and-outliers/
- http://pkghosh.wordpress.com/2013/10/21/real-time-fraud-detection-with-sequence-mining/
- Multi variate distribution model
- Average Distance
- Relative Density
- Markov chain
Project's resource directory has various tutorial documents for the use cases described in the blogs.
Please feel free to email me at [email protected]