Hi all, Following the implementation of Fraud Rules, and Markov Chain capability in order to do outlier detection in CEP, we are hoping to implement Fraud Scoring capability.
Fraud Scoring is a mechanism to evaluate multiple features of a transaction (eg:- geolocation, ip address, billing/shipping address, transaction velocity etc;) and based on historical trends and blacklists, compute a score for each transaction (eg:- between 0 and 100). Higher the score, higher the risk that the transaction will be a fraudulent transaction. [1] is a good introduction to Fraud Scoring. Now that we have already implemented several fraud detection rules, the plan is to augment this using a scoring system, so that siddhi calculates a score for each transaction, based on how it performed in the rules. [2] gives a very simple example of how this might be done. When we complete this, we are able to show that CEP can perform fraud detection in the following ways a. Rule based b. Using Markov Chains c. Using Fraud Scores 1. http://www.fraudpractice.com/fl-fraudscore.html 2. https://www.maxmind.com/en/ccfd_formula Cheers, Seshika
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