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Fraud detection within financial platforms remains a challenging area in which criminals continue to thrive, breaching security mechanisms with increasingly innovative and sophisticated system attacks. Following the migration from reactive to proactive screening of transactional data to reduce an organisations fraud detection latency, fraud analysts now find themselves responsible for the maintenance of extensive fraud policy sets and their implementation as complex data stream processing procedures. This paper presents a Financial Fraud Modelling Language and policy mapping tool for high level expression and implementation of proactive fraud policies using stream processors. A key aspect of the approach is reduction of the complexity and implementation latency associated with proactive fraud policy management through abstraction of policy functionality using a conceptual level modelling language and innovative policyion of policy functionality using a conceptual level modelling language and innovative policy mapping tool. This paper focuses upon the rule based language model for high level expression of financial fraud policies and the associated compiler tool for specifying and mapping policies into StreamSQL.

SPECIFYING AND COMPILING HIGH LEVEL FINANCIAL FRAUD POLICIES INTO STREAMSQL