Abstract: An apparatus and a method are disclosed for analyzing attributes of electronic transactions. The method includes generating a combined standardized transaction data structure based on analysis of transaction data; creating or updating one or more composite risk signals based on analysis of event data; obtaining one or more additional risk signals using machine learning based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, the event data, or third party data received from a third party data provider; and generating at least one of a detection event, a transaction alert, a case management message or a regulatory filing message based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, or the one or more additional risk signals obtained by machine learning, or the third party data.

Abstract: An apparatus and a method are disclosed for analyzing attributes of electronic transactions. The method includes generating a combined standardized transaction data structure based on analysis of transaction data; creating or updating one or more composite risk signals based on analysis of event data; obtaining one or more additional risk signals using machine learning based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, the event data, or third party data received from a third party data provider; and generating at least one of a detection event, a transaction alert, a case management message or a regulatory filing message based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, or the one or more additional risk signals obtained by machine learning, or the third party data.

Abstract: An apparatus and a method are disclosed for analyzing attributes of electronic transactions. The method includes generating a combined standardized transaction data structure based on analysis of transaction data; creating or updating one or more composite risk signals based on analysis of event data; obtaining one or more additional risk signals using machine learning based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, the event data, or third party data received from a third party data provider; and generating at least one of a detection event, a transaction alert, a case management message or a regulatory filing message based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, or the one or more additional risk signals obtained by machine learning, or the third party data.

Abstract: An apparatus and a method are disclosed for analyzing attributes of electronic transactions. The method includes generating a combined standardized transaction data structure based on analysis of transaction data; creating or updating one or more composite risk signals based on analysis of event data; obtaining one or more additional risk signals using machine learning based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, the event data, or third party data received from a third party data provider; and generating at least one of a detection event, a transaction alert, a case management message or a regulatory filing message based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, or the one or more additional risk signals obtained by machine learning, or the third party data.

Abstract: An apparatus and a method are disclosed for analyzing attributes of electronic transactions. The method includes generating a combined standardized transaction data structure based on analysis of transaction data; creating or updating one or more composite risk signals based on analysis of event data; obtaining one or more additional risk signals using machine learning based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, the event data, or third party data received from a third party data provider; and generating at least one of a detection event, a transaction alert, a case management message or a regulatory filing message based on at least one of: the combined standardized transaction data structure, the one or more composite risk signals, or the one or more additional risk signals obtained by machine learning, or the third party data.