Anti-money laundering system and method based on machine learning
A machine learning and data system technology, applied in machine learning, instruments, finance, etc., can solve the problems of anti-money laundering system, such as poor timeliness, inability to intercept in real time, and unstable detection accuracy, so as to reduce manpower and time costs and realize Real-time detection and improvement of the effect of the effect
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Embodiment 1
[0055] An online real-time anti-money laundering system based on machine learning, characterized in that it includes:
[0056] Time series feature processing layer: construct time series features based on user information;
[0057] Distributed model operation layer: Based on the time series characteristic data, build a money laundering model, and integrate the money laundering model result set;
[0058] Real-time strategy layer: Based on the money laundering model result set, construct a money laundering strategy set;
[0059] Decision-making level: Integrate new information from policy sets to make anti-money laundering decisions
[0060] The time series feature processing layer builds time series features based on the transferred user information and data, and processes the time series features in three modes, and transfers the processed time series features to the distributed model operation layer, which is based on the time series The characteristics of the model are cal...
Embodiment 2
[0062] Embodiment 2: The decision-making layer is connected to an anti-money laundering verification system, and the anti-money laundering verification system connected to the decision-making layer can manually verify suspicious transactions provided by the anti-money laundering system, and further detect money laundering transactions.
Embodiment 3
[0063] Embodiment 3: The anti-money laundering verification system is connected to the anti-money laundering verification data system, the anti-money laundering verification data system is connected to the anti-money laundering data system, and the anti-money laundering data system is connected to the sequential feature processing layer. The anti-money laundering verification system transfers the manually verified data into the anti-money laundering verification data system, and the anti-money laundering verification data system transfers the anti-money laundering verification data into the anti-money laundering system. Through the above data closed loop, the coverage of the anti-money laundering data system is increased, enabling The timing feature selection of the timing feature processing layer is more extensive and targeted.
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