Reduce the human cost of anti-money laundering compliance, identify suspicious cases, assist with analysis and reporting, and address the problems of ‘omission’ and ‘overstatement’ of anti-money laundering institutions by means of AI anti-money laundering technology.
Intelligent Case IdentificationAI anti-money laundering technology can efficiently identify suspicious transactions from within massive transactions, and carry out pre-processing operations such as classification.
Intelligent Case Classification OptimizationSort the flagged suspicious cases according to order of suspicion, increase the priority level of suspicious cases and shorten the average reporting period. Implement the intelligent human-case matching to optimize overall review efficiency
Intelligent Assistant AnalysisAutomatically summarizecase points of suspicion to improve the review efficiency. Report generation by automatic writing together with manual review to improve reporting efficiency
Improve Reporting Rate
Compared with conventional expert rules, the AI anti-money laundering model delivers higher accuracy rate and increases the recall effect, which reduces the number of false reporting and improves the reporting rate
Reduce Operating Costs
Intelligent case identification, case sorting optimization and assistant analysis can improve the efficiency of human analysis and significantly reduce the labor costs in review and reporting.
Continuous Updating and Evolution
The high-dimensional model is combined with self-learning to construct a complete on-line closed data flow loop to realize automatic model iteration through continuous data feedback. New rules discovered will be provided as feedback which can help improving business rules.