Fraud, money laundering and cyber attacks are growing in sophistication and creating losses in the billions. Many software fraud detection efforts are focused solely on signaling & detection but are not adequate for attacks that cross multiple investigation silos causing investigation groups to be stretched. The increased sophistication of these attacks reveal that internal firewalls between the detection and investigation groups must be broken down or institutions will face massive losses against these sophisticated attacks.
This session will focus on how new ML and graph analytics work together with simple deep link visualization to reduce false positives by 60%, increase detection accuracy by 70% and improve overall team transparency and productivity by more than 80% to allow real time alerting to avoid sanctions and fines.
We will demo Expero CoNNected for Financial Crimes with Neo4j and show how the solutions together can assist executives and special investigation teams to leverage current technology and unlock the potential in your organization, complementing existing tools and technologies.
Unique Challenges in Transaction Monitoring and Screening - Discuss complexities of new types of AML and Fraud, why they are more difficult to intervene, even with a myriad of current technology and and other impacts on compliance, and the best way to identify real time threats
Technology Innovations - how new technologies like Neo4j and Analytics, Master Data Matching, Machine Learning, and Adverse Media are assisting in reducing false positives and increasing accuracy
Empower the Investigator - Capabilities in visualization technology and human processes that increase throughput and provide valuable human intelligence, creating quicker and more efficient outcomes for different roles like Case Management, Alerts, ML and Investigators, and Data and Analytics teams
Rise of ML & AI with ‘Explainable’ ML - how to implement practical uses and methods of transaction monitoring of fraud identification, complex dependency and case management with ‘humans-in-the-loop’ for higher accuracy and process streamlining
Fraud, money laundering and cyber attacks are growing in sophistication and creating losses in the billions. Many software fraud detection efforts are focused solely on signaling & detection but are not adequate for attacks that cross multiple investigation silos causing investigation groups to be stretched. The increased sophistication of these attacks reveal that internal firewalls between the detection and investigation groups must be broken down or institutions will face massive losses against these sophisticated attacks.
This session will focus on how new ML and graph analytics work together with simple deep link visualization to reduce false positives by 60%, increase detection accuracy by 70% and improve overall team transparency and productivity by more than 80% to allow real time alerting to avoid sanctions and fines.
We will demo Expero CoNNected for Financial Crimes with Neo4j and show how the solutions together can assist executives and special investigation teams to leverage current technology and unlock the potential in your organization, complementing existing tools and technologies.
Unique Challenges in Transaction Monitoring and Screening - Discuss complexities of new types of AML and Fraud, why they are more difficult to intervene, even with a myriad of current technology and and other impacts on compliance, and the best way to identify real time threats
Technology Innovations - how new technologies like Neo4j and Analytics, Master Data Matching, Machine Learning, and Adverse Media are assisting in reducing false positives and increasing accuracy
Empower the Investigator - Capabilities in visualization technology and human processes that increase throughput and provide valuable human intelligence, creating quicker and more efficient outcomes for different roles like Case Management, Alerts, ML and Investigators, and Data and Analytics teams
Rise of ML & AI with ‘Explainable’ ML - how to implement practical uses and methods of transaction monitoring of fraud identification, complex dependency and case management with ‘humans-in-the-loop’ for higher accuracy and process streamlining
