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High-Risk Jurisdictions model
Identifying high-risk transactions from High-Risk Jurisdictions model
Introducing our federated learning models for High-Risk Jurisdictions – an advanced solution designed to empower financial institutions (FIs) with unparalleled insights into high-risk transactions from jurisdictions identified as high-risk by global regulatory bodies like the FATF.
This state-of-the-art model harnesses the collective data from over 20 local banks in high-risk jurisdictions, with 40% of transactions manually reviewed for risk, resulting in the most comprehensive and accurate machine-learning model for detecting suspicious activities from these regions
Key features
Jurisdiction-specific risk indicators: The model is specifically trained to identify high-risk transaction patterns associated with jurisdictions flagged by regulatory bodies, such as those with weak AML/CTF controls, high levels of corruption, or significant terrorist financing risks.
Behavioral anomaly detection: Detect anomalies in transaction behaviors, such as unusual transaction amounts, irregular timing, or complex transfer routes that could indicate money laundering, terrorist financing, or other illicit activities.
Cross-border transaction scrutiny: The model analyzes cross-border transactions, particularly those moving through high-risk corridors, providing FIs with critical insights into potential risks.
Our HRJ transaction model is built from over 20 participating banks in high-risk jurisdictions to collaboratively train a robust machine learning model on every international transaction leaving that jurisdiction.
Global transaction insights: By aggregating insights from diverse transaction data across multiple institutions, the model gains a unique ability to detect subtle patterns and anomalies specific to high-risk jurisdictions that no single bank could identify on its own.
Extensive transaction dataset: With access to a dataset comprising thousands of transactions from over 20 banks, including 40% manually reviewed, the model is built on a foundation of accuracy and depth unmatched in the industry.
Manual review integration: Integrating manually reviewed transactions ensures that the model is data-driven and incorporates expert judgment, significantly enhancing its reliability in identifying actual risks.
Over 50% of transactions over a period of 12 months, being sent from the high-risk jurisdicatation was manually reviewed including all documentation to ascertain it legitimacy. Where suspicious activity was considered the transaction was further investigated.
Federated learning allows AI models to be trained directly on local datasets within the confines of an organization's secure infrastructure. Only the aggregated model updates, not raw data, are shared across participants.
By avoiding centralized data pooling, federated learning minimizes the risk of data breaches, reducing the security concerns often accompanying inter-agency or inter-institutional collaborations.
Key benefits
Unmatched detection capabilities
Leverage a model trained on the most comprehensive dataset
available, offering unparalleled accuracy and reliability in detecting
high-risk transactions from jurisdictions where financial crime risks are
most prevalent.
Enhanced compliance
Stay ahead of regulatory requirements by utilizing a solution that meets and exceeds the standards set by international bodies for monitoring transactions from high-risk jurisdictions.
Operational efficiency
Automate the detection of high-risk transactions, significantly reducing the manual workload for compliance teams and enabling them to focus on investigating the most critical cases.
Data privacy and security
Participate in a federated learning ecosystem that maximizes the utility of collective intelligence while ensuring that individual data remains confidential and secure.
Competitive advantage
Elevate your institution as a leader in AML innovation by adopting a solution that delivers unparalleled insights and protection. Gain a decisive edge with a model that outperforms all others, strengthening trust with regulators, customers, and partners alike.
Unmatched detection capabilities
Leverage a model trained on the most comprehensive dataset
available, offering unparalleled accuracy and reliability in detecting
high-risk transactions from jurisdictions where financial crime risks are
most prevalent.
Enhanced compliance
Stay ahead of regulatory requirements by utilizing a solution that meets and exceeds the standards set by international bodies for monitoring transactions from high-risk jurisdictions.
Operational efficiency
Automate the detection of high-risk transactions, significantly reducing the manual workload for compliance teams and enabling them to focus on investigating the most critical cases.
Data privacy and security
Participate in a federated learning ecosystem that maximizes the utility of collective intelligence while ensuring that individual data remains confidential and secure.
Competitive advantage
Elevate your institution as a leader in AML innovation by adopting a solution that delivers unparalleled insights and protection. Gain a decisive edge with a model that outperforms all others, strengthening trust with regulators, customers, and partners alike.
Navigate high-risk transactions with collective intelligence
Our unique federated learning model for identifying high-risk transactions from high-risk jurisdictions offers a revolutionary approach to AML.
By leveraging the collective intelligence of over 20 banks and integrating insights from manually reviewed transactions, this solution provides FIs with the most accurate and effective tool for detecting and mitigating risks associated with high-risk jurisdictions.