DataVisor, the world’s leading AI-powered fraud and financial crime prevention platform, is excited to announce significant enhancements to its advanced multi-tenancy solutions. These enhancements allow organizations to configure and customize fraud prevention and anti-money laundering (AML) strategies and seamlessly deploy them across multiple sub-tenants. This includes the deployment of features, business rules, and machine learning models, ensuring comprehensive and consistent protection, with flexible data segregation, orchestration, and reportings.
DataVisor’s new multi-tenancy enhancements empower core banking providers, processors, and acquirers to offer advanced fraud and AML tools to their customers, while utilizing their network-level view of transactions and activities to develop consortium risk signals. It also addresses unique compliance challenges for sponsor banks, enhancing their risk management with fintech collaborations with better transparency, governance, and risk control. Additionally, large financial institutions can also leverage the multi-tenancy setup to centralize data and feature computation at the main tenant level, while enabling individual business units to make decisions independently through sub-tenancy.
DataVisor’s next generation multi-tenancy capabilities offer customers three distinct options tailored to different levels of data segregation, control, and configurability at the sub-tenant level:
- Enforcement Option: Provides the main tenant with the highest level of control, allowing it to define all data computation, strategies and reportings for the sub-tenants.
- Recommendation Option: Centralizes data computation, but offers sub-tenants the flexibility to define their own strategies while building upon those established by the main tenant.
- Enrichment Option: Allows sub-tenants to be in complete control of their own data computation, development of strategies and reportings, with the ability to retrieve consortium risk signals from the main tenant to enrich decision-making.
These options empower organizations to choose the right level of control and customization that best fits their operational needs. Different from other multi-tenancy solutions in the market, DataVisor supports true data segregation to ensure complete data isolation and privacy, providing better protection with customizable access controls at the tenant level, data level, and view level. It also includes advanced data orchestration and reporting functionalities at both the main-tenant and the sub-tenant level, enhancing visibility and transparency–particularly in today’s regulatory environment–to allow effective compliance policy control and monitoring across different business units and between sponsor banks and fintechs.
The enhanced multi-tenancy from DataVisor brings innovation and versatile benefits to both large and small organizations alike. It boasts a cloud-native architecture with total elasticity to scale performance as the number of sub tenants increases, supporting real-time payment use cases with over 15,000 transactions per second (TPS) and 100-200 ms end-to-end processing latency for both the main tenant and the sub-tenants. Additionally, with no-code/low-code support, unsupervised machine learning and Gen AI powered AI Co-pilot, DataVisor’s multi-tenancy enables larger organizations to extend advanced machine learning models and AI capabilities to their clients who may not have in-house machine-learning capabilities, enhancing protection across all sizes of clients against the most sophisticated attacks in the world.
“The enhanced multi-tenancy capabilities exemplify our dedication to empowering customers in their fight against modern fraud and money laundering activities,” said Caiwei Li, CTO of DataVisor. “Unlike other solutions, we offer a greater variety of advanced technology and flexible options, tailored to meet the specific business needs we’ve identified through customer feedback. These enhanced capabilities are already being rolled out to several of our existing customers, demonstrating its effectiveness and reliability.”
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