Real-time decisioning
Detect and score fraud and AML activity in real time, with the homepage citing less than 100 ms latency for real-time scoring and 15,000+ QPS in live production.
DataVisor es una plataforma de fraude y AML para detectar, investigar, optimizar y reportar delitos financieros en tiempo real.
DataVisor is a fraud and AML platform for enterprises that need to detect new and known financial crime patterns in real time. The homepage describes it as an AI-native decisioning platform that combines adaptive AI, cross-entity intelligence, and real-time scoring for fraud and risk management.
The product spans detection, investigation, optimization, and reporting. Its integration guide says teams can send data through real-time or batch pipes, receive detection results through API or cloud-bucket push, and connect the system to existing analytics, orchestration, and fraud workflows.
Detect and score fraud and AML activity in real time, with the homepage citing less than 100 ms latency for real-time scoring and 15,000+ QPS in live production.
Use adaptive AI, patented machine learning, and intelligent automation to identify new threats and support fraud and AML workflows across detection, investigation, and reporting.
Create and edit features, rules, and lists from chat, including allow, block, and watch lists, so teams can operationalize changes without switching tools.
Prioritize and cluster alerts, explain why alerts triggered, and guide investigators through checklists that log actions for an auditable record.
Generate reporting outputs with built-in regulatory reporting, including SAR/CTR generation and an audit trail, according to the AI Agents page.
Integrate through real-time or batch pipes, with API or cloud-bucket delivery of results, and support for structured and unstructured data.
Monitor transactions and user activity in real time to detect fraud and risk events, then pass results into downstream systems for auto-actioning or review.
Use onboarding and application checks to spot suspicious accounts, loan applications, and new customer activity before approval or activation.
Prioritize alerts, summarize why they fired, and guide analysts through case steps with checklists and audit logging for consistent reviews.
Tune rules, features, and thresholds by chat, then test changes against recent or sample data before pushing them into production workflows.
Generate regulatory reporting outputs and maintain an audit trail for compliance teams working on SAR/CTR-style reporting tasks.
The integration guide says setup usually takes less than two weeks and requires the customer to provide sample data, then stream data into DataVisor’s integration endpoint. DataVisor also provides technical account managers, training, and 24/7 support during onboarding.
Yes. The guide says DataVisor can be integrated with existing data analytics platforms and data warehouse solutions, and it can ingest multiple data formats from multiple sources.
Yes. The source says results can be returned through API or cloud bucket push, and teams can use them to trigger auto-actions or feed downstream systems.
The integration guide says DataVisor supports real-time and batch processing, asynchronous and synchronous modes, structured and unstructured data, and deployment on major cloud providers as well as on-premises and private cloud.
The integration guide says DataVisor does not collect PII data and processes non-PII data only. It also states that dedicated cloud machines, encryption at rest, HTTPS for real-time transfers, and GDPR-compliant deployments in Europe are supported.
Los datos de tráfico son solo como referencia.
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