Discover how our AI models tackle these challenges head-on, addressing each with precision and efficiency.
ADI's TM Alert Optimization revolutionizes the approach to transaction monitoring by integrating AI downstream of traditional rule-based systems. This innovation scores alert outputs and historical decisions, identifying likely false positives for automatic resolution. This strategic application of AI refines focus, enabling AML teams to concentrate on high-priority investigations, thus optimizing operational efficiency and accuracy.
ADI's Mule Detection utilizes dual AI models to preemptively identify potential mule accounts from the moment of account opening. By analyzing KYC application data against behaviors of known mule accounts, these models provide a sophisticated layer of security, enhancing early detection and ongoing monitoring capabilities.
ADI's end-to-end Fraud Management solution empowers financial institutions with AI-driven insights to detect and manage fraud. By scoring KYC data and monitoring transaction behaviors, the system flags unusual activities for investigation, streamlining case management and enhancing detection capabilities through advanced analytics and customizable workflows.
ADI integrates AI with traditional transaction monitoring to reduce false positives.
By analyzing alert outputs and past decisions, our models predict false alerts, closing them automatically. This shift allows teams to prioritize critical cases, cutting operational costs significantly, with a 42% automatic closure rate at 98% accuracy.
Significantly decreases the operational expenses of compliance teams by reducing alert workloads by 40% or more, thanks to a high accuracy score of 98%.
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Achieves a 42% rate of automatic alert disposals with a remarkable 98% accuracy level, streamlining the alert management process.
Offers a flexible scoring mechanism that works with any monitoring system, whether in-house or externally acquired, allowing for customized operational adjustments.
Enables investigators to concentrate on high-priority cases by automatically closing alerts deemed as false positives, enhancing efficiency.
ADI’s dual-model approach targets the nuanced challenge of detecting mule accounts.
By evaluating KYC data and account behaviors against known mule patterns, our solution boasts a 42% success rate in identifying mule accounts and ensures 90% accuracy in new customer verification, significantly enhancing fraud prevention.
Strengthens the new customer onboarding process with scored KYC data, incorporating ADI’s POI dataset for an additional layer of risk assessment.
Leverages insights from real-world typologies to improve detection logic, making the system more adept at identifying mule accounts.
Elevates mule account detection capabilities through AI-based monitoring, achieving a 42% detection rate with behavior monitoring models.
Supplements existing risk controls with AI models, speeding up the risk management process and enhancing overall security measure
ADI delivers a comprehensive fraud detection suite, leveraging AI to assess KYC data and monitor for suspicious transactions.
This end-to-end solution streamlines alert management, facilitates deeper investigations with advanced analytics, and supports a customizable workflow for efficient case resolution and audit compliance.
Provides an all-encompassing solution for monitoring, detecting, and investigating fraud, employing AI for improved detection of unusual transaction behaviors.
Features investigative tools like graph analytics to uncover non-obvious relationships between account holders, enriching investigation depth.
Includes a rules library for transaction monitoring with both standard and customizable rule-building capabilities, meeting diverse operational needs.
Ensures a complete audit trail capability, facilitating thorough tracking and documentation of all actions taken during the investigation process for compliance and review.
