naztech Enterprise Financial Fraud Management Solution
Our intelligent autonomous AML suite combines domain expertise, Machine Learning, AI, RPA & Intelligent Automation to detect, manage, and resolve your customer’s suspicious financial activity.
Why Modern Fraud Detection Technology is Important to Implement your AML systems?
Money laundering is the process of transferring large amounts of money generated by criminal and illegal activities such as narcotics and illegal weapon trading, bribery; tax hiding, etc., and all these transactions appear to come from a legitimate earning source. Thus Anti Money Laundering is a common issue for financial institutions. The conflict between the various financial sectors and money laundering entities has led financial institutions to set up technologically intelligent systems to save money and time in complex AML detection processes. Our AML detection system uses automated analytical and detection technologies such as AI, machine learning to combat various financial crimes effectively. Moreover, financial institutions have to comply with central compliance guidelines where regulators impose severe sanctions for such offenses. Bank Branches are always in a threat of supervising sanctions and risk damaging their reputation than ever. Therefore it is highly important to detect money laundering and the financing of terrorism (AML / CFT) activities in financial transactions.
Adaptive Fraud Intelligence
Our Financial Fraud Management Solution provides organizations with a complete solution to detect, investigate and report the financial crime. The solution covers all key areas involved in the AML processes – including customer due diligence, profile screening, suspicious funds flow tracking, transaction and all kinds of suspicious activity monitoring, watch-list filtering, and case management.
We use advanced, innovative, and flexible detection technology, such as RPA, machine learning, artificial intelligence, and help you to monitor, investigate and report transactions activities. By considering the complex inter-dependencies between various activities, we are able to significantly reduce the rate of false-positive alerts.
With a consolidated real-time, view across the enterprise, we help you to identify financial threats, detect & prevent potential fraud and manage regulatory compliance.
Anti Money Laundering
The risk-based approach to monitoring transactions for money laundering and terrorist financing activities. Intelligent risk categorization & segmentations automatically identifies, categorize, score, and actively monitor ongoing high-risk customer activity.
naztech AML monitors transactions across multiple channels and automatically analyzes a customer’s profile and historical behavior. Using advanced analytics on data from various sources we are able to improve detection accuracy, reduce false positives and generate high-quality alerts. By utilizing artificial intelligence and machine learning, nAML proactively alerts you to a wide range of potentially suspicious activity and financial crime, including structuring, money laundering, and terrorist financing.
Fraud Detection and Management
Our Fraud Detection and Management solutions use industry-leading data analytics, customer-driven and machine learning models leveraging AI to monitor transactions and events enable faster response to new threats and reduced false positives
Adaptive fraud alerts, robust case management, centralized and intuitive management dashboards, and user-friendly reporting functionality allow you to detect, prevent and manage fraud in real-time.
Real-Time monitoring of a client’s transaction across various channels to detect structuring and/or attempts of illicit fund transfers. Use of advanced analytics that goes beyond transfer in/out analysis to identify and detect activities such as funnel accounts to terrorist financing.
Graphical views such as Sankey diagrams, geographic maps, balance graphs, and heat maps help to visualize and track the flow of funds between entities and allows users to see the debits and credits, as well as variations in volumes of funds, between entities.