Deter Detect Defend

naztech Enterprise Financial Fraud Management Solution

naztech’s intelligent autonomous AML suite combines domain expertise, Machine Learning, AI, RPA & Intelligent Automation to detect, manage, and resolve suspicious financial activity.

Tailor our solution to fit your unique needs and risk profile

Adaptive Fraud Intelligence

naztech consolidated Financial Fraud Management Solution provides financial institutions with a complete solution to detect, investigate and report financial crime. Our solution covers all key areas involved in the AML processes – including customer due diligence, screening, funds flow tracking, transaction and suspicious activity monitoring, watch-list filtering and case management.

Using advanced, innovative and flexible technology, such as RPA, machine learning and artificial we give you the ability to monitor, investigate and report transactions and activities of a truly unusual and suspicious nature. By considering the complex interdependencies 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.

Integrated Solutions

Anti Money Laundering

Risk-based approach to monitoring transactions for money laundering and terrorist financing activities. Intelligent risk categorization & segmentations automatically identifies, categorizes, scores and actively monitors ongoing high-risk customer activity.

naztech AML monitors transactions across multiple channels and automatically analyze a customer’s profile and historical behavior. Using advance 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 uses 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

Flow of Funds

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 go 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.



From customer onboarding to ongoing surveillance with real-time risk rating, helping to help you accurately assess your customers and alerting you to suspicious activity


Watch List Scanning

automatically scans your customers against dozens of watchlist with unique fuzzy matching algorithms, intelligent scoring and alert consolidation to generate high-quality hits with low false positives to assist in an efficient regulatory reporting infrastructure and focusing on true target matches and not just random similarities. 


Machine Learning & AI

hybrid analytic and AI techniques, including modern statistical, machine learning, deep learning and text analytics algorithms for greater accuracy and better predictive performance


Supervised Models

Scheduled supervised models blend the latest insights with historical data to adjust to changing data patterns and keep your system performing at its peak.


Graph Analytics

identify complex money laundering schemes by looking beyond simple transaction monitoring and understanding the multiple layers and players


Real Time Alerting

scoring engine using multilayered detection methods – business rules, anomaly detection & advanced analytics for greater accuracy.


Unsupervised Machine Learning

to automatically identify customer segments and discover unusual connections through the multi-channel link analysis


Unsupervised Models

Dynamic, multi-layered clustering and anomaly detection combined to produce superior results.


Scenario Modelling and what-if analysis

apply intelligent segmentation, adjust and simulate risk with configurable risk factors. Alert Validation with Simulation


Peer Group Anomaly Detection

compares an entity’s behavior to its historical behavior, as well as the behavior of its peers.


Transaction Monitoring & Analytics

Analyze users, transactions and organizations activity and risk in order to detect money laundering


Intelligent Case Management

configurable workflow with a systematic process for fully audited investigations


Advance Machine Learning & AI technology automatically assembles self-similar groups of customers and customers-of-customers. This allows the tuning of the thresholds within each scenario but from a principled starting point.


Highly accurate superior groupings are created through discovery. This provides enhanced resolution to manage the delicate balance between signal and noise.


Our AML solution is constantly looking at newly arriving data, identifying changing patterns and suggesting updates to segments and rankings based on that information.

Start your Journey to Autonomous AML

Our nAML Software combines Artificial Intelligence, Machine Learning, Intelligent Automation and Domain Expertise to combat Money-Laundering and Terrorist Financing.

naztech is a trusted partner, providing deep expertise in custom application development, data engineering and business process outsourcing services to clients across multiple industries.

US : +1 (469) 223-9013
Email: [email protected]


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