The challenges faced by financial institutions (FIs) regarding money laundering activities have increased substantially in the globalization era. Additionally, there is the rising menace of terrorism financing and counterfeiting. As money launderers become more sophisticated, the effectiveness of Anti-Money Laundering (AML) policies is under heightened regulatory scrutiny. Probability of banks facing rigid penalties and reputation loss in case of shortcomings in AML management have increased.

AMLOCKTM is ideally positioned to help FIs and other organizations subject to compliance requirements. It is compliant with all the relevant KYC, transaction monitoring and regulatory reporting requirements and assists banks in proactively detecting and managing money laundering transactions.

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AMLOCK Lite caters to small and medium non-banking finance companies (NBFCs). It is specifically designed as per NBFCs regulations. It enables these businesses to fully comply with AML regulatory requirements, covering KYC processes, sanction list screening, risk classifications, transaction monitoring and regulatory reporting, including Suspicious Transaction Reports and Currency Transaction Reports.

AMLOCKFinancial Crime Detection and Management Solution (FCDMS)

AMLOCK FCDMS is the enterprise level end-to-end financial crime management solution. It integrates the best of anti-money laundering and anti-fraud measures to effectively identify, manage and report financial crime. It provides various features that cater to the Know Your Customer (KYC), profiling, risk categorization, transaction monitoring and reporting requirements of financial institutions. All the features that form part of this offering are in line with major Global AML regulations.

Financial Crime Detection

AMLOCK Analytics

AMLOCK Analytics brings the latest dimension of Analytics and Artifical Intelligence to uncover hidden AML patterns / risks. This model uses various statistical methods and machine learning algorithms to derive an analysis and predictions based on institution specific historical data. It helps financial institutions to meet their most critical challenge of managing huge false positives.



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