By Ravikanth Sama, Global Head, Amlock™ at Azentio
In an increasingly digital environment where financial crimes are getting more sophisticated, AI scores the highest among the emerging technologies that has the potential to take this threat head on.
The money laundering trends that have gained strength during the pandemic include the use of virtual currencies and eCommerce. This period has also witnessed a rise in the number of charity-oriented financial frauds and unlicensed money-service providers. The increasing dependence on technology and remote working patterns, has also resulted in the rise of phishing incidents, hacking, and malware infringements, among others.
An article by Matheson, a law firm focused on global financial institutions, mentions that the Interpol has projected that the global financial loss due to cybercrime for 2021 will be $6 trillion, approximately double that of 2015, with losses expected for the global economy amounting to $10.5 trillion annually by 2025.
Financial institutions are facing a substantial rise in financial crime. Violators have become more sophisticated, using innovations such as instant payment programs and blockchain. Financial institutions are now under pressure to invest in innovative solutions to fight the growing threat of financial crime.
In an increasingly digital environment, incidences of financial crime can only be kept in check, by using advanced technologies, of which artificial intelligence (AI) tops the preferred list.
To give an example, innovative models of machine learning (ML), can automate a large of number of manual checks pertinent to trade transactions, bringing down significantly the threat of financial crime.
Here are 9 ways by which AI can help financial service providers in their fight against money laundering:
- Hybrid AI processes, that depend on both knowledge-based, incorporating codified insights gained over years by innumerable AML experts globally, and data-based AI approaches, can dramatically improve the monitoring and analyses activities of financial institutions
- Leveraging customer and transactional data, AI can help identify suspicious activities accurately. The relevant data, supported by data visualisations, case summaries and risk scoring patterns, can subsequently be provided to investigative teams
- AI can make the Suspicious Activity Report (SAR) process simpler by improving the speed, proficiency and accuracy of a financial service provider’s AML reporting activities. This becomes possible due to AI’s capabilities in generating up-to-date SARs that are automatically filled with precise information
- AI enables identification and analysis of unstructured data (emanating from multiple external sources, including social media) and use this information for effective risk management
- AI-based Customer Due Diligence (CDD) and Know Your Customer (KYC) processes allow financial service providers to effectively identify and gather data from a larger range of external sources, including watch and sanction lists. It also reconciles data across internal systems to stem duplication and other errors, enhancing AML measures among customers
- By giving a superior insight into the customer’s transaction patterns, AI plays a crucial role in ensuring a highly transformational effect to the noise level generated during the AML process
- AI-based systems already have a proven track record in helping decrease false positives, which is essential for financial institutions to save money and investments in internal resources
- When a customers’ transaction data is incorporated into an AML program, ML models can analyze it to make predictions about the customer’s future behaviour
- As the regulatory compliance processes grow more technology-oriented with each passing day, AI-based systems can be vital in alleviating the effects of human error
Amlock™, Azentio’s financial crime detection and management solution, employs the latest features of AI technology to ensure innovative use of data analytics. It has been deployed by financial institutions of various sizes and geographical spread, to improve their AML and sanctions compliance processes with the efficient use of advanced analytics. Amlock™ is compliant with global regulations, including Financial Action Task Force (FATF), Bank Secrecy Act (BSA), and European Union (EU) guidelines. It supports regulatory reporting (Suspicious Transaction Reports and Cash Transaction Reports) of 35+ countries, which includes AML reporting. With an alerts library having over 200+ alert scenarios, it comes with on-premise and cloud-based deployment options.
Amlock™ provides an integrated view across data streams and includes analytical and investigative tools that transform routine data into meaningful, valuable and actionable intelligence to detect potential money laundering and meet compliance requirements.
To conclude, it is evident that AI is the most promising technology for fighting financial crimes, especially because of its capabilities to adapt to new and dynamic money laundering practices, ensuring that financial institutions are able to swiftly reposition themselves to proactively face the threat.