New sanctions are continually being imposed, making life difficult for banks, which must comply or face stiff penalties. In the past, much of the work toward sanctions compliance involved burdensome manual tasks, but today, technology can lift off much of the load. Since compliance is not an option and pleading ignorance doesn’t work, banks are turning to tools such as intelligent process automation to do the job better and quicker.
The mandate of financial institutions is to process financial transactions for individuals and businesses, but unfortunately, these institutions are sometimes used for illicit purposes, such as money laundering and terrorist financing. Effective, accurate risk assessment is the foundation of a financial firm’s risk management and regulatory compliance, and there are a number of manual and automated methods available to assess risks. Detecting and acting against suspicious activities is a must for banks today.
For several years now, anti-financial crime (AFC) regulations have prohibited the operation of shell banks. A shell bank is a bank that has no physical presence in the jurisdiction where it is incorporated or licensed and no affiliation with a regulated financial group.
Money-laundering activities should have received a fatal blow from the scandals revealed in such documents as the Panama Papers, but recent events paint a different picture: the offshore finance industry and money laundering continue to be alive and well! Financial institutions that find AML compliance an escalating struggle are not alone, but the costs of non-compliance are even more taxing. It’s past time for banks to take a closer look at their client portfolios.
Are You Safeguarding Against Hidden Criminality? The Next Gen Technologies That Could Save Financial Institutions Billions
An increasing number of European banks and their supervisory authorities are being drawn into money laundering allegations.According to the Organised Crime and Corruption Reporting Project (OCCRP) the latest allegations on ‘Troika Laundromat’
Digitally native customers are driving banks to jump into the future by embracing technological breakthroughs such as artificial intelligence, machine learning and robotic process automation. And in the process, banks are discovering the many advantages of these innovations, from cutting down on costly human errors to improving everything from fraud management, operational efficiency and trading. As they progress through their digital evolutions, many are reinventing themselves for the better.
In spite of the recent rise of protectionism amongst major trade partners, international trade growth is strong, with emerging markets providing the main impetus. Trade growth could be even stronger if not for the shortfall in trade financing supply relative to demand, a gap that is partly due to regulation compliance. Technology is coming to the rescue, not only in addressing the trade finance gap but ameliorating operations throughout trade channels.
The rapid adoption of artificial intelligence and machine learning in all corners of the financial sector, particularly in anti-money-laundering (AML) efforts, has excited and inspired onlookers and participants alike. But as with all innovations, there are pitfalls to unquestioning acceptance that can actually worsen the situations these technologies are meant to address. Human intelligence must work cooperatively and in the lead role alongside AI and ML to guarantee the best results.
Money laundering and terrorism financing are serious issues that banks must address, especially as too many financial institutions are complicit in enabling the flow of unlawful funds. Unfortunately, the need to act decisively has also resulted in a disabling tightening of trade finance, sorely needed for economic growth. The new Asian Development Bank Scorecard seeks to ameliorate the inadvertent consequences of AML and CFT compliance.
Combating money laundering is no longer a choice but a must for banks. But the effort that must go into fighting it is daunting. How can technology, especially artificial intelligence and machine learning, battle the costs and drains on monetary and human resources required for AML compliance, making the whole process a lot easier and more effective? Can AI be trusted to do the job right?