{"id":22923,"date":"2021-04-13T05:22:39","date_gmt":"2021-04-13T05:22:39","guid":{"rendered":"https:\/\/codeandpepper.com\/?p=22923"},"modified":"2023-12-21T10:02:25","modified_gmt":"2023-12-21T10:02:25","slug":"fight-against-anti-money-laundering-aml","status":"publish","type":"post","link":"https:\/\/codeandpepper.com\/fight-against-anti-money-laundering-aml\/","title":{"rendered":"AI vs. Financial Crime – Fight Against Money Laundering (AML) and Bad Actors"},"content":{"rendered":"\n

Artificial intelligence (AI) in FinTech is often associated with Big Data and analysis of customers\u2019 behavior. In reality, it can be used in a wider range. Anti-money laundering (AML) AI is used to fight financial crime and secure apps\u2019 reputation<\/strong>. After all, financial technology is all about trust. How is it done and what conclusions can you draw for yourself?<\/p>\n\n\n\n\n\n\n\n

\"Impact<\/figure><\/div>\n\n\n\n

Criminals are getting more sophisticated with each passing year. In the world of financial regulations, the term \u201cbad actors\u201d is reserved for individuals or companies that abuse applications\u2019 privileges<\/strong>. FinTech companies have to deal with them, growing amounts of complex user data and connections between these information. <\/p>\n\n\n\n

Especially, if the product is complicated, has many different services, or the app itself functions in a larger ecosystem on the market (exchanging data between companies, etc.). A few things can fall into cracks, causing legal and marketing problems. The AML AI is used to fight money laundering<\/strong> with highly specialized algorithms.<\/p>\n\n\n\n

How to fight money laundering?<\/h2>\n\n\n\n

These algorithms analyse big pools of data and raise a red flag if something suspicious comes up. Automated processes like customer due diligence (CDD), transaction monitoring inputs, and sanctions screening<\/strong> help applications\u2019 owners spot suspicious activities. <\/p>\n\n\n\n

Machine learning can help even more. With vast amounts of data to learn from, the AML AI can make an \u201ceducated guess\u201d about whether a particular behavior represents a money laundering incident. If a financial crime technology detects an occurrence that differs from the norm, it can send a suspicious activity to report (SAR) to the authorities. This way, officials can be notified about transactions that seem not ordinary, may be interpreted as a precursor to a crime, or even be viewed as a factor threatening public safety. SAR is required when transactions reach a certain level of value, international money transfers are over a certain level, or when there are unusual transactions or account activity. <\/p>\n\n\n\n

It\u2019s important to implement a know-your-customer<\/a> (KYC) solution. It\u2019s a dance between daily business activities, customer experience, and the regulatory landscape. On one hand, applications need access to customer data. On the other hand, they need to be equipped with some form of safety mechanisms, to not abuse the trust of people who do not abuse the application itself. In other words \u2013 the AML AI software needs to be reactive, not intrusive. <\/p>\n\n\n\n

Fighting financial crime with processes<\/h3>\n\n\n\n

Nothing happens by itself, nor it\u2019s given a chance. Not in the world of FinTech software development<\/a>. Processes mentioned below will utilize the power of financial crime technology.<\/p>\n\n\n\n

Customer due diligence<\/strong> is about assessing your customer\u2019s background to establish their identity and assess the risk they possess to the app or its reputation. You can do it by obtaining personal information, like name, a photograph from some kind of ID, address, etc. Then, it\u2019s about beneficial ownership and business relationships. The first is required when you\u2019re making a B2B application and you want to understand the control structure of the company. The second \u2013 when it\u2019s hard to know whether getting into bed with this company is good or not.<\/p>\n\n\n\n

There\u2019s also a question of enhanced due diligence (EDD).<\/strong> You can do it when there\u2019s a doubt about the source of funds of the user\u2019s wealth. Also, when you have questions about the nature of the business intentions or purpose of the specific transaction on the account.<\/p>\n\n\n\n

Transaction monitoring<\/strong> can involve things like sanctions screening (explained further on), customer profiling, and blacklist screening. It\u2019s about identifying suspicious behavior, increasing automation to minimize human oversight, increasing effectiveness with AML technology solutions, and boosting the confidence of regulators and business partners alike.<\/p>\n\n\n\n

Sanctions screening<\/strong> is important to keep up with changes. It\u2019s very demanding, since the list of sanctions towards money launderers, arms dealers, narcotics traffickers, human rights violators, and terrorists changes daily. Plus, the nature of law has changed. Back in the day, sanctions were aimed to impede states or organizations. Today, they are focused more on specific economic sectors or even individuals. On top of that, the list of sanctioning bodies is growing. From the United Nations (UN) to European Union (EU). From Switzerland\u2019s banking systems to Interpol. From Consolidated Canadian Autonomous Sanctions to\u2026 you get the idea.<\/p>\n\n\n\n

If you\u2019re struggling to keep up, we can help you a bit. Check the list below for guidance:<\/p>\n\n\n\n