The new and innovative methods, procedures and technologies are being developed constantly for the purpose of the successful, effective and up-to-date implementation of AML (Anti-Money Laundering) and CFT (Combatting the Financing of Terrorism) requirements. Recently, on November 26th, 2021 I was a panel speaker for 1st Compliance Conference in Turkey where the AML/CFT compliance was the main focus of the discussion. According to international standards, AML/CTF compliance is all about managing the risk. According to the Financial Action Task Force (FATF), if financial institutions are going to run a compliance program, it must be risk-based. Due to complexity of determining the risk, and benchmarking with regulatory standards, a mountain of paperwork emerges and human resources are not enough for such an operational task when all the process is taken into account, so a risk-based approach should be used and the emerging technologies are capable of providing this enhancement for financial institutions. Recently, the FATF released a report focusing on and indicating both the opportunities and challenges of the new technologies for AML and CFT.
The report emphasizes that the new technologies are able to support AML and CFT efforts by ensuring increased cost-efficiency, pace and effectiveness while at the same time they can support the institutions in achieving a better implementation of FATF Standards and consequently higher rates of financial inclusion. The main advantages of the improved technologies are smoothing the processes such as data gathering and analysis, better monitoring and detection of risks related to money laundering and terrorist financing in a relatively shorter period of time. As the speed, accuracy and efficiency of the transactions’ monitoring, identification and data sharing among institutions increase with the help of these new technologies, the fight against the financial crimes is also getting fortified.
On the other hand, the FATF highlights challenges that accompany the developments coming with the new technologies. It is possible to deduct that the main challenges are closely related to operational and regulatory limitations. The traditional point of view in the regulatory landscape and frameworks as well as in the AML/CFT compliance requirements makes it harder for the new technologies to be improved and adopted. According to the FATF, conventional financial institutions are slower to adapt to these new technologies, whereas FinTechs have different ways of doing business but have a risk appetite. Previous year, the increase in FinTechs also increases the demand for Regtech, and we have observed that FinTechs have a modern approach that can offer all the services provided by banking. Cost should not be the biggest barrier for banks and other financial institutions to use emerging technologies. Approximately, 8 billion dollars invested in RegTech software each year, but only one bank can be cut off 8 billion dollars a year due to non-compliance with AML / CFT regulations, and this can result in a riskier situation in terms of cost and loss of reputation. With this technology, the aim is not only to reduce false positives, but also to increase the customer experience, as well as to reduce repetitive work. As Fineksus, we are constantly investing in new technologies, the significant one we have made in recent years is in AI and Machine Learning. By adapting these technologies to our software programs, we have achieved 95% confidence in for the success of these technologies we have developed.
Who is using new technologies?
Mainly multinational financial institutions, internet-based firms namely, FinTechs and other similar FIs, and finally retailers and commercial banks constitute the bigger proportion. Outstanding inequalities are reported by the respondents among financial institutions depending on their size in terms of the request and implementation of the new technologies. Also, there are still gaps to fill in at the international and local level when it comes to the degree of actualizing digital innovation.
What AML/CFT functions are they are being used for?
The expectation is that the new technologies will boost the speed and reduce the costs spent on AML/CFT activities by providing cutting-edge tools and thus improve the overall efficiency of them. The most prominent advantage of employing the new technologies is the increase in AML/CFT effectiveness. It is followed by risk management, cost-efficiency and accuracy. Some natural features of the new technologies such as speed, agility, aptitude and better management are listed by the respondents as important factors supporting the overall effectiveness of AML/CFT efforts.
Which underlying technologies are being used to perform those functions?
Artificial intelligence (AI), which also encapsulated ML (machine learning) and NLP (natural language processing) tools, Application Programming Interfaces (APIs) and specific tools designed for customer due diligence (CDD) procedures are high promising technologies to support and enhance AML/CFT efficiency.
Techniques of technologies and practices in use
The adoption of digital solutions in AML/CFT processes expands day by day as they have proven to be competent in detection of the risks and monitoring suspicious activities both in private and public industries especially with the support of the techniques that are based on artificial intelligence (AI), machine learning (ML) and natural language processing. As the enhanced real-time monitoring and sharing of information among related parties promoted better supervision on the public sector, the private sector benefited from improvement in onboarding procedures, risk assessments, communication with qualified parties, liability, cost-efficiency and overall management.
With mobile banking, the volume of transactions has increased a lot in recent years. We cannot sit down and do a static process to manage this volume because here AI and machine learning act as the workhorse after all and to provide a more refined solution for human decision making.
- Artificial Intelligence (AI):
One of the most preferred and functional technologies used in AML/CFT procedures is the AI technology and machine learning as the subset of AI that aims to teach a computer system to read and learn from data without a need for human intervention. ML technology is mostly used to analyze data for creating an automated analytical model, therefore it is commonly operated for supervisory purposes. The Central Bank of Brazil designed a priority matrix in 2019 that determined which supervised entities to prioritize in the Annual Supervision Planning (ASP). The priority matrix was further developed in terms of risk-management by using machine learning technology. With the inclusion of an ungoverned learning method in the matrix, the risk-based approach was achieved and the risk scores of the supervised entities were calculated.
- Natural Language Processing and soft computing techniques:
Natural language processing (NLP) is another subset of AI technology that empowers computers to comprehend, interpret and control human language. The technique that uses logic to process uncertain or rough data by referring to different multiple values to achieve an inexact but functional output is called fuzzy logic.
Italy’s Financial Intelligence Unit (UIF) and the Directorate General for Financial Supervision come together to develop an application based on fuzzy logic that analyzes quantitative data for checking AML indicators and helping with AML/CFT risk assessment of non-banking financial intermediaries.
Another example of NLP use is from the Central Bank of Brazil (BCB). The Natural Language Processing (NLP) SupTech Project that was approved in April 2020, intends to operate NLP based AI applications for the purpose of better supervision, lessened risks in compliance-related matters, and higher productivity.
- Distributed Ledger Technology:
DLT is very effectively used in managing requirements related to customer due diligence (CDD). It supports the system by dealing with user anxieties about the process, offering better cost-management in the private sector and increasing accuracy and quality of the data collected.
Nine private companies from various industries came together and created an entity that seeks to handle digital identities from the perspective of users. The entity uses DLT with the purpose of giving the users the possibility to manage their activities by using a wallet so that the transactions and CDD processes are as simple as possible.
- Digital Solutions for Customer Due Diligence:
a) Digital Identification solutions
eKYC (electronic Know Your Customer) is a preferred system for electronic ID verification that is implemented by many institutions as an effective digital solution for CDD procedures. India is one of the countries that adopted the eKYC system by using a 12-digit ID number issued by Unique Identification Authority of India (UIDAI), called Aadhaar.
b) Machine learning for CDD purposes
Brazil’s Systemically Important Financial Institutions (SIFIs) employ a ML-based monitoring system in their CDD and other identity management processes for their employees and partners for the effective, faster and more accurate detection of new money laundering or terrorist financing risks.
- Application Programming Interfaces (APIs) :
Finally, the APIs offer great benefits to the financial institutions in their AML/CFT efforts by enabling an integration of various incompatible systems. The main benefits of APIs are:
- Increasing the level of interoperability in traditional banking data and offering fragmented models instead of sticking to the siloed systems
- Higher accuracy in outputs and better optimization of the resources as a result of enhanced automation
- To support and simplify the customer onboarding process, providing clustered and standardized data for achieving a more accurate risk profile
As a conclusion, we will keep using brand new technologies as our forces to tackle financial crime, but we should also be aware that using these technics will come with new problems besides its colloquial advantages. These problems should not stop or slow down our way of adaptation and encouragement of regulatory authorities will also help us to tackle them.
Ahmet Vefik Dinçer, CEO