How AML/KYC Measures Have Changed as Digital Banking Has Grown

The digital transformation in the economy began long before the global health crisis, but the last 20 months have certainly accelerated digital-first trends in eCommerce and banking. Leading financial institutions (FIs) now know that in order to engage technologically savvy consumers, they must provide efficient, simplified, and engaging banking experiences – all of which rising digital-only banks and FinTechs already excel at. 

According to PYMNTS data, half of customers increased their use of online or mobile banking between July 2020 and July 2021, with young individuals and affluent consumers exhibiting the greatest increases. Between July 2020 and July 2021, more than 20% of consumers who use a digital baking app “substantially” increased their usage. Digital banking app adoption rates climbed significantly at both national and digital banks: consumers raised their use of mobile payment applications by 31% and digital wallets by 28%. 

Consumers have also grown to anticipate increased access to more complex digital banking services, such as the ability to open a new account or be accepted for a mortgage or loan. However, due to the significant danger of cybercrime, banks frequently fail to provide these services adequately online or via banking apps. Banks are required by anti-money laundering (AML)/know your customer (KYC) rules to verify clients’ identities, which are not always straightforward to perform online because data breaches might provide fraudsters with access to consumer information.  

This month’s Deep Dive looks at the problems that financial institutions face in meeting AML/KYC regulatory standards as digital banking grows in popularity. It also examines how sophisticated technologies like biometrics, artificial intelligence (AI), and machine learning (ML) are assisting banks in adapting to changing market conditions while remaining AML/KYC compliant and keeping their customers secure from online dangers.  

Why Do Financial Institutions Need to Adopt AML/KYC for the Digital-First Market? 

Digital – first banking – an umbrella phrase that includes traditional banks, digital-only banks, and FinTechs – is making inroads around the world, offering people with convenient and safe access to online banking services. While laying the basis for fully digital banking solutions to emerge, regulators in many countries have also permitted traditional banks to access new innovations that will allow them to transition to digital-first banking.  

For example, open banking promotes data exchange across networks and third-party transactions. It also opens up new potential for non-banks to compete by providing consumers with a broader range of customized services. In the meantime, cloud hosting enables banks to extend their infrastructure and gain access to next-generation systems. It also allows financial institutions to comply with local data hosting and protection rules. AML/KYC compliance remains critical in traditional banking, and electronic know your customer (eKYC) technology can assist. This technology, in conjunction with eSignatures for remote customer validation, offers digital onboarding that uses datal analytics to validate customers’ identities and minimize AML. 

Digital identity verification utilizing face comparison technology is one alternative that banks are using when opening new accounts. This feature enables banks to comply with AML/KYC laws and prevent unscrupulous actors from opening new accounts using stolen identities. New clients can use their smartphone cameras to take a selfie and photograph their government-issued ID. Following that, the documents are validated using modern computer vision and biometric facial comparison technologies. 

Banks are also implementing innovative technology to combat identity theft and account takeover (ATO) fraud, such as behavioral biometrics. Fraud teams can continuously watch user activity during a mobile banking session, identifying irregularities in finger pressure, navigation, and swipe patterns, and then requiring additional authentication if the user does not appear legitimate.  

FIs also use real-time behavioral analytics to monitor banking transactions for fraudulent activity, depending on data recognition of consumer behaviors rather than aggregated consumer data to detect changes. The latest adaptive behavioral analytics tools, powered by AI and ML, deliver real-time insights into customer behaviors and fraud detection. These cutting-edge solutions allow financial institutions to better analyze client behavior, spot abnormalities, identify suspicious behavior, and prevent fraud before it occurs. 

The Advantages of Using AI and Machine Learning for AML Compliance 

Historically, financial institutions have spent a significant amount of time, money, and effort to comply with AML/KYC requirements – regulatory compliance costs US banks $25 billion per year. Compliance caseloads are increasing as banks struggle to adapt to clients increased digital habits, and AI and ML technologies can be a feasible answer. Increased interest in AI and ML can be related to the pandemic’s soaring surge in digital transactions for goods and services, as well as skyrocketing online crime and identity theft. The health crisis has placed new security demands on AML compliance teams that traditional technologies and processes cannot meet.  

Such anti-fraud solutions rely on deterministic systems, which have difficulty recognizing changes in online behavior, resulting in more false positives and lower productibility. AI and machine learning are feasible alternatives since they are dynamic in nature and can adapt to changing behaviors as well as respond more effectively to emerging threats. Some AI and ML solutions can even be integrated into existing compliance infrastructures.  

AI and ML for AML compliance have seen significant uptake among mid-market and tier II institutions, according to a recent poll of FI decision-makers on the influence of the pandemic on their AI and ML implementation plans. According to the poll, 15% of participants indicated they are piloting AI solutions, 21% said they have adopted an AI solution, and another 21% said they aim to do so within the next 12 to 18 months. Nonetheless, 27% of FIs stated that they have no present implementation plans.  

Recognition of the benefits of AI and ML for AL compliance is driving adoption, as is regulatory support, with 66% of survey respondents reporting that their regulator was supportive of AI/ML deployment. Regulators in the United States, the United Kingdom, and Singapore are among those who encourage, but do not enforce, technological innovation for AML compliance.  

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