In the last year, the payments industry worldwide has undergone a huge transformation, and the momentum of these changes continues. While we may be a long way off from becoming a completely cashless society, businesses globally are moving towards touchless and online payments methods as the way forward.
Financial products and services that have proven the test of time are now being rendered obsolete, re-shaping the landscape of financial institutions, and presenting new challenges in risk management and financial crime.
There are several factors influencing the challenges for financial institutions in the prevention and risk management of financial crime.
As a ripple effect of increasing customer demand, technology is quickly driving huge changes in the way organizations deliver products and services to the customer. But with increasing connectivity and the continuous development of financial solutions, comes the high risk of fraud, money laundering and related financial crime including terrorist financing.
Technological advances have given rise to more and more sophisticated transaction monitoring financial crime solutions. Anti-money laundering (AML) transaction monitoring software allows banks and other financial institutions to monitor customer activity in real-time for risk. Advanced analytics and data, combined with a customer's historical information and account profile can provide financial institutions with a complete view of risk levels, and predicted future activity.
As well as monitoring cash deposits, withdrawals, ACH activity and wire transfers, advanced AML transaction monitoring software can also generate reports and alerts to detect suspicious activity.
Customer identity verification is a priority for every financial institution. Technology advancements have allowed customers to use their smartphones, for example to authorize a financial transaction using built-in facial, voice or fingerprint recognition. A person's identity can quickly be confirmed by comparing them to a pre-existing database, saving time and expenses.
While biometrics can help prove identity, and curtail financial crime, the information gathered on each customer is valuable and sensitive, so financial institutions need to use due diligence to protect it. If used separately, biometric checks have a potential to produce false positives. False positives could occur in facial recognition for example, by wearing a mask, or voice recognition could produce false positives by pre-recording a voice.
For governments and regulatory bodies worldwide, AML compliance and terrorist financing are huge priorities. Anti money laundering solutions and compliance legislation are becoming more complex. Regulators are forcing financial institutions to supply more and more detailed suspicious activity reports. Compliance is so heavily monitored that if financial institutions fall short on these obligations for any reason, they risk crippling enforcement action that could run into multi-billions of dollars. Compliance solutions that meet regulatory standards are crucial for any financial institution.
One of the challenges with compliance in the global financial world is that anti money laundering regulators adopt different approaches in different countries. For example, compliance regulators in some smaller countries tend to focus on issues more domestically, while others adopt a much higher standard of compliance equal to those in place in North America and Europe.
There are many various technologies applied to AML transaction monitoring today. Artificial Intelligence (AI) has become an important and necessary strategy to combat money laundering and terrorist financing, as well as other financial crimes. The fact that criminals themselves are using more and more sophisticated technology is a huge driving factor in the increasing adoption of AI in the fight against anti money laundering
Machine Learning (ML) is one type of AI that uses multiple algorithms to recognize patterns in bulk data. The development of machine learning has seen big improvements in the collation of client data through natural language processing. This is an area where learning algorithms can translate human communication into machine-readable data which can better identify suspicious activity while reducing the incidence of false positives - and false negatives. In the UK for example, around two thirds of financial institutions are already using machine learning.
Image source: Napier - article on machine learning
AI technology has evolved so rapidly that financial institutions are willingly adding it to their arsenal of AML compliance and transaction monitoring solutions. Here are some of the many benefits of using advanced AI as a monitoring solution.
False positives are a constant challenge, costing time and money, AML compliance issues and even the risk of huge inconvenience to customers. AML transaction monitoring and screening measures can unfortunately create alerts to suspicious activity for certain customers. For example, a customer who makes several cash withdrawals from different bank branches might raise a suspicious activity alert, even though the transactions are legitimate. False positive AML alerts would mean that AML compliance teams may need to freeze customer accounts during remediation. AI could potentially reduce the number of false positives without compromising regulatory obligations.
Machine learning can also automate the process of tracking anomalous behaviors, continuously monitoring and detecting suspicious activity patterns as they occur. Due to the vast volumes of data that flow through a financial organization, the task of identifying complex behavior patterns is almost impossible for humans alone to manage effectively.
AI is proving successful at keeping up with sophisticated criminals. Not only can it detect suspicious behavior, but by design, it can support AML compliance and increasingly strict regulatory expectations. It can also help to protect against the chance of being linked to, or even facilitating financial crime.
The data collected through AML transaction monitoring plays an important role in economic sanctions. With cross-border banking and the complexities of today's financial systems worldwide, it can allow criminals to exploit vulnerabilities and engage in money laundering and terrorist financing activities. Economic sanctions restrict or prevent business relationships between certain countries and individuals, and help to enforce anti money laundering policies worldwide.
While this blog has focused primarily on the importance of AML and fraud detection, transaction monitoring does more than detect suspicious activity. It allows financial organizations to gain deep, real time insight into data to improve customer satisfaction and grow revenue streams while streamlining operational costs.
IR Transact is a transaction monitoring solution that can simplify the complexity of managing a modern payments ecosystem. With real-time visibility into your entire payments environment, Transact can analyze data, transactions and trends to help you streamline the payments experience. By turning data and detailed analytics into intelligence, you have complete management and control over your payments environment, allowing you to spot patterns of behavior and ensure optimal performance from your payments system.
Click here for a comprehensive guide to real time transaction monitoring with IR Transact.
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