An array of financial crime and cyber security challenges plagues the modern world. The digital infrastructure has surely provided a better way to transact and purchase goods or services. However, cybercrimes, including identity theft and data leaks, have made it easier for hackers to access confidential financial records. There is a growing need for robust cyber security measures that can help ensure the safety of data stored on online servers. Deploying artificial intelligence (AI) and machine learning (ML) technologies can help to address these challenges to a great extent. Communication surveillance should also be improved to counter cyber thefts. Let’s learn more about how this can be achieved.
Understanding communication surveillance
Communication surveillance can be broadly explained as the act of monitoring, collection, and preservation of communication data that has been intercepted over different communication channels. In this process, a third party intercepts this communication data between two or more parties. Interception here can be in different forms, such as monitoring, diverting, duplicating or storing communication-related information. It is usually carried out by law enforcement and intelligence agencies for security reasons.
What are financial crimes?
Before we dig deeper into how communication surveillance is used to tackle financial crimes, let’s understand what financial crimes are. Broadly, it can be explained as criminal activities that are carried out with the intention of economic gain by individuals or crime syndicates. Earlier, financial crimes were limited to money laundering, but today it has expanded much beyond that. This has created an urgent need for regulatory bodies to monitor suspicious activities and keep a check on financial crimes. Some of the most common financial crimes that we see today include money laundering, terror financing, tax evasion, market abuse, insider trading, information security, information security, etc.
Communication surveillance and financial crimes
Establishing a direct connection between communication surveillance is hard in the first instance. However, communication surveillance can help to address and overcome these challenges to a great extent. So, what goes into this process? Well, reviewing communication is the first step after a breach is recognised. Financial crime teams work in conjunction with the communication surveillance team to monitor and pause the illicit flow of money. The communication data helps to build a narrative that evaluates how the crime happened. It also sheds light on the parties involved in this crime.
Traditionally, the technologies deployed to investigate financial crimes were limited to Know Your Customers (KYC), Customer Due Diligence (CDC), transaction monitoring, etc. Most of the practices that have been used here are limited to investigating the matter after the crime has taken place. It doesn’t include a proactive approach to identifying criminal patterns beforehand. These measures do act as an important deterrence for financial crimes. However, they are not that effective to monitor and investigating modern-age financial crimes.
Tackling financial crimes with communication surveillance
Financial crimes can be tackled using a methodological approach that involves partnering with the communication surveillance team. A strategic partnership between the financial crime investigation team and the communication surveillance department can help to provide the complete picture. Communication in the digital era has evolved beyond phone calls and text messages. It includes various other communication channels such as Zoom, Slack, email, etc. Tracking these channels can be challenging, but it is needed to build a robust strategy.
To tackle financial crimes head-on using communication surveillance tactics, you need to go beyond just capturing communication data. It is important to understand the context behind the communication to reduce false positives. Incorporating automated surveillance technologies can be a game-changer for controlling and monitoring financial crimes. Artificial intelligence and machine learning technologies can be deployed to flag the riskiest transactions. This will make it easier to manually review selected transactions for financial crimes.
Today, the communication surveillance landscape has also become quite complex. Financial institutions are operating across different nations and their employees are using multiple communication channels, including Zoom, emails, Slack, etc. Besides this, they also communicate in different languages and use a wide range of lingos. All these diversities can add to the complexities of communication surveillance. However, there are some pre-built AI & ML models which are helping financial crime teams to detect financial breaches and evaluate intent.
