We will remember 2020 as the year of social unrest and one which played havoc with global financial markets, driven predominantly by the coronavirus pandemic and intensified by political turmoil in the US and Europe. With reduced staffing and rushed technical implementations, the resulting confusion has left financial institutions more exposed than ever to a wide variety of cybercrime like hacks, thefts, and fraud.
A pressing concern is the rise of inadequate compliance processing, which quickly results in loopholes that are easily exploited by hackers and data thieves.
Shockingly, research reveals that some of the highest profile attacks begin with simple email phishing scams - where the victim unwittingly installs malware via an innocent-looking email. Despite their simplicity, these types of attacks have been successfully used to infiltrate top-secret government security facilities.
FATF uncover rising data breaches and financial fraud
Because of these weaknesses, the Financial Action Task Force (FATF) has uncovered incidents of money-laundering and terrorist financing in areas like Southeast Asia, particularly in Cambodia and Myanmar. The inability to adequately secure communication channels between remote workers and offices is a key factor that has led to a rise in data breaches and subsequent financial fraud.
Countries that lack proper funding for robust technology and fully compliant software often use subpar alternatives. Most times, hackers know about these software platforms and know exactly how to exploit them.
However, it's not a problem unique to poorer, third-world nations. Even the US National Security Agency (NSA) suffered an embarrassingly public hack as recently as 2016, when a covert hacking group called ‘Shadow Brokers’ infiltrated their systems and stole highly sensitive government secrets.
Data breaches are now so common that in 2017 Internal Revenue Service (IRS) Commissioner John Koskinen said that all Americans should assume that someone has stolen their data at some point.
Good tech to police bad threats
To combat this threat, governments and regulators are increasingly turning to artificial intelligence (AI) to help speed up the research and development of cybercrime defences. With well defined, globally accessible AI-drive regulation technology (regtech), the FATF believes an international standard for compliance can be achieved.
Most importantly, this technology is not an optimistic quick fix that is being rushed out, but rather conveniently the result of years of development. AI has already proven its worth in financial fields, particularly risk assessment and predictive analytics. Its ability to speed up processes through automation has proven time and again to be even more successful than expected, so scientists have strong faith that its use in compliance regtech will be beneficial.
Furthermore, the advantages of combining AI with machine learning make it not only easier to implement but consistently more productive over time.
Artificial intelligence algorithm to the rescue
All this makes the artificial intelligence algorithm the perfect option for resource-poor nations that don't have the time or money to analyze all the data necessary to implement effective compliance measures. With AI-enhanced regtech in place, these companies can rest assured that each and every failure point on the network is monitored and accounted for.
In the blink of an eye, new customers are evaluated, network connections analysed, data compiled, and solutions implemented - all without any need for human intervention.
A recent survey from data analytics firm FICO found that most Southeast Asia nations are now committed to using AI-enhanced regtech tools to meet AML standards. Dubbed the ‘Integrated AML Compliance Survey’, FICA conducted the study in May 2020 across several countries including Thailand, Vietnam, Singapore, South Korea, Hong Kong, Taiwan, Malaysia, Indonesia, and the Philippines.
What about AI-enhanced hacking?
Unfortunately, as is often the case in cybersecurity, that which can be secured can be hacked. And the technology used to create better security is often co-opted by cyber criminals to break the very same security.
Recently, hackers have begun weaponising AI to preempt security measures and develop workarounds in real-time. Used in this way, an AI can make split-second assumptions about what a security system will check next and then develop a decoy before the system even has time to act in defence.
It works in a similar way to how AI security systems do - by predicting a human or machine's behaviour based on all the data available and developing a defence for all possible outcomes.
The speed at which most AI programs can do this means they are often one milli-step ahead of the competition, second-guessing each move as it happens. When you pit two equally proficient AI programs against each other, the outcome can often be unpredictable and down to chance.
Unlike humans, an AI can remain active 24/7, monitoring a system and waiting for the perfect moment to strike. All it takes is a minor blip in the electricity grid to take an entire security system down just long enough to infiltrate. Some advanced AI systems can even trick another AI into doing its work for it, sending out stolen data in the guise of a genuine communication.
AI in Regtech
Implementing the artificial intelligence algorithm in regtech or any other scenario requires more than just technical proficiency. Since AI is based on human intelligence, it needs to be programmed differently to a computer. In fact, for it to work at all, this is a necessity, since we design computers to not think, only compute.
In order for AI to 'think' like a human it requires elements of psychology, philosophy and sociology to be hard-wired into its coding. It needs to understand what an emotional, fallible human mind would think in a certain situation, not a computer. Once again, integrating these mental aspects is only made possible by the massive amount of readily available data that the system can peruse in mere minutes.
However, this heavy reliance on data brings with it its own set of problems. Regulators are becoming increasingly wary of providing AI programs with unrestricted access to large amounts of sensitive data. The speed at which AI reaches a conclusion makes it near impossible to moderate in real time, leaving us with no choice but to trust its chosen course of action.
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