The good, the bad, and the quickly adaptable/predictive algorithms:
From “I, Robot” to iFinance
Short answer (but you will want to keep on reading): both.
Artificial intelligence (AI) is no longer science fiction with thrilling tales of robots taking over the world; it is real, current, practical science. Artificial intelligence has already surrounded us in many facets of our day-to-day life. For example, predictive text, or voice recognition such as when you use Siri or Google are commonplace examples of AI usage among laypeople.
Technology driven industries are the ones most likely to try and exploit AI to its fullest potential, and the financial industry is no exception. While the eagerness to integrate AI into the financial sector has waxed and waned over the past few decades, it now appears that finsec is ready to dive head-first into AI as a standard for handling customer transactions, financial risk assessment, industry regulatory compliance and reduced institutional costs (read: replacing placing salaried employees with low-maintenance, single-cost AI installation).
AI is already extremely promising for convenience and multitasking. Take for example Amazon Echo. While washing dishes or making dinner one can access news reports, request a song be played, order a taxi or even (amazingly by how unnecessary but also how freaking cool it is) turn on or off your home’s lights or adjust your thermostat, all using only your voice.
This is AI technology that anybody with an Amazon account can purchase. What could possibly be the limits for AI use in the financial industry, a technology driven sector with emphasis on the cutting-edge and a perpetual increase in efficiency?
In finsec, AI is already in place and rapidly developing thanks to the exponential rate of software design advancements and affordability.
Today we are going to go over how AI is proliferating within the financial industry, and also the benefits and drawbacks that come with using this still young technology.
How AI ties into the financial industry
There is no other business sector that is more focused on developing and implementing AI for speed, accuracy, and efficiency as much as the financial industry.
Titans of the wealth management industry, such as Barclays and Charles Schwab are already implementing AI into their operational infrastructure. According to Barclays, they are “actively pursuing” the use of AI to improve the customer experience in an effort to boost their slumping stock value. The goal is to incorporate hands-free, voice activated financial management for customers, which ten years ago would have been laughed at for plausibility.
AI in finsec doesn’t just stop with the customer experience. Wall Street trading pits have been entirely transformed, with the majority of trading now performed by AI computers. Soon, gone will be the days of cocaine-fueled 20-somethings flashing frenzied hand signals on the trading floor. In the near(-er than you think) future, almost all stocks will be bought and sold not through a middleman, but through a middle-computer.
Next we are going to get into the benefits and threats that AI poses to the financial industry.
Finsec benefits of using AI
Most business executives and managers can make an assumption of the benefits that come along with using software to handle operations in place of people. Direct savings on time and money are obvious, but the benefits also run a bit deeper than that. Before we go into the technical aspects of AI benefits for finsec, consider the predictable behavior of computers over people.
Circumventing personnel issues
Say you have an educated and experienced employee but down the road you discover that they have personal issues that interfere with their performance. Either tardiness, attitude, substance abuse, you name it, and you have tried talking to them but to no avail. Now you have to let them go and replace them.
With AI, personal issues are null, and if there is an issue with the software it is a one-time fix.
Technical benefits of AI in finsec
Again, some of these may be obvious, but they underscore how valuable AI is for saving time and money for a financial institution. The benefits to using AI in place of human operators are:
Reliability in regulatory compliance
Personalized degree of risk preference in investments
Increased efficiency through standardization
Enhanced customer service; speed and effectiveness
These are all valid benefits to the industry, and why finsec/fintech executives responded this year with the following expectations regarding AI: 49% plan on incorporating AI for risk assessment, 29% plan on it being a boon for monitoring money laundering, and 26% plan on incorporating AI for regulation and compliance.
Especially with the push for banks and financial institutions to monitor compliance and have anti-money laundering measures up to snuff, AI comes to the rescue. AI systems can be programmed to investigate and calculate whether a transaction is committing a crime or not in mere milliseconds as opposed to the hours it takes a human monitor to investigate. The savings on time, and thus money, are in the very least extreme. Not only is time saved with AI, but so is the risk of human error during analysis and determination of risk.
The threats of AI to finsec
Besides the threat to the global finsec employment rate, AI poses other less blatantly obvious threats to the industry.
Of the primary threats posed by AI to finsec is the potential error rate due to its technological infancy. While software does exactly what it is programmed to do, there is still a human responsible for the initial programming. A single programming error can be catastrophic, as in the case of what happened to Knight Capital, who lost $400 million in 30 minutes due to a programming glitch.
Another major concern for financial executives is data security and present lack of trustworthy AI regulation. In line with the previous concern, AI is only as good as who has designed it, but also whose hands it is in.
Data and intellectual property security is a tremendous threat to any new technology. On one hand, regulation is required, but how trustworthy is the state when they have the AI source codes for regulatory examination? A handful of Chinese hackers were recently able to hijack the personal information of over 20 million US federal employees from a government database, so AI developers are understandably hesitant to hand over their source codes to the feds.
However, without regulation data security is as good as anyone’s guess. Implementing AI in finsec is still treacherous terrain, and poses risks to the industry until kinks are ironed out and it becomes the industry standard.
What comes next?
There is no doubt that AI can be invaluable for the financial industry, but it comes at a price. We expect to witness both success stories and tragic failures over the course of the next few years. With any first-generation technology there are going to be bugs to solve, and a learning curve before intimate industry familiarity with AI is obtained.
That being said, in the long run AI is not only going to revolutionize the financial industry, but become the industry itself.