AI development is moving at a rapid pace. In industries across the board, from car manufacturers, game developers, the online betting world and even medicine. AI is taking the place of old, outdated systems, with the finance sector adding it as well.
AI is now being implemented in the finance sector, especially fraud prevention, as it is able to detect the smallest details that can lead to fraud detection. However, to do this effectively, the AI needs access to massive amounts of data to analyze.
To do this, companies need to fully commit to adopting AI systems if they want fraud prevention results. Financial institutions will also all need to work together to ensure the integrity of the system and prevent any chinks that can cause a failure in the detection process.
One way that AI is helping the financial sector is through more advanced risk identification. This would usually be done by the financial institution a client was part of, and they would only have access to the information they have gathered. They would then use this information to make a decision.
With AI though, it is able to draw information and data from across the board and give a more holistic assessment of the risk, or lack thereof, of a particular client. Once again, this does rely on institutions sharing information.
Before, financial institutions would either be wary, or refuse to share information simply because it is too risky. AI allows a more secure network of sharing, drastically minimizing, and in some cases eliminating, that risk.
One of the biggest advantages with implementing AI is the detection of fraud. Fraud is big business across the globe, and there is a new way to defraud a bank developed every single day.
It is a constant battle to not only detect fraudsters, but to also figure out how they are defrauding. This is where AI comes in. AI can instantly detect the smallest infringement and react accordingly.
AI can also constantly adapt to new techniques that people use for fraud. It can detect them, learn them, and then be able to prevent the use of them in the future. It is quick and efficient, and does a better job than a human sitting at a computer.
Considering there are massive cyber hacks that occur every year, a solid and effective AI framework is required to not only stop them, but learn from them and be able to prevent them in the future.
AI is also being utilised in the investment banking sector. While it hasn’t completely taken over just yet, banks are using them to help themselves and clients with their investments and portfolios.
AI can be used to develop a more detailed and comprehensive investment strategy. Considering investments require quite a lot of information to make a solid and informed decisions, having all that information at hand will almost give you an advantage.
Making good investment decisions also requires more than just looking at a few graphs and the stock market. You are looking for potential, guaranteed growth, as well as some signals that indicate whether the decision you’re making is good in the long run or not.
These signals are very hard to spot, but with AI automation, it can pick up on every single detail and return a detailed strategy, allowing you to make more informed decisions and not leaving most of it to chance.
Like most things though, there are difficulties with implementing AI. You may think that it is the AI that is causing the problem, it might be missing certain problems or not adapting quick enough, but you would be wrong.
The main problem is that there are not enough people to manage the AI that have sufficient experience in both the financial and AI sectors. There aren’t enough people to recognise the current and future needs that the industry will need with regards to AI.
Another problem that is holding AI back is the aversion to implementing it by companies. Whether it be because of budget limitations, general resource limitations, or companies being nervous to let a computer control their security, the AI is not being implemented at the speed you would think.
Another aspect that is holding AI back, is the lack of accountability. In a regular human to human relationship, if an employee makes a decision and it can then be questioned by their employer if the decision was incorrect, and therefore there is accountability.
This isn’t the case with AI. When the AI makes a decision, you can’t call it into your office and question it and find out why it made that particular decision. AI is incredibly effective, but it is also not always 100% correct.
This combination of not being completely reliable every second of the day, and the fact that you can’t question its decision making, is something that many businesses just can’t accept.
AI is most definitely the future, and the finance industry is slowly but surely adopting AI in its business. Even though there are some challenges, AI technology is moving at such a rapid pace that these difficulties can and will be overcome in the near future, and only to the benefit of the financial world.