Artificial Intelligence (AI) is one of the most rapidly emerging and progressive technologies globally. We can define it as “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” (Britannica, https://www.britannica.com/technology/artificial-intelligence)
Over the next few years, AI will have significant influence not only in accounting and finance but also in most business sectors. However, there are many uncertainties around the subject, so organizations are hesitant about implementing AI technology. That is why it is essential to be aware of the risks to increase acceptance gradually.
How Does AI Transform Accounting and Finance?
Already, there are many AI solutions available for businesses to employ, and many other, more reliable and efficient, are being developed as we speak. We can categorize them into four main types: assisted, augmented, automated, and autonomous.
Autonomous AI relates to solutions that act autonomously and can adapt to different situations. Assisted AI refers to those solutions that aid human decision-making. Augmented AI enhances human intelligence by using Machine Learning (ML) to provide the user with a broader view of the subject. Automated Artificial Intelligence can be used in routine tasks, by replacing the need for human interaction.
The advancement of AI has transformed accounting and finance by eliminating the need to perform humans’ tedious and routine tasks. This way, accountants and finance professionals can focus on high-level analysis and do their jobs more efficiently. With time AI is becoming more powerful and able to handle more complex tasks. Some areas in which Artificial Intelligence can boost efficiency include risk management and assessment, fraud detection, trading, preventing cybersecurity attacks, process automation, reducing human errors, saving money, etc. Let’s look at some of these advancements in more detail.
Credit score assessment
All financial institutions are in the business of making money. That is why they need to be as accurate as they can when lending resources. Probably the most common use of Artificial Intelligence in finance is bank credit scoring. Previously, the credit score assessment involved interviews and analysis performed by a finance professional to decide whether the potential borrower’s risk of repayment is sufficiently low.
AI can provide a much faster and more precise way of doing this analysis. With machine learning and other advanced algorithms and scoring methods, AI can quickly and more accurately determine whether the borrower is eligible for a loan. An example of such AI software is Ocrolus, which allows organizations to make “Faster, More Accurate Lending Decisions.”
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Fraud prevention
With the boosted popularity of online shopping in the last few years, credit card frauds have been surging exponentially. In the past, financial institutions made strict rules to prevent such fraud, but with time, malicious hackers figured out those rules and started abusing them in their favor. We can avoid this by using AI, which evolves and “learns” to spot irregular activities, pointing them out, and even autonomously blocking fraudulent transactions. One such AI software is Vectra AI.
Automation
AI offers a significant increase in workers’ efficiency by automatically performing most of the tedious and time-consuming tasks. With the help of Optical Character Recognition (OCR), Artificial Intelligence can autonomously process documents and forms, thus alleviating finance professionals and allowing them to focus and be more effective when dealing with more complicated analytical tasks. An example of such AI software is Rossum, which many leading organizations such as Bloomberg, EY, Siemens, and others use.
Algorithmic Trading
When it comes to trading with financial instruments, speed is of the essence. In many cases, even if the trader identifies a pattern, it might be too late as the window of opportunity has already passed. Here, AI comes to play. Many stock market players are increasingly starting to use algorithmic trading to make split-second decisions and even allow the AI to automatically make trades based on predetermined (by the user) scenarios. An AI software example here is Kavout.
Potential Challenges
We looked at some of the most impactful benefits of AI in the finance and accounting sector. However, there are many obstacles connected to it, as well. Many finance professionals are hesitant to implement AI software to alleviate their work simply because of the early stage of development. Many accountants do not fully believe that their tasks can be automated and performed with higher accuracy using Artificial Intelligence. Here are some examples where we can see the potential challenges connected with the use of AI software:
Data Security
Financial data is often sensitive and confidential; thus, Artificial Intelligence software providers should implement more rigorous security measures to ensure that the software appropriately handles such information autonomously. Various security options, including data protection with regulations and certificates, are a must for the user to feel safe when using such AI software.
Transparency
To develop such AI software, you need to use customer information as input. Customers will always need assurance that their data is collected responsibly and handled securely. Moreover, the output provided by the software should be easily explained and understood by the user, which will make it even more trustworthy.
Data Intertwining
Artificial Intelligence enables the user to combine data from various pipelines to tailor the output for the task at hand. Finance and accounting professionals should make sure the input data is correctly structured to ensure that the machine learning algorithms will work according to the company’s business goals.
Conclusion
Given what we discussed above, we can safely say that AI is probably the most impactful development in the last few years. All the perks that come with it allow for more faster, more precise, and more focused way of handling tasks, not only in the finance and accounting industry but pretty much in every aspect of the world. However, to understand and use Artificial Intelligence properly, we must also know the potential challenges that come with its implication. We can be sure that the productivity and efficacy aspects will further develop in the future, while the obstacles will become fewer or even none.
Boneslav Mitev
Financial Analyst
Hi there! My name is Boneslav, and I’ve been studying and working in the sphere of finance for the last 6 years. I am always eager to learn more, gain experience, further develop the skills that I have acquired so far, and share my knowledge with others interested.
I am a sea person and most of my vacation time is spent there. I am also an avid DOTA 2 player, preferably playing with good friends.
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