The Role Of AI In Finance

Nowadays, artificial intelligence(AI), machine learning and robots have become unimaginable and infeasible business scenarios, which are profitable investments. In the financial field, operations have been trusted in accounting, fraud detection, customer credit rating, resource planning and reporting. However, the introduction of technology has brought new challenges and risks.

Automation benefits

The algorithm responsible for data network security can detect fraud before it occurs, and quickly check transactions of all product portfolios of the bank. An individual loan can be evaluated as a potential borrower faster and more accurately by AI than a living expert, and more parameters can be considered.

Protect the company from employee errors by automating daily processes. Robots can also perform more functions, reducing company costs. Therefore, the bank introduced a robot cash register that can call customers with less debt. It is predicted that if you believe that AI has 30 processes, you can save 4 times the cost, up to 85 million rubles.

Financial institutions use artificial intelligence to make WeChat robots to answer customers’ simplest and most common questions. The robot can also quickly form a product portfolio according to the preferences and interests of specific customers, and prepare detailed expense reports and notify payment bills.

Another core area of the financial sector, where AI is necessary, is compliance with regulatory standards. It can monitor changes in the law and help comply with the law – starting with the “law”; “Know the customer”; combine the money laundering control rules with the asset management law.

Why train machines?

Machine learning(MO) is a technology based on artificial intelligence. It is based on mathematical models and is used to identify patterns of data arrays and predict situations.

How does MO actually work? As time goes by, the blacklist of counterparties of all companies is increasing. This is a company with high default risk. Initially, people who delay payment or register in the hazardous jurisdiction will be absent. As time goes by, filtering becomes more and more complex. Machine learning will help identify previously suppressed patterns related to macroeconomic indicators, credit ratings, third-party auditor data, and the results of companies on the Internet. Technology is better than people who may not be able to handle so much information.

Innovation challenges

However, the role of AI is not without problems. The most important thing is that there are not enough qualified people. This study shows that 30% of people in the financial world only listen to this word, but do not know how AI works. Today, the entire industry is facing an important task to improve the level of technical literacy.

The second serious problem is the lack of job data. The larger the initial data, the higher the accuracy of AI prediction: the error probability of small samples is 20%, and the error probability of large permutations is 2%.

The introduction of AI into the business of the financial sector is also hindered by some other obstacles, such as operating costs, lack of obvious advantages in the use of civil defense, regulatory requirements and ethical issues.

New technology – new risks

When introducing new tools, the company is faced with risks that have not been experienced in practice before, which may lead to financial and judgment costs. This leads to the responsibility when mistakes occur, that is, the legal issue of who will be blamed, whether financial experts or AI developers.

Considering practical examples, the trained algorithm may not always be able to avoid bias. Therefore, historical samples show that women are less and less likely to approve loans in recent decades. The data provided shows that the algorithm is an unreliable female borrower, even a borrower with good credit. The conclusion will be “will be rich”. The bank may face claims from regulators, who believe that there is a gender difference in these decisions.

Due to the introduction of artificial intelligence and machine learning, the financial system will expand, which is related to the expected increase in the number of financial transactions by 2025. A person cannot process so much information, but this does not mean that AI will let living experts leave the financial industry. If algorithms are used for daily work, employees always have ultimate control and communicate with customers in real time.

conclusion

Generally speaking, AI is really a good financial tool, which can avoid complex situations and arrange work, which usually requires great efforts of human beings. When you have a robot, It can hardly make any mistakes. But in the financial field, artificial intelligence plays an increasingly important role, but it may also lead to other problems.