How AI is changing the business processes of startups in finance

According to a study by Carnet Consulting Group and MCA, business interest in neural networks doubled in 2023. More than a third of companies began to use them in their work. Experts believe AI will fully automate half of business processes by 2026. In 2023, startups began actively to introduce machine intelligence.

How is AI useful to startups?

In today’s dynamic world, time is one of the most valuable resources for business. If the new project did not have time to interest the audience with its product, competitors will overcome it. Therefore, entrepreneurs need modern effective tools that will help optimize business processes and increase productivity.

AI has opened up many new opportunities for startups. It helps them to build processes, effective marketing, define growth strategies and at the same time save time and money. AI allows new projects not to spend them on many routine tasks, such as processing orders and calls, managing the warehouse. They can do without large staff costs, accelerating the start of the business and its effectiveness.

Neural networks help businesses analyze large amounts of data. This enables companies to collect, process, and make decisions much faster based on this analysis.

Previously, brands had to do this based on hypotheses, spending extra money on their testing. Today, AI helps them build strategies based on real data. Marketing and sales analysis, for example, helps startups better understand the needs of their audience and develop better customer offerings. FinTech appreciated immediately the wide possibilities of AI.

Why is the number of AI startups in fintech skyrocketing?

The global AI market in fintech is estimated at $10 billion. It is expected to exceed the $25 billion mark by 2026. Russian FinTech is actively investing in the development of AI. According to AFL estimates, the largest of them in recent years amounted to about 600 billion rubles. In 2023, one fintech corporation invested an average of 80 billion rubles in AI projects per year. The profitability of investments turned out to be three times higher than investments. And this trend has continued since 2022. Then, on investments in AI, Sberbank earned 94 billion rubles with investments of 24.7 billion rubles.

About 85% of major players intend to continue investing in AI technologies. And it’s not just their desire to make money. Financial market participants need AI solutions that will help improve the user experience, work more efficiently, and increase the level of security.

With such financial flows, it is not surprising that a large number of startups have appeared in fintech, ready to satisfy the needs of market participants.

How does AI help financial market players?

FinTech companies and startups collect huge amounts of data and need regular analysis. For example, banks have many customers. Each of them almost daily uses a number of products – cards, accounts, deposits, loans – and makes many transactions. If you think about the quantity of banks and their branches, ATMs, as well as of legal entities and entrepreneurs among the bank’s clients in our country, it becomes clear that the amount of data is really huge. Thanks to AI, banks no longer need to waste time analyzing it.

Financial organizations also need neural networks heavily to:

  • search for effective solutions in the field of information security. Fraud is expensive for financial companies. Identity thefts alone cost the market $26 billion, and each victim $1,100. AI is already helping fintech detect suspicious behavior and cybercrimes.
  • automate customer service. Chatbots interact with customers around the clock, providing them with personalized assistance. In 2023, global savings from chatbots amounted to $7 billion.
  • provide simple and fast payments. AI helped advance fintech in terms of payment gateways. Payments become seamless and instant.
  • assess the creditworthiness of customers. Of course, the final decision on the loan is made by a person, but AI can filter applications of unreliable borrowers by basic criteria. For these purposes, it collects and analyzes credit history data.

This is only a small part of the tasks that neural networks help financial institutions cope with. Market participants with a different line of business may need them for other purposes. For example, investment companies, brokers, exchanges with the help of AI can collect market analytics, forecasts, and reduce them into single schedules that reflect the dynamics of an asset. Neural networks help them automatically parse quotes, tracking even micro-movements of the market in real time.

In recent years, investing based on algorithmic data has proven effective. Computer trading strategies have already closed $1 trillion in hedge funds. AI is less likely to be mistaken than a person, which, given the increased interest of Russians in passive earnings, allows them to get, at first glance, a ready-made tool. It may seem to many that there is no need to learn financial literacy and become a professional investor, since AI knows everything for them.

Moreover, bots do not give in to emotions, unlike traders. However, maximum efficiency in investing is possible only in a combination of artificial and human intelligence. AI notices patterns, a person can analyze other events, such as a geopolitical crisis, relations between countries, dominant industries in a particular state. As you know, these factors have no less impact on the value of assets.

Neural networks help to make more accurate forecasts, but they cannot completely replace a person yet. AI provides valuable information, but critical thinking still has to be learned. Therefore, financial literacy is necessary for investing and managing finances, as well as for portfolio, risk management. And in this matter, neural networks also came in handy.

AI in financial literacy

AI is a great assistant for financial literacy startups and their clients. He not only knows how to answer people’s questions, but also helps them plan the family budget, analyzing expenses. As a result, training is faster and more efficient. In this area, neural networks are able:

  • to conduct individual financial advice and make personal recommendations depending on the goals and needs of the person (AI gives advice on savings and debt management; unlike books and articles where a generalized theory is written, AI takes into account specific numbers and the individual situation of a person or family);
  • to analyze transactions, drawing people’s attention to their financial habits;
  • to warn about the possible actions of fraudsters;
  • to simulate financial scenarios;
  • to provide the necessary information: on trends in the market, on exchange rates, on share prices.

AI is helping to take the first steps in the world of finance. For example, he can talk about the difference between assets and liabilities, revenue and net income, different investment instruments. By the way, neural networks teach people regardless of their age and basic knowledge. They communicate in a simple and understandable language, know how to adapt to the level of understanding, so they can teach even children how to handle money. AI will be able to explain more complex terms: what is diversification or insurance in banking, what is it necessary for and what are the examples.

Interestingly, you can communicate with AI in a dialogue format, almost like with a living person. For example, if you are striving to achieve certain financial goals and have requested calculations from the neural network that you do not agree with, then you can ask to send its justifications. In addition, machine intelligence can compare credit conditions, tariff plans. This involves a person in obtaining financial knowledge. But do not forget to check the data provided by the machine: while AI quite often mistakes and misunderstands user requests or provides irrelevant answers. In addition, ordinary users have yet to learn how to make requests for intelligent assistants. This is more difficult than searching the Internet.

In matters of improving financial literacy or teaching investment, it will not be possible to rely fully on AI yet. Indeed, in order to request this or that information from him, a person needs to understand that he needs it. In other words, if he has never heard of compounding, then he will not have a desire to find out what it is. For training, a high-quality and well-thought-out program consisting of theoretical and practical knowledge is needed, which will help a person go through the path “from simple to complex.”

Let’s sum up: what awaits AI in fintech in the future

A rapidly growing number of FinTech startups offers the market promising products based on AI. They are of interest to large players as tools to help optimize business processes, as well as to people who are looking for ways to preserve and increase their capital. The volume of the market and investments in it is growing rapidly, which means that the number of AI tools will increase.

Neural networks are effective not only in the field of finance, but also in most other industries. But FinTech is in second place among the areas that use AI capabilities most actively. Experts are convinced that this trend will continue over the coming years.

By Nikita Konev, founder of the Earnie investment platform

Previous ArticleNext Article