Artificial Intelligence in Fintech
The introduction of AI in different industries quickly proved itself to be a very successful endeavor. The Fintech field is not an exception to this rule – more intelligent tools and solutions can help both individuals and companies improve their business efficiency by simplifying resource management and reducing costs.
The Fintech industry is highly lucrative and has been growing nonstop for over a decade. The overall growth rates slowed down considerably in 2022 due to the slowdown in investment volumes, but the overall results of the industry are still setting new records with each passing year.
Fintech segments and AI assistance
It is not particularly difficult to see how introducing AI into the field of Fintech is seen as a highly positive event. At the same time, there are some segments of Fintech that AI can improve the most. These four segments are productivity, security, customer service, and investment.
The productivity is a relatively apparent factor since one of the most prominent use cases of AI-assisted software is the capability to automate menial and time-consuming tasks. This can open up plenty of additional free time for users to work on more meaningful tasks, boosting total productivity in the process.
The security aspect of AI introduction is not as apparent, on the other hand. However, in a world where ransomware attacks are performed daily and tend to evolve at an extremely fast pace, the introduction of AI-related security measures makes it much easier to monitor activity and look for unusual and suspicious patterns in behavior, improving overall security in the process.
The customer service has been one of the most apparent advantages of AI, ML, and LLM development for over a year now. The introduction of chatbots based on Large Language Models simplifies many customer service interactions, which can benefit both the business and the customer. The former receives an overall productivity boost, while the latter receives a guaranteed answer to most simple questions in a matter of seconds.
The investment aspect of the Fintech industry may be the least apparent one on this list. It covers the ability of AI-assisted advisors to manage various assets worldwide using various calculations and predictions to find the best possible investment avenues. There is also the fact that newer, more innovative AI-oriented platforms can potentially find or create completely new investment channels.
The role of AI in Fintech
The total value of the Fintech market is said to go over $60 billion by the year 2031, significantly boosted by the widespread acceleration of new technology introduction for most industries on the planet. There are three main factors that are contributing to Fintech’s explosive AI-related growth:
- The inevitable fusion between Fintech and similar markets and niches – insurtech, regtech, etc. Introducing AI into this field significantly boosts the total value of software that can work with multiple industries simultaneously (cross-disciplinary software).
- As horrible as the COVID-19 pandemic was for the planet in general, it also led to an incredible acceleration of new technology adoption worldwide. In this context, AI-centric businesses and solutions can do nothing but thrive.
- Efficiency is a massive advantage of most AI integrations, especially in Fintech. AI-powered calculations for parameters such as credit score tracking bring an overwhelming advantage to businesses that are already using these kinds of tools and solutions in their work, and the rest of the market has to adopt them to keep up with the competition, as well.
With this kind of growth over a very limited time span, the most prominent role of Artificial Intelligence in Fintech is to improve upon the existing technologies and tools. This improvement can bring a variety of advantages by itself, which is something that we can discuss further below.
The advantages and use cases of AI applications in Fintech
The overall field of Fintech can reap an extremely large number of benefits from the introduction of Artificial Intelligence, mitigating or solving many of the existing issues in the field. Here are some of the most prominent advantages that can be acquired with AI applications in Fintech. This list also doubles as a description of some of the most notable use cases in the industry without mentioning specific businesses or services.
Customer service automation
Artificial Intelligence offers one of the most noticeable differences in the realm of Fintech regarding customer service improvements. The ability to use AI-based chatbots to process and respond to the majority of basic customer queries offers a tremendous performance boost to the entire customer service field, and there is even an option to make customer responses more personal and specific. Additionally, chatbots don’t have holidays or work hours; they are always online, solving one of the most significant issues of customer support around the globe – accessibility in different time zones.
Fraud detection
Detecting fraudulent transactions is much easier with AI than ever before since it relies on one of the most basic capabilities of modern-day AI and ML systems – data analysis. This advantage comes from the ability to detect and analyze behavior patterns to monitor for actions that deviate from the standard pattern. All of these questionable deviations can be passed down to a human observer to determine whether a transaction is fraudulent or not.
Financial forecasting
Data analysis alone can offer a multitude of advantages to its users, and AI-based data analysis goes a step further than that. Artificial Intelligence’s ability to analyze unstructured data to offer extensive insights into the current market situation can be a deal-breaker for many companies, with priceless insights into parameters such as short-term trends, exchange rates, long-term investments, and more.
Credit score assessment
Another significant advantage of AI in Fintech is the ability to automate credit score calculations. The credit score acts as a person’s capability to repay debts, which is also a major deciding factor when it comes to choosing whether a single person can get a loan from a financial institute. Credit score calculation is a complicated process by design, and the ability to both automate and expand the coverage of this calculation is greatly beneficial to businesses – while also having the potential of providing more people with loan opportunities if necessary.
Security improvements
As security gets more and more important for practically any business in the world, there is a lot more demand for various security measures now. This trend also affects the Fintech industry a lot, since financial data is often some of the most valuable data types in the eyes of cybercriminals. The addition of Artificial Intelligence to existing security systems makes it possible to implement plenty of new or improved security checks, ranging from simple face recognition to analyzing customer patterns to detect irregularities.
User behavior analysis
The ability to analyze user behavior can be useful in several ways, and not just as the means of fraud detection. There is also great potential when it comes to generating extensive insights based on available customer information – offering a more personalized approach, case-specific advantages for customers, and more.
Future AI applications in Fintech
At the same time, it would not be fair to say that AI in Fintech has already reached its limit. There are still at least four different fields of Fintech that are yet to adopt AI in any significant way:
- Advisor software gained incredible popularity over the years, especially among the younger clientele. Introducing AI in this field would make digital advisor software even more accurate and profitable.
- Record management is an extension of the previous field to a certain degree. It is a field of applications that are tasked with finance management on a personal level after tracking user activity, such as purchases, bills, assets, etc. The addition of AI-centric analysis is bound to make the finance management process much more effective and convenient for the end user.
- Digital banking is something that has been developing and expanding for years, putting more and more pressure on traditional financial organizations that have been around for decades. The introduction of AI can make the existing digital banking offerings better than ever before.
- Compliance can be a very daunting topic for most industries, and the Fintech field is definitely one of the most problematic ones in that regard due to the sheer number of rules and regulations that these companies have to follow. The ability to delegate paperwork preparation and similar time-consuming tasks to a trusted AI system is a game-changer for most businesses in this context.
Problems of AI in Fintech
Artificial Intelligence can greatly help the entire Fintech industry, but it also has its own share of challenges that businesses have to work with in some way.
Investments and trust
The Fintech industry relies on initial investments for a lot of its projects, and getting investments in this industry is tough enough as it is. The introduction of AI into this situation, combined with the overall mistrust to anything AI-related that some people have to this day, and it becomes easy to see how finding resources for AI implementation in a Fintech industry can be somewhat daunting.
Security and sensitivity
Financial information is, by default, one of the most sensitive data categories out there. Implementing AI into a Fintech business dramatically expands the amount of data a company has to process on a regular basis. As such, massive investments in security are inevitable for most of these companies, as well as the overall optimization of the infrastructure to ensure that all kinds of security checks are not affecting the customer experience in a negative fashion.
Compliance and regulation
The fact that so much financial data has to be processed for AI in Fintech to be of any use puts a lot of pressure on Fintech companies regarding compliance. The entire financial industry is heavily regulated, and plenty of compliance frameworks apply to customer payment data specifically – including massive fines for breaking these rule sets. Ensuring the proper compliance of a business before going all-in for AI implementation can be extremely tough for many companies.
No-code app development as a potential application for AI in Fintech
There can be plenty of different use cases for AI applications in the context of Fintech industry. Some of them are extremely large and complex, and others can be something relatively simple, such as an app that creates a summary of financial news from an RSS feed.
Lazy AI is an excellent solution for these kinds of smaller use cases. It is an AI-based no-code app development platform that uses the power of Artificial Intelligence to make application creation simple and accessible.
Lazy AI uses templates to set up specific contexts for the AI engine to work with, and hundreds of different templates are already available on the website – with more to come soon. Here are a few examples of how Lazy AI can be helpful in the context of the Fintech industry specifically:
- A daily news summarizer app that can pull the latest articles in a specific field based on Google Alerts RSS feed and create short summaries of these articles – making sure that the user misses none of the recent financial news.
- A financial news converter app in the form of a Telegram bot that uses Bloomberg’s RSS feed to access the latest financial data. This data is analyzed using an LLM model, processed, and then transferred to the end user in the form of emoji representations for the sake of “short and simple” information.
Conclusion
AI managed to become an incredibly popular term in a very short time frame, and the widespread introduction of LLMs added even more potential to Artificial Intelligence as a whole. Its overall value for the Fintech industry is tough to quantify and may be somewhat challenging to set up, as well – but the sheer number of advantages it can bring is well worth the effort and the resources.
