8 Finance AI and Machine Learning Use Cases for 2022

6 Artificial Intelligence use cases in financial services

Finance AI technologies have changed the lives of millions of people worldwide by providing 24/7 access to bank accounts, professional support, and fast and easy operations with financial apps resulting from the implementation of artificial intelligence in finance. This article will outline the latest use cases of AI in finance and define the technical aspects of applying machine learning (ML) to the banking industry. Let's start!

Implementing AI Tech Solutions

Artificial intelligence (AI) technologies have brought huge changes to society. They mainly affect the following 5 industries:

  • Retail
  • Finance
  • Transportation
  • Healthcare
  • Advertising

The banking, retail, and healthcare sectors have made the biggest investments in AI technology development.

The aim of artificial intelligence technologies is to develop smart software solutions, technologies and machines that can perform actions and make decisions like humans. Artificial intelligence can learn, analyze, plan and carry out human functions. Furthermore, AI can improve itself without human help or developer efforts. It builds the model of behavior based on input data and its own experience.

The development of AI brings incredible changes. One of the most important ways is that AI analyzes information, solves tasks and carries out operations more quickly than any human could.

Read also: What are machine learning use cases in the automotive industry?

Technological aspects of AI

Artificial intelligence includes four main technological aspects. A few of them are sometimes considered to be synonyms for artificial intelligence.

  • Machine learning. This modern technology is responsible for the analytical model building. It uses algorithms and allows the computer to study and find mistakes without being pre-programmed for that.
  • Deep learning. This type of machine learning is able to recognize objects in images or videos. One of the famous examples of deep learning technologies is DeepFace developed by Facebook. As you can see by yourself, this technology recognizes you in the photos you are not tagged in.
  • Language processing. AI-based software has the ability to understand natural language. Siri, the application that was mentioned above, can hold a conversation with you, thanks to high-quality language processing features.
  • Internet of things. IoT technologies claim that the components of our lives can be connected via information technologies. Have you ever dreamed of a cup of fresh coffee waiting for you when you have just got out of bed? Well, with IoT technologies, your alarm clock may be connected to the coffee machine, so you can get a cup of your favorite drink after the alarm clock rings.

The application of AI in financial services needs a more comprehensive study to be made. The point is that this innovative technology, together with its components, can be of great use in one of the most important modern industries.

AI in Financial Sector

The use of artificial intelligence for banking can minimize the number of potential risks, help optimize processes, increase capabilities and multiply the profit. These results can be reached thanks to AI algorithms.

Based on an Insider report, almost 80% of banks are aware of the benefits of using finance AI. The pandemic increased the rapid growth of advanced technologies in the financial sector. AI in finance became a game-changer in how people manage their accounts. Also, it helps banks to save money. By 2023 general savings will reach $447 billion. Most banks and financial institutions try to invest in advanced technological solutions to help their bottom line while providing better service to customers. Artificial intelligence in banking helps manage data-related processes. The following types of data can be analyzed by AI with high accuracy:

  • Numbers
  • Texts
  • Images

Accurate analysis means that AI can process these data types better and faster than even the most skilled financier.

Benefits of Using AI for Financial Services

How a company can benefit from using finance AI:

  1. Improve data-driven decisions.
  2. Increase income by using accurate predictions.
  3. Improve customer relationships by learning from user experiences.
  4. Automate tasks that can be performed faster by AI.

Implementing AI for finance was revolutionary for most companies. Forbes researched that 70% of financial institutions already use artificial intelligence to improve their services, predict cash flow, fine-tune credit scores and detect fraud.

Using AI for financial services is essential for connecting with Millenial and GenZ customers in particular: they prefer mobile banking over traditional systems.

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Use Cases of AI in Financial Services

Artificial intelligence for financial services automates processes and replaces human decision making. What does it mean for practitioners? Let's do a review.

Fraud Prevention

Banks and financial organizations deal with huge volumes of personal data as well as people's money. Fraud is the most dangerous thing in this industry: one mistake can lead to unbelievable losses, troubles and liabilities. When we speak about fraud, we mean credit card fraud, money laundering, and other forms of financial breaches.

The key aim of AI in financial services is fraud detection. AI detects suspicious activities, provides an additional level of security and helps prevent fraud. In short, AI improves bank security.

Trading Algorithms

One of the common problems in trading is getting market analysis too late to take advantage of opportunities. AI finance tools can outperform human trades and bring faster and better decisions on trading. Also, the comprehensive analysis of different market aspects and factors allows banks to achieve new heights in trading algorithms. Nowadays, a lot of well-known hedge funds use AI for these purposes. The technology is quite popular for data science as it helps a company build its trading system.

Risk Management

Artificial intelligence in financial services makes a huge difference in investment management and risk analysis. AI can accurately estimate the client's creditworthiness and answer the crucial question: is this person reliable?

The AI-based system analyzes the risks by considering transaction and credit history, income growth, market conditions, etc. Predictive analytics provides considerable details on micro activities and behavior to determine if investments should occur. Note that all of these tasks cannot be performed and processed by humans.

MORE ON TOPIC: DIACAP or RMF | Benefits of Risk Management Framework for Your Business

Corporate Finance

Finance AI in a corporate world can be considerable support in loan risk assessment and prediction. It means that many companies use these instruments for underwriting and reducing financial risk, providing advanced fraud detection and making an accurate financial analysis. Moreover, corporate organizations use AI finance solutions to stop money laundering; the Insider report says it was pretty successful for many big companies in the corporate sector.


Customers want to have a connection with their bank 24/7 (not a surpise). And finance AI technologies can assist with this by running chatbots.

Banking services are enhanced by simulating a real conversation. Сhatbots in financial services using natural language processing technology answer customer queries in real-time and precisely. That means a lot of extra attention, new clients, and better conditions for the current ones.


The considerable interest in passive investment makes fintech companies invest in AI solutions. Robo-advisory is based on providing recommendations based on investors' individual goals and risk preferences. Finance AI automates the investment process so that the only thing investors need to do is deposit money into an account. The most significant benefit of using this tool is offering the ability for people not familiar with finance to make investments. You don't need to do financial analysis to succeed in passive investment! And it is also cheaper for financial institutions to have robo-advisory than human asset managers.

Regulations and Rules

A financial institution must comply with different laws and rules that are sometimes even hard to keep track of. Reports take too much time, and one tiny detail missed by a bank specialist may lead to minor complications or even serious problems. AI takes into account all the regulations, detects deviations, analyzes data and follows the rules accurately. Thanks to the complete automation of the processes, it is possible to avoid issues with the help of AI.

Process Automation

Artificial intelligence finance tools can offer massive support in process automation. There are a lot of tasks that are usually done manually by bank employees. For example, preparing documents or accessing information for clients.

Everything can be done in a few minutes or hours with AI automation. Another example of process automation with AI is the ability to verify personal ID. You often need to submit your ID and take a photo of yourself to be confirmed as a user. AI can check the match between an ID and a picture while examining that the ID was not used for fraud.

Challenges of Finance AI Implementations

Using artificial intelligence for financial services can boost revenue, reduce errors, automate the banking system and provide customer support 24/7. But we need to point out the challenges that fintech will face in 2022.

  1. The data quality. It should be clean and well-maintained data for machine learning input, which is a challenge to get.
  2. Removing bias in the data. All solutions made by AI can have a significant impact on a person’s life. For example, if AI makes a mistake and does not approve a loan request, the effect on the customer's future can be significant. That is why we need to pay extra attention to removing any sources of bias in the data.
  3. Black Box. We apply the latest solutions and perform calculations behind the scenes. But in finance, it can be complicated: in many cases, the bank will need to explain a conclusion made by AI, like a declined loan or a low credit score. There should be a backup review for every solution made by AI.

Final Thoughts

There are tons of opportunities to use artificial intelligence technologies in financial services. All of them aim at the process of automation and improvement and elimination of the necessity to involve human action and effort.

The above mentioned applications prove that AI has strong potential to stabilize the whole financial industry and bring the world economy to a higher level. AI-based tools for financial institutions can have a huge positive impact. However, the field is as profitable as it is complex. The decision to implement AI-based financial software calls for a technically rich process that works out many technical aspects. But don't be frightened by the potential challenges. It's all about the staff you use to choose and implement AI and ML technologies! You can always cooperate with our skilled, competent development team – let's make the best of your ideas come to life together!

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