AI and ML in financial services in recent years is becoming popular and is rapidly being implemented into various industries of the banking sector, opening new opportunities for increasing efficiency, personalization of services, and improving the customer experience. According to McKinsey, artificial intelligence can generate up to $1 trillion annually in additional value for global banking. Let us consider the AI development services benefits of using AI development services in finance industry.
In the coming years, use of generative AI in financial services will be increasingly implemented into various aspects of banking services and products, opening new opportunities for increasing efficiency and improving the customer experience. The global artificial intelligence in FinTech market is projected to grow from $42.8 billion in 2023 to over $49.4 billion in 2024. With the use of technologies, fintech companies create more personalized offers for clients, based on detailed analysis of their financial behavior and needs. Based on the experience of Artjoker, its experts will share more details on AI for finance.
AI in the Financial Sector: Major Reasons to Use
80% of financial institutions already use AI solutions for finance in some form. Technologies based on artificial intelligence allow participants of the financial market to make real technological breakthroughs, such as:
- Security
- Personalization of services
- Business modeling and many other spheres of activity
Those are the main advantages of AI in finance. Let us examine some examples of AI for financial services:
- Assessment of clients with the help of artificial intelligence. This allows reducing the time of application approval. The cost of scoring decreases, while its quality increases and thereby affects the amount of delay.
- Artificial intelligence in voice assistants. This is a unique solution, because artificial intelligence provides access to intelligent call routing inside a call center. Such assistants are also perfect for communicating with clients when human agents are unavailable.
- Document processing. The use of generative AI in banking and finance sector involves doc processing. This feature auto-processes and enters customer data instead of doing it manually. It speeds up procedures like opening a bank account.
- ATM servicing. Another example which proves the AI impact on financial industry. Artificial intelligence predicts ATM load and reduces the cost of cash collection.
- Use of smart chatbots. These are multichannel communication tools that imitate the activity of a real person. They prove that the role of AI in financial services cannot be underestimated. Today, most customer requests are closed by bots in automatic mode.
That is how AI is transforming financial services. In conditions of tough competition in the banking sector, the importance of AI in finance is vital as smart technologies help increase the competitiveness of your business and attract new clients. The implementation of artificial intelligence will allow banks to scale financial systems.
EXPERT OPINION by O.Prokopiev
Artjoker helps fintech companies implement artificial intelligence capabilities through custom AI to solve finance problems, ML-driven automation pipelines, and enterprise-grade integrations. They deliver cloud-native solutions that reduce costs and improve customer experience. By combining deep engineering expertise with the growing impact of AI in financial services, Artjoker enables financial organizations to adopt intelligent automation faster and more confidently, just like in the examples of generative AI application in finance below.
Artificial Intelligence in Finance: Popular Applications
Today, artificial intelligence is rapidly developing, introducing more and more generative AI in fintech use cases. Thus, artificial intelligence is becoming a priority for the financial sector of the future. Here are some AI applications in finance.
Process Automation
Promising industry leaders turn to robotic process automation (RPA) as it is the future of AI and automation in financial services. RPA reduces operational costs and increases productivity. Intelligent character recognition systems allow automating many daily, labor-intensive tasks that previously required thousands of work hours and increased payroll costs. Software powered by artificial intelligence checks data and generates reports according to specified parameters, reviews documents, and extracts information from forms (applications, agreements, etc.). Using RPA for high-frequency repetitive tasks eliminates room for human error and allows the company to redirect workforce efforts to processes that require human involvement.
For example, Ernst & Young reported reducing costs for such tasks by 50–70%. JPMorgan Chase has already begun successfully using RPA to perform tasks such as data extraction, compliance with KYC rules, and document collection. RPA is one of the five new technologies that JPMorgan Chase uses to improve the cash-management process. AI automation services are something Artjoker offers based on your business needs – check it out today!
Trading
Automated trading systems, which began their rapid development in the early 1970s, assume the use of complex artificial intelligence systems to make extremely fast trading decisions and gain other benefits of AI in financial services. Machine algorithms give many significant advantages. The impact of AI on finance industry is obvious as it monitors both structured (databases, tables, etc.) and unstructured (social media, news, etc.) data in an extremely short time.
EXPERT OPINION by O.Prokopiev
Faster processing means faster decisions, which, in turn, means faster transactions. Stock performance predictions become much more accurate because algorithms can test trading systems based on past data and bring the verification process to an entirely new level before launching it into action.
Customer Service
This is one of the most common AI use cases in fintech. Chatbots and conversational interfaces are a rapidly growing area of venture investment and customer service budgets. Companies such as Kasisto are already creating specialized chat-robots for finance to help clients ask questions through chat to find out more about their spending, for example.
EXPERT OPINION by O.Prokopiev
Banks and similar institutions that use such a service can “win back” clients from their competitors, who “the old-fashioned way” require people to go to the traditional online-banking portal and search for all answers themselves. This type of chat (or in the future — voice) is not yet the norm in banking or finance, but may become a viable option for millions in the next five years.
Final Thoughts
Artificial intelligence in FinTech is not just a trend but a true turning point that fundamentally transforms the financial sphere and society as a whole. Artificial intelligence gives us unique advantages such as unparalleled efficiency, cost reduction, high service quality, innovation, and broad access and inclusion in the financial system. However, artificial intelligence is integrated not without problems and challenges related to technical, legal, security, ethical, and other aspects. Therefore, banks should develop and apply artificial intelligence consciously and competently, considering its potential and risks, as well as adhering to rules and standards that will ensure its reliability, transparency, fairness, and accountability.
Generative AI use cases in financial services open new horizons and opportunities for the financial sector that will contribute to its digital transformation and socio-economic development. With deep expertise in smart engineering, automation, and fintech compliance, Artjoker helps financial companies adopt artificial intelligence safely, efficiently, and at scale. Our team delivers end-to-end generative AI impact on financial services that enhance decision-making, reduce operational costs, and accelerate digital transformation.
