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How AI and ML Will Be Transforming Banking and Finance

Artificial intelligence and machine learning remain the hottest topic in the financial world for the past few years. By adopting smart solutions, companies get a huge competitive advantage to cope with the changing industry landscape. AI provides a deeper understanding of customer needs and empowers business processes. Companies can optimize and quickly refine their market offering for the fast-paced world. 

There is a high demand for AI and ML in almost all industries, and it’s not going to reduce. Currently, AI technology holds a global market value of over $30 billion US. It’s forecasted that the global AI market will grow rapidly in the coming years, reaching up to $126 billion US by 2025.  

In Fintech alone, the use of AI in 2019 reached an estimated value of $6.67 billion US and is expected to grow over $22.6 billion US in just five years. The fintech market also expects a CAGR of 23.37% until 2025, and there are lots of factors even fastening the growth. 


What AI & ML Solutions to Target in 2021-2025?

In 2020, the epidemic and constant lockdowns boosted the demand for digital services of the future powered with AI. And now we see a growing demand for cutting-edge technologies in the financial industry. It means that in the upcoming years customers will expect fast and functional artificial intelligence and machine learning financial services and personalized approaches among banks and SME lenders. So it’s the best time to explore the fintech trends to have a good thing going in this decade. 


Process control and optimization (PCO)

Process control and optimization are already one of the most applied approaches in the fintech field that will be the leading competitive advantage of companies in the decade. PCO helps companies in reducing or completely dispensing with manual work. It makes business processes more efficient, fast, and increases overall productivity. Process optimization is used by call-center and sales departments, refines employee training by moving it online, and accelerates accounting activities. 

In the coming years, the technology will become more widely available and drive more systems towards automation. AI finance software will be able to reply more effectively to customers, generate detailed reports, analyze big data. 


Customer service

The higher level of customer experience you make, the more successful your business will be. There’s no secret that customers might turn to competitors after several fails from your side. To minimize such failures, businesses start utilizing AI and ML which solve two the most significant aspects - response time and personalized customer approach. 

Customers won’t wait for a response for hours, even minutes. If they get the needed information faster, you have more chances to make a deal. Chatbots powered with AI and ML will respond within seconds. With the growing competition on the market, quick customer engagement will be a must that never before. 

The technology can also gain insights into customer needs and disappointments. The great amount of analyzed information allows creating athe more personalized customer experience. It includes not only customer response in a chat, AI can collect data from social networks, review websites, send personal emails to specific audiences for feedback, and more. 


Credit scoring and churn prediction 

The majority of currently-used credit scoring systems are outdated. Their decisions are based on a supposed customer base, including demographics, age, marital status, possible preferences. So the system doesn’t collect real data, it targets possible customers. While modern credit scoring and churn prediction software solve the issue of analyzing real clients.

AI / ML churn prediction will consider every client making a loan application. In the banking future, you’ll have a great marketing campaign based on real customer preferences and will understand how to target them in case there is a risk of churn. Churn prediction with AI allows reducing the number of lost customers by 45% and empower the whole marketing and sales campaign. 

Credit scoring powered with AI and ML is the future of credit risk management that you can already try. The software will analyze historical data based on previous lending operations, debts, marital status, financial behavior of applicants, and more to help you decide whether to grant loans or not. AI credit scoring can reduce non-performing loans up to 53% while boosting your revenue by 37%. With AI and ML, companies will reduce risks and speed up decision-making processes to days instead of weeks.  



Robo-advisors will be a great side-benefit for customer service. They provide automated portfolio management and personalized product recommendations with little to no human supervision. AI / ML advisers collect information from clients about their financial situation and goals to offer advice and automatically adjust the marketing approach. Although there are lots of debates considering the ethics and accuracy of the technology, its demand will keep growing in the coming years. With the information on marital status, income, and investments, the latest AI solutions can recommend a client, for instance, to start saving money to pay for a child's college in ten years. 



As cyberattacks get more sophisticated and target diverse, cybersecurity should be one step ahead to predict vulnerabilities and eliminate them. And AI can help with the problems that people are unable to solve manually. While statistically, 95% of security issues and data breaches happen due to human errors. 

The number of cyberattacks grows from year to year. According to Experian, 55% of companies reported fraud in the last year and is going to reach up to 60% by 2025. In the lending domain, fraud is common. AI in finance allows you to find breaches in the security system and explore solutions. It will be able to analyze documentation for account registration, detect issues within accounts, and more. 

How to Adapt ML & AI? 

As technologies develop, artificial intelligence and machine learning in banking will be more technically-smart and adapted to business processes. Choosing the new technologies for the business, it’s better to start with a single element, sort it out, and only then pick up another one. Analyze your business processes, find problem areas, and begin with them. Remember that AI and ML are complicated technologies that only start evolving. In the years to come, they will be essential for any company driving to progress and market leadership. 



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Dmitry Dolgorukov

Dmitry Dolgorukov



Member since

19 Mar 2018


Vilnius, Lithuania

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