How AI and ML Will Be Transforming Banking and Finance

Artificial Intelligence (AI) and Machine Learning (ML) 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.

This is just the beginning. As we head towards interesting times, let’s discuss the impact of AI on finance, how that affects consumers and businesses, and how AI will change the financial services sector in the future.

AI & ML Financial Solutions in The Future

In 2020, the epidemic and constant lockdowns boosted the demand for digital services of the future powered by 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 the near future.

1. 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 future. 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, and analyze big data.

2. 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 failures from your side. To minimize such failures, businesses start utilizing AI and ML which solve two of 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 the 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.

How AI and ML Will Be Transforming Banking and Finance

3. 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.

4. Robo-advisers

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.

5. Security

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.

6. Fraud and anti-money laundering (AML).

Algorithms analyze the history of risk cases and identify early signs of potential future issues. AI in finance is a powerful ally when it comes to analyzing real-time activities in any given market or environment. AI can drive significant efficiencies in operations like Know Your Customer (KYC) verification procedures and transaction monitoring controls through machine learning and automating formerly manual workflows.

Future Outlook

The finance sector is seeing radical transformation. Deloitte reports that “the economic fundamentals are strong, the regulatory climate is favorable, and transformation technologies are more readily accessible, powerful… than ever before.”

What can we expect in the future? There are high hopes for increased transactional and account security, especially as the adoption of blockchain and cryptocurrency expands. Blockchain will become part of the core business platform, enabling transactional transparency across a wide variety of business functions. In turn, this might drastically reduce or eliminate transaction fees as a result of removing the “middleman” in transactions.

Digital assistants and apps will continue to perfect themselves with improvements in cognitive computing like deep learning. Managing personal finances will then be easier, especially as robots continue to do the heavy lifting of the day-to-day. Consumers and employees alike can focus on what really matters, like longer-term decision-making and strategy.

Acquiring the right talent to drive machine learning and AI in organisations will remain a challenge as innovation is focused in different areas and new technologies are being implemented. In lockstep with this will be the constantly evolving regulatory landscape surrounding adoption of AI in financial services as each side races to match and often contain the other. However, the multiple benefits that come from implementing AI and machine learning are clear, and it will be a key area of focus and growth for businesses within financial services over the next few years.