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AI-Based Solutions in the Banking Industry

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The first aim of any bank is to generate profit. However, the goals of providing excellent services to customers, risk diversification, and reduction of costs are just as important, and that’s where artificial intelligence comes in useful. It considerably accelerates all the processes by analyzing arrays of information and automating all routine tasks.

AI to Serve the Banks

If artificial intelligence technologies are successfully integrated into banking, this could save an astounding trillion dollars by 2030, which sounds really impressive. Three-quarters of banks with assets worth more than 100 billion dollars are using AI solutions in their activities, and they are going to do so on a wider scale.

Here are some insights into the future of AI for the banking industry:

  • 45% of banks and insurers save considerable costs if they use AI for report generation.
  • More than half of financial product and service companies heavily invest in AI solutions.
  • By 2034, AI is expected to take over from 15% to 25% of all banking operations.
  • When it comes to the use of AI in the banking sphere, North America is an undeniable leader that occupies a market share of 34%.
  • The implementation of AI technologies has created new jobs for 83% of banks.

To crown it all, the market of AI banking solutions is expected to grow at a pace of about 25% a year to reach a jaw-dropping 67.57 billion US dollars by 2025!

Use of AI in the Banking Sphere 

Let’s look at several examples of how AI technologies contribute to the banking sector transformation:

  • Customized services and recommendations. Customer data and preferences are analyzed by AI to result in personalized financial advice, which brings customer satisfaction and loyalty to a new level.
  • Trading. AI helps make important trading decisions by monitoring structured and unstructured data and predicting stock performance.
  • Fraud prevention. As the e-commerce sector is developing at a tremendous speed, the number of fraudsters who are after your credit card data has increased. AI can develop algorithms that help analyze the buyer’s spending patterns, location, and online transaction behavior and take relevant security measures to prevent credit card fraud if it detects something suspicious.
  • Loan decisions. Bank employees are required to assess the borrower’s creditworthiness, but AI will do so faster and more accurately. Credit decisions are taken in a smarter way as AI credit scoring systems provide reliable and unbiased customer data.
  • Customer service. We are all used to chatbots and dialog interfaces that improve the quality and efficiency of customer service and make customer interactions much easier.
  • Process automation. There are a lot of routine tasks that AI can automate, including form information extraction, data analysis, report generation, and document processing. Bank employees no longer need to deal with payments, document verification, and loan application processing as the bank will do it for them instead.

AI is a beneficial banking instrument that provides investment advice, optimizes asset portfolios, and creates trading algorithms, thus mitigating risks and increasing return on investments. Money laundering, one of the biggest banking problems, now has a powerful adversary represented by state-of-the-industry AI-based solutions. Dubious activities are quickly detected by AI algorithms, which helps to considerably decrease the costs incurred by the banks on investigation matters.

AI in Banking: Benefits

AI is used in the banking sector much more actively than in other industries as it gives numerous advantages.

  1. Increasing Performance Through Process Automation

As the banking sector relies more and more on automated document authenticity verification, data analysis, and processing of applications with the help of AI-based technologies, there is less need for manual labor. AI solutions save a lot of time as they complete all these tasks much more quickly and accurately. This results in decreasing labor costs and making the banking processes more efficient.

Customer support services no longer suffer from major overload as they have chat-bots to take care of some operations. In addition, there are voice assistants that guide clients through various online menus and solve quite complex issues. With AI, the productivity of the banking industry will certainly be on the rise.

  1. AI for More Security

An astounding 67 billion US dollars per year is the cost of fraud for the banking industry. As the banks process an enormous number of transactions on a daily basis, it is very important to timely detect possible fraudulent actions – especially if we consider all banking channels, such as social networks, online banking, and mobile apps.

Security departments in banks get real-time alerts of dubious transactions, helping them fight fraud more efficiently. Here are the main components of AI-based banking security:

  • Monitoring of social media
  • Accessing management systems
  • Analysis of cyber threats
  • Biometric authentication
  • Automated monitoring systems

As a result, the losses due to fraud are expected to be considerably reduced.

  1. More Profitable Investments and Asset Management

Banks need to analyze big data, and that’s where AI technologies come in useful. News updates, market trends, economic indicators, financial reports – all of that can now be handled without human efforts.

AI-based solutions help banks predict what the situation in the market will be like by tracking the trends and analyzing historical data. As a result, banking institutions can reduce possible risks, make informed decisions about the time of asset sale and purchase, and adapt to actively changing market dynamics.

AI is a great assistant when it comes to the following asset management operations:

  • Automated trading systems. These take into account pre-defined strategies and criteria to make decisions regarding asset purchase and sale.
  • Investment recommendations. AI analyzes the customer’s finances, goals, and preferences, and suggests optimal investment options.
  • Portfolio management. AI manages portfolios with the help of automated diversification strategies and trading algorithms.
  • Risk management. Mitigation of risks requires developing appropriate strategies, predicting potential losses, monitoring market risks, and evaluating creditworthiness. AI can successfully manage all these tasks.

Interested in the use of AI-based technologies in the banking sector? Follow the above link to read more as this is a trend that is here to stay for many years ahead.