Artificial Intelligence (AI) may be applied in banking to reduce and optimize transaction costs, attract customers and sellers, increase sales, and increase advertising plus marketing.
AI plays an important role in ensuring the automated operation of various systems. This article will provide 3 examples of artificial intelligence in banking: from chatbots to fully digital banks, recommendation systems, and audit systems.
Why Implement Artificial Intelligence in Banking Systems
The introduction of artificial intelligence (more specifically, Machine Learning methods) into the banking sector has several reasons. These include:
- Banking speed and accuracy.
- Reduced operating costs to improve return on equity.
- Banks work 24/7.
Since users are in the system, leave reviews, and use certain services, it helps collect data and increase the banking system.
1. Chatbots and Digital Bank
Banks provide financial services, so they require specialized services. The value of maintaining an agency involves the purchase or rental of a building, energy costs, and, just as important, staff salaries.
Whenever it decides to decrease costs, it usually believes in personal resources. A person is not always able to complete all duties, including working with money, informing clients about the policy and proposals of the bank. The rational brain becomes involved, particularly when there is a charge at the bank. This leads to pauses in progress and economic needs for the bank.
Thanks to advances in artificial intelligence, several banks should add chatbots to their ranks. Chatbots’ communication style is becoming more and more similar to how a real person writes. The advantage of using chatbots is that b can work for a long time without the additional time investment, 24/7 throughout the year. Another positive feature is that chatbots may handle many customers at an identical point with the same precision.
2. Audit System
Artificial intelligence can assist reduce human mistakes. The machines run without fatigue, and they are not worried about the weather. They do not give in to emotions and are always motivated. Bots can make complex also important duties without any mistakes, subject to external control. If a bank may reduce damages caused by human factors, it can improve its bottom line.
3. Recommender Systems
Artificial intelligence helps banks form personalized offers. Banks work with a broad field of clients, from people to businesses. Conventional banks are spending their private clients as the financing opportunities of individuals diminish, and more people have started investing during the pandemic.
Their main problem is that a bank may own hundreds of thousands of clients, and preparing individual proposals is difficult and costly. But gratitude to the most advanced technology, banks may immediately use the potential of artificial intelligence to explain the financial behavior of each customer.
Ai development company assists in their search for personalized data-driven offers. CrayOnData is one example that helps develop platforms for personalized presents. On top of that, there is Optimizely plus Maya AI, which also offers a significant contribution to this cause.