Banking is estimated to benefit the most from integrating artificial intelligence (AI) systems in the next few years and will save the industry over 1 trillion dollars by the year 2030. The banking industry is now using AI-based solutions for most traditional banking issues. Below is how AI affects banking.
1. Personalized Customer Service
With the increase in automation, some fear reduced customer loyalty because of less personal contact but the truth is that increased usage of AI will increase the client satisfaction, maintain customer loyalty and improve efficiency in several ways. An AI-enabled tool gives financial guidance via text and voice messages. This service is available 24/7; hence, clients can access services all the times. Customer service personnel don’t need to be hired and therefore significant cost reductions.
2. Fraud Detection, Compliance and Anti-Money Laundering
Money laundering and fraud have for a long time affected the banking industry. Artificial intelligence can help banks in becoming more efficient in spotting money laundering and fraud. AI will help in monitoring potential customer threats and prevent any potential criminal activities. Cybercrime has been estimated to cost the global economy 600 billion dollars and this is quite a loss. AI detects fraud in real time.
In the banking industry, personalization is more than just product customization and marketing. It includes security. Banks are now using biometric data such as fingerprints to augment or replace passwords plus other types of client verification. Facial recognition technology is one useful invention that has improved security levels. Blockchain technology benefits heavily from AI and machine learning.
4. Process Optimization
Among the most promising usages of AI in banking is from automating very high volume, low-value processes. Online only banking utilizes AI to serve as many people as possible within a matter of seconds. Many people can make transactions at the same time, which is very convenience. It performs the work of several full-time employees within a short period.
5. Managing Portfolios with Algorithms
Creating a portfolio is an extensive endeavor since every user has various goals with risks associated with those goals. Machine learning and AI streamlines the whole process of creating a portfolio through reviewing the goals and risk tolerance of a client so as to come up with an individualized portfolio. An algorithm could help in analyzing information such as the customer’s income, age, and current assets.
6. Lend Credit to those who are Under-served
Machine learning’s benefits extend to the people who have struggled for a long time to get credit. Machine learning has ways of carrying out risk assessments which could be very accurate in predicting consumer scores. This could enable the under-served consumers to get an opportunity to present themselves with their credit profiles. In turn, consumer lenders would achieve a competitive advantage over the other institutions by using traditional credit scores.
7. Regulatory Compliance
With the rapid evolution of regulations and laws in the financial industry, AI is capable of learning, remembering and complying with all the applicable laws. It helps eliminate human errors and identify complex patterns and help financial institutions meet their regulatory obligations.