The term "artificial intelligence" (AI) is often associated with futuristic technologies that may not be available to everyone. However, AI is a modern tool that is commonly used in nearly every industry. Even the banking sector uses it to increase efficiency and create better customer experiences across the board. Working in tandem with professionals in the field, AI and automation technologies create a more effective and secure banking system.
According to data collected by McKinsey and Company, "the potential annual value of AI and analytics for global banking could reach as high as $1 trillion." AI and automation tools are active in your banking system, so let's explore some of the most effective and common applications.
Robotic Process Automation
Robotic Process Automation (RPA) is a method of automating banking processes that would otherwise be done manually. Many banks have implemented RPA because it helps them remain competitive in the market and increases customer satisfaction since tasks can be completed quickly. You may have used this digital banking solution if you've ever transferred money to another account electronically or deposited a check using your bank's mobile app. This frees up the financial institution's staff to focus on more complex banking activities.
AI Biometric Authentication
Many banking services have gone digital in an effort to boost convenience and efficiency. AI goes hand and hand with these kinds of banking services, mostly to increase security. From facial recognition or fingerprint recognition, it can increase authentication and protect consumer financial information. The same technology is also being applied behind physical desks to protect sensitive internal bank data. The 2020 Cambridge Centre for Alternative Finance and the World Economic Forum reports that 56% of financial services companies have used AI in risk management.
Financial Forecasting
For banks that offer personal and business loans, machine learning can help them offer an appropriate interest rate according to expected market trends. This is a great example of how AI and financial professionals can work together to create more accurate financial reports and services. In this case, the bank is able to run a successful business and the borrower will receive a fairer loan. Data analyzing algorithms and AI machine learning benefit customers and those who work in the industry.
Customer Service
From the front office to the back office, AI is instrumental in increasing customer satisfaction. Here are some examples of how this technology can help increase the best consumer experience possible:
- Chat-bots for after-hour questions.
- Detect fraud patterns to increase security.
- Automation to increase efficiency.
- Boost flexibility due to machine learning.
A combination of knowledgeable professionals and machine learning technology makes up the modern banking industry. To learn more about the digital services offered by The Federal Savings Bank, reach out today.