The use of artificial intelligence (AI) continues to grow across every industry that relies heavily on data, and the banking sector is no exception. In fact, a 2018 study conducted by PricewaterhouseCooper showed that 52% of financial service executives are making big investments in artificial intelligence, and 72% think that AI will give their companies an advantage in the future.
Artificial intelligence has been the central topic of quite a few discussions at the World Economic Forum’s meetings at Davos over the past few years. That prestigious group has partnered with Deloitte Consulting to conduct a study that would offer useful insights into this emerging technology for business leaders and public policymakers.
If you are in the banking industry, it would be wise to educate yourself on the subject of artificial intelligence and machine learning. Reading just a few of the best books on artificial intelligence in 2020 could give you the edge over the competition. The more you know about the future of this technology, the better you’ll be able to serve your investors and customers in banking.
Keeping this in mind, let’s look into a few of the areas where banks are using AI.
Streamlining Customer Service
The time that banking customer service representatives have to handle customer issues is often limited. In fact, the high demand for customer service has long been a sticky issue for all retail banks. Fortunately, chatbots offer an affordable solution for answering basic customer questions. Thanks to this type of AI, bank customers can receive quick answers to their questions, helping them to make the right decision.
Bank of America has a chatbot charmingly named “Erica.” Erica offers BOA customers financial advice based on their banking habits. Erica uses artificial intelligence, predictive analytics and cognitive messaging to help customers make the best financial decisions.
For example, Erica can calculate how much the customer should save to reach a specific financial goal, such as the best way to quickly pay down a credit card. Bank of America customers can reach Erica via a mobile app or text messaging to ask questions, get answers as well as financial advice.
Security and fraud detection
This is always a top priority for any bank, for obvious reasons. With more and more banking transactions being done online and from mobile devices there are more security threats and opportunities for fraud. Artificial intelligence can use algorithms to detect if a particular online activity looks suspicious and act accordingly.
Anomaly detection is one way that AI can detect possible fraud. This type of application uses machine learning that is continually trained with the stream of incoming consumer data. This trains the application to have baseline normalcy for all different types of banking transactions. When something out of the norm is detected, the transaction is flagged for further investigation.
Mobile banking
Banking apps rely heavily on AI. Mobile banking provides banking services anywhere, 24/7, and AI can quickly help banking customers check their balance, answer banking questions, and remind customers of upcoming bills. Customer service, security, and fraud detection applications make mobile banking possible. The fact is, mobile banking powered with AI is fundamentally reshaping how people use banks.
Improving User Interface
The user interface involves both website and mobile designs. Simple and intuitive navigation for both bank websites and mobile apps is important for enhancing the customer’s experience. Artificial intelligence can analyze customer action, and use that data to redesign the navigation for easier use.
Also, artificial intelligence and machine learning can be used to simplify the process of loan application approvals or uploading documents by accurately calculating the information on the documents customers upload using the built-in cameras on their mobile devices.
Algorithmic trading
A person is very limited when it comes to the amount of data that can be analyzed compared to AI and machine learning algorithms. AI can simultaneously analyze thousands of bits of data, allowing it to calculate both potential risk and expected gain, thus returning an accurate evaluation. This can help an investor make better trading decisions.
In fact, within the tight parameters set by investors, algorithms can control many key trading decisions. Algorithms now control most “micro-level” decisions for trading equities, defining where to trade, what quantity, and at what price. However, algorithms are not fool-proof, and humans still need to use their common sense and intuition before finalizing any big investments.
The future of banking relies heavily on AI and machine learning, shaping how everyday people interact and conduct business with banks. Learning more about how AI is shaping the future of banking gives you an edge in the future.
