AI-Powered Banking: Enhancing Human Expertise for Improved Customer Experience

The fear is real. 

Artificial Intelligence(AI) has shown it can pass competitive exams and even clear job interviews. So does it mean it’s coming for your job at the bank?

As the world grapples with the pace of AI powered banking tools adoption, it opens new avenues to improve customer experience. It’s agreeable that speaking to a human helps address (or vent) one’s complex grievances. However, building the skill set required to appease an angry customer takes time. And it’s years before an Artificial Intelligence can replicate.

AI performs many redundant and time-consuming tasks at scale to assist humans and help organizations prevent losses. Let’s discuss how the banking industry benefits from using AI to enhance its operations and customer experience. For instance, Wells Fargo uses Machine Learning (ML) to contain losses by detecting untrusted financial transactions.

A report by Autonomous Research about the financial industry shared this statistic: By 2030, AI may yield $1 trillion in cost savings and revenue. So consider implementing AI to complement your existing banking services and improve customer relations. Let’s see the banking areas where technologies like AI, ML, and Deep Learning will create a positive impact. 

AI-Powered Banking Functions and Services

AI allows banks to automate many processes for improved efficiency and reduced costs. In addition, by analysing existing data and processes, AI/ML can detect anomalies and vulnerabilities. Here are some important uses of AI in the banking industry.

Customer Service

One poor experience is enough to turn a customer away from a bank. Even routine tasks like knowing account balances, credit scores, and investment status are most important to customers. Using AI, you could provide quicker and smoother replies without spending your staff’s time.

Insights for Improved Business Decisions

Let’s face it, humans are bound to err. The worst is discovering the mistake only after the damage is done. AI algorithms identify patterns and trends that human analysts may miss. For example, some vital banking decisions are managing risk, where and when to invest, and how to improve processes. With AI-powered insights, your bank can stay ahead of the curve.

Personalization

Every customer craves that personal attention. It helps to address your customer based on their account and transaction history. Banks are turning to AI for personalized services based on their needs and preferences. Imagine offering your highest-spending customers credit cards with rewards to encourage more spending and saving. A win-win for your customer and you!

Risk Management

Banks evaluate numerous factors and take calculated risks. It’s a long, complex process for humans to screen businesses or persons before lending approvals or disapprovals—a process so tedious suits AI’s capability. AI analyzes large data sets against several parameters to identify potential risks. Leveraging AI for risk management, banks improve risk profiling and process several profiles faster to take on more business.

Chatbots

These are alternatives to bank assistance you’d find at the bank but more. Chatbots answer customers’ fixed questions instantly. It helps portray your bank’s faster customer service and allows you to serve many more customers than traditional banking methods.

Challenges in Implementing AI-Powered Banking Functions

While AI simplifies several time-consuming and extensive data analyses, it also has limitations. 

Data security

Like any data-driven application, AI, too, is vulnerable to data theft, loss, or manipulation. Organizations must take steps to safeguard access to data inputs for the training to prevent security or data breaches.

Understanding AI Decisions

AI algorithms are complex. In the banking industry, decisions cannot be biased. Understanding how AI arrives at conclusions gets challenging. Banking institutions must ensure data input for AI training doesn’t contain biases toward customer groups.

Implementation Cost

AI comes with its costs. The heavy investment costs may put off banks with modest budgets. In addition, banks must even consider the cost of training and bank staff acclimatizing the AI.

Using AI to Better Your Customer Experience

You can improve customer service by powering your complex processes with AI. For example, with predictive analysis, banks can anticipate market trends and suggest strategies for max impact. Forecasting leverages machine learning algorithms to help banks identify potential risks, market opportunities, and customers’ changing behaviour. 

[Learn more: What are the Top 6 Machine Learning Algorithms You Should Know for 2023?]

AI combines with deep learning to boost your bank’s volume handling capacity. Contrary to the belief, AI-powered banking is not coming for bankers’ jobs but allows them to free up time from manual and redundant tasks. By adopting AI technology, banks can enhance their ability to deliver improved customer services, streamline operations, reduce overall costs, and achieve greater operational efficiency.