Artificial intelligence (AI) can be found in just about every area of the financial institutions’ sector.
Today, AI is being used by financial institutions and fintechs to automate processes, reduce operating costs, increase customer satisfaction, improve fraud detection and deliver more personalized digital experiences through predictive analytics.
And, while the vocabulary of AI can be daunting to many, there is plenty of room for small banks and credit unions to make an investment in this growing area in order to gain a competitive advantage.
How should my financial institution think about adopting AI?
In order for AI to benefit your financial institution, you have to think about the needs of your audience (i.e., your customers and your internal stakeholders) first, and only make decisions that directly benefit them.
Think about the use of predictive analytics to detect specific patterns and correlations in the data relevant to customer data in a way that legacy technology never has.
Customer service teams will have more information to help them tailor sales opportunities for specific types of customers, analyze operational data to determine how each customer wants to interact with the financial institution, and pinpointing opportunities to personalize how financial institutions engage with their customers with each touchpoint.
These are the types of opportunities that have a direct impact on yearly revenue.
Cybersecurity teams can use data from previous attacks, picking up patterns and indicators that often seem unrelated in an effort to predict and prevent attacks in the future. AI can support systems that monitor both external and internal attacks or breaches, make suggestions on how to avoid problems and prevent the theft of customer information.
AI can support banks and credit unions by reviewing the creditworthiness of customers by analyzing data from traditional sources. This assists lenders in the development of innovative lending systems for customers who may not otherwise receive a loan due to a low credit score or limited credit history.
How financial institutions can — and already are — adopting AI
Chatbots: The expectations of today’s customers have changed. AI tools, including ChatGPT, are proving to be helpful for both external customers as well as employees. Both parties expect the technology they engage with to feel as turnkey as retail.
If you’ve ever communicated with your financial institution — or a retailer, hotel, or any number of other customer-centric businesses — using a digital chatbot, then you’ve experienced how different AI is being deployed to meet the direct needs of customers in real time.
Many financial institutions are using chatbots as the front door into customer service. Rather than hold a customer on the phone or have them visit their local branch to answer questions that can be done through self-service, chatbots can provide 24/7 client support to existing and potential customers to solve their most fundamental problems.
When developed appropriately, chatbots can significantly reduce call and email volume, giving time back to employees to invest in more strategic tasks.
Predictive analytics: Santander Spain is using artificial intelligence to manage and analyze large volumes of customer data that gives them the ability to create analytical and predictive patterns that benefit their customers. Once these patterns are identified, the financial institution is able to use digital channels to help customers manage their finances.
For example, a financial institution uses predictive push notifications that alert customers to upcoming transactions. If a customer had a health insurance bill coming up on the first of the month and the customer did not have enough money to cover the bill, they would get an automatic notification alerting them to a possible overdraft. This helps the customers to monitor their spending habits.
The push notifications feature has been adopted by almost 5 million digital customers. The feature is also being used by customers in the United Kingdom. Brazil is in the process of adding the feature to its suite of customer benefits as well.
Fair credit and lending practices: Financial institutions have been accused of unfair bias against groups based on race, gender, age and sexual orientation. That’s why relying on algorithms to make credit decisions is more objective than human judgment.
These underserved groups are often overlooked due to a lack of formal credit history, pushing them to sources of credit that do not rely on financial institutions. However financial institutions and alternative lenders are using complex models to analyze hundreds of structured and unstructured data from social media, browsing history, telecommunications usage data and more.
The process is automated, making it quick and easy for both the customer and the lending institution. The process also allows the institution to test and refine their fair lending model over time.
AI can also be used to determine the maximum amount a customer can borrow. These modern systems are able to use optical character recognition (OCR) to pull data from bank statements, tax returns and utility bills. They can also determine a customer’s disposable income and their ability to make loan payments.
Cybersecurity and fraud. As financial institutions are looking to create new models to expedite credit approval and disbursement of funds digitally, there also are new ways for financial institutions to be exposed to fraud and cybersecurity threats. Most fraud falls into one of five categories:
- Identity theft
- Employee fraud
- Partner fraud
- Customer fraud
- Payment fraud
The overall cost of fraud for financial services and lending institutions in the U.S. and Canada is between 6.7% and 9.9% higher than before the global pandemic. Fraud costs are represented the most in online banking for U.S. banks at 33% in 2021, up from 26% in 2020. Mobile transactions come in at a close second at 29% of fraud costs in 2021, up from 20% the year before.
As financial institution customers expect fast and convenient services, they also want to move seamlessly between platforms and devices. Fraud occurs across all parts of the customer journey, from the opening of a new account all the way through to the disbursement of loan funds.
U.S. banks identify loan disbursement as the most prevalent point in the customer journey where fraud occurs at 43%, with account login at a close second. Any interruption in the customer workflow like these can easily ruin a financial institution’s brand reputation.
Automation. Danske Bank is a global financial brand that used AI to modernize its fraud detection capabilities. The bank was following up on up to 1,200 false positive cases per day with 99.5% of its cases not even being fraud related. The high number of false fraud cases proved to be a waste of investment in people, time and monetary resources. Once they were able to implement a fraud detection system using AI, the banks saw a 60% reduction in false positives and an increase in true positives by 50%. As a result, Danske Bank was able to focus its resources on actual fraud cases.
How Wipfli can help
Whether you need AI, a mobile strategy, new core systems, cyber or completed digital transformation and strategy, Wipfli Digital can help them there. Our team doesn’t just offer digital solutions. We offer digital clarity — cutting through to make the future work for you. Let’s overcome your biggest challenges and stay in compliance with the right tech strategy.
Learn more on our digital services for financial institutions web page or check out these additional educational resources: