Here are three banking AI tools to watch in the coming years.
AI has received a lot of attention for its role in generative art, writing, and more. Banking AI, on the other hand, has received less attention for a variety of reasons.
First, financial institutions are inherently conservative and less likely to embrace new technologies, especially given the uncertain regulatory framework. Second, current AI tools have limitations, and many banks are concerned about exposing sensitive customer data to untested AI solutions.
Nonetheless, banking AI is starting to impact the industry and banking experiences. Here are three banking AI tools to watch for in the coming years.
Chatbot
According to a blog post from netomi, chatbots are a fairly common solution in banking today, with examples including Erica from Bank of America, May from HSBC, and Ally Assist from Ally Bank.
These chatbots typically provide customers with a variety of information, including answering questions about products and facilitating transaction transfers.
For Erica at Bank of America, she uses natural language processing for tasks like viewing bills, providing personalized financial insights about charges, and providing tailored advice to customers.
Banking chatbots can also match customers with dedicated bankers who can provide advice. California-based BAC Community Bank uses an app called Smart Alac to answer questions and set up a banker as a customer contact, CNBC reports.
AI chatbots can also escalate issues to bank staff as needed. In the future, it is expected that chatbots will start to provide more advanced services by leveraging AI, including the ChatGPT protocol.
According to a report from Emarketer, Bank of America’s Erica currently doesn’t use generative AI, but instead leverages existing customer data, but some banks are considering integrating it in the future.
Nonetheless, given the sensitive nature of banking data and the high potential for ChatGPT to convey misinformation, these tools will likely face increased oversight as bugs are fixed in the future.
Branch Management
Banking AI will not only transform digital platforms, but will also bring significant changes to retail branches in a variety of ways.
According to a CNBC report, JPMorgan Chase is exploring ways to use AI to increase the productivity of its branch employees.
AI could also help improve security at bank branches by integrating with cameras to detect dangerous behavior or weapons, and quickly alert authorities if someone is trying to rob a bank or steal money from an ATM.
Mark Aldred, Auriga’s head of sales, said on the ATM Marketplace blog that AI can also improve ATMs.
For example, when it comes to lifecycle management of physical devices, AI can identify usage patterns for ATMs and predict when those devices will need maintenance.
“For example, when it comes to managing the life cycle of a physical device, AI can identify usage patterns for an ATM and predict when that device will need maintenance,” he said. “Banks can monitor the cash supply in an ATM to predict withdrawal and deposit trends over a given period. These insights can help ensure that the ATM has the required amount of cash and improve the cash replenishment process.”
Banks can also use AI to detect fraud both in branches and on digital platforms.
Data processing
While regulatory issues are a top priority for generative AI, in the meantime, banks can reap real benefits by using AI to process big data.
David Becker, CEO of First Internet Bank, the world’s first online-only bank founded in 1999, believes that data processing should be the first step for banks considering adopting AI.
“For years, bankers have had to pore over endless spreadsheets and toggle equations to track the data most essential to their needs. Sooner than you think, AI tools will crunch those numbers in seconds, allowing bankers to leverage their data more efficiently for complex processes like loan underwriting, personal finance recommendations, or regulatory reporting,” he said.
As an example, a bank can use AI to automate the loan process, thus reducing customer approval times. This will have the dual effect of improving operational efficiency and the banking customer experience.
Concluding thoughts
The future of AI remains uncertain in many ways, as customers grapple with whether to fully embrace AI, fight against it, or take a middle ground. Of course, there are also concerns about job losses in both the financial sector and other industries.
In other words, banking AI does not replace human interaction. Instead, it enables bankers to provide better insights to customers and improve the overall experience. The goal is not to replace human contact, but to have a greater impact.