The banking industry is undergoing profound change as new technologies such as blockchain, IoT and open APIs are transforming the way bankers interact with their customers and conduct business both inside and outside the organization. Of all the technologies having an impact on banking, however, artificial intelligence holds the greatest promise of opportunity in terms of operational efficiencies and customer satisfaction industrywide.

A multitude of research shows just how impactful AI could be for financial organizations. Accenture estimates AI will add more than $1.2 trillion in value to the financial industry by 2035, while Autonomous Next projects it will save organizations more than $1 trillion by 2030.¹ Already, the impacts of AI are being felt—according to Autonomous Next, the jobs of 2.5 million financial services employees in the United States are directly impacted by AI today.²

Currently, AI is being used throughout the industry for customer service, such as chatbots that answer basic customer questions or can escalate a query to a human customer service agent if they are unable to help. These chatbots are helping improve customer satisfaction and productivity: Swedbank’s Nina chatbot was able to achieve a 78 percent first-contact resolution within its first three months, freeing human employees to work on more value-added tasks.³

AI is also being used to help banks tailor offers to customers based on historical data like average daily balance, current account types, or even interactions with other professionals. For example, using AI, a bank could determine that a customer is looking to purchase a home through social media posts. The bank then could send the customer targeted marketing information regarding home mortgages, like blog posts or instructions for applying online.

There are a number of ways AI is impacting the back office, as well. For example, JPMorgan Chase is using AI to analyze and extract important information from legal documents, bringing what used to amount to 360,000 man-hours spent analyzing 12,000 commercial credit agreements down to mere seconds.⁴ Meanwhile, Bank of NY Mellon’s use of bot technology to handle repetitive tasks, such as data requests from external auditors, has improved processing time by 88 percent and freed employees to focus on more essential duties.⁵

Autonomous Next predicts that applying AI to compliance, authentication and other forms of data processing will save banks as much as $217 billion by 2030, including a potential $31 billion in savings in underwriting and collections systems.

Indeed, there are a multitude of uses for AI in the banking industry, from detecting fraud to improving customer service. The technology is still in its nascent stage, however, with future possibilities for AI in financial services not yet imagined. Regardless, banks would do well to update their networks today to ready themselves for the future. AI—and all technologies related to digital transformation—need an infrastructure capable of handling the constant flow of data necessary to take full advantage of their benefits. AI and other technologies transforming the banking experience need a network powerful enough to provide the speed, agility and flexibility necessary to provide services that increase operational efficiencies and improve customer satisfaction.

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^[1] Lisa Joyce, “Artificial Intelligence and The Banking Industry’s $1 Trillion Opportunity,” The Financial Brand, May 29, 2018
https://thefinancialbrand.com/72653/artificial-intelligence-trends-banking-industry/

^[2] Ibid.

^[3] John Manning, “How AI is Disrupting the Banking Industry,” International Banker, July 4, 2018
https://internationalbanker.com/banking/how-ai-is-disrupting-the-banking-industry/

^[4] Kumba Sennaar, “AI in Banking – An Analysis of America’s 7 Top Banks,” TechEmergence, Sept. 16, 2018
https://www.techemergence.com/ai-in-banking-analysis/

^[5] Ibid.