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How are Robotics and AI Impacting the Banking Industry?

Written: March 2023


Robotic Process Automation (RPA) is a revolutionary technology which allows businesses to streamline operations and automate repetitive manual processes. RPA can execute transactions more quickly, reduce costs, reduce errors, and improve customer satisfaction. RPA uses business logic and structured input, which would otherwise be manual. RPA can free administrative personnel from menial and boring tasks, and free their time so they can spend more time with customers.

RPA interfaces with existing processes and can send data and messages between multiple applications without human interaction. This is why RPA includes the name robotic. Like robotic surgery, 3-D printing, and drones, RPA is not a robot, but the automated way in which it works is considered robotic.

David Schatsky, a Managing Director at Deloitte LP, follows how banks have been implementing RPA. He reported one bank had redesigned its claims process by deploying 85 software bots, another term for RPA, which ran 13 processes and handled 1.5 million requests per year.  The transaction capability the bank was able to add with the RPA was equivalent to adding more than 200 full-time employees at approximately 30 percent of the cost of recruiting, hiring, and training human staff.

Dozens of RPA vendors, including Blue Prism, Cortex Intelligent Automation, IBM, UiPath, and WorkFusion offer easy to implement software bots which require no custom software or complex implementation. Some vendors enable enterprises to combine RPA with artificial intelligence technologies such as machine learning, natural language processing, and speech recognition to take their automation efforts to a higher level with judgment and perceptual capabilities which formerly could only be done by humans.

RPA implementations of this nature can automate 15 to 20 transaction processing steps which were previously manual. According to Gartner, a global research and advisory firm, automation and artificial intelligence will reduce employee requirements in business service centers by 65 percent.  The global RPA market size was valued at around $1.5 billion in 2020 and is expected to reach more than $25 billion by 2027, growing at a CAGR of 33.6%. Gartner says 40 percent of large enterprises have adopted an RPA software tool.

I believe banks implementing RPA to make processes speedier and more accurate will have benefits for consumers, but implementing RPA does not bode well for bank employees. RPA has the potential to eliminate a large number of jobs. In the short term, employees will have more time to build customer relationships and work on their personal career development. Banks will attempt to transition as many workers as possible to new jobs. However, in the medium and long term, the RPA software will eliminate jobs which are no longer needed. Forrester Research estimates RPA will cause the loss of 230 million or more workers worldwide, or approximately 9 percent of the global workforce.

Entrepreneur Magazine described five areas of banking where AI may have the greatest impact. The biggest area is customer service. Natural language processing technology will make it difficult for consumers to distinguish between a voice bot and a human customer service representative. Combined with AI, the bots will resolve customer issues without human intervention. Automating customer service will lead to huge savings for the banking industry. A recent study predicted AI could lead to a reduction of 1.2 million jobs resulting in up to $450 billion in savings by 2030.

A second area of opportunity in banking is the use of personalization. Banks have access to a large amount of data about its customers, including detailed demographics, website analytics and records of online and offline transactions. Banks will apply machine learning to analyze the consumer information and develop a comprehensive view of the consumer’s financial behavior. Using these views, the banks will create personalized financial products and services.

Personalization of financial offerings is dependent on consumer trust and strong security. Apple and Goldman Sachs have taken a leadership role with the Apple Card. A growing number of banks are utilizing biometric authentication such as fingerprints and faceprints to replace or supplement existing login and password approaches. A report by Goode Intelligence forecast 1.9 billion banking customers will be using some form of biometric identification by 2025.

In a widely discussed innovation to its popular iPhone, Apple has evolved its Face ID so it now uses AI-powered facial-recognition technology to unlock the device as well as validate purchases using Apple Pay, its digital wallet service. As facial recognition and other biometric authentication techniques become more sophisticated and secure, they are poised to become commonplace.

A fourth area of great importance to the banking industry is fraud prevention. McAfee, LLC, a global computer security software company headquartered in Santa Clara, CA, estimates fraud and cybercrime costs the global economy $600 billion.  AI and machine learning can sift through massive amounts of data and identify patterns which human observers would never detect. Most people have experienced a case where their credit card was turned down for an unknow reason. AI technology will become smarter over time. According to tech news site Tech2, Mastercard was able to reduce false declines by 80 percent using AI technology.

The fifth area highlighted by Entrepreneur Magazine was process optimization. As discussed above, significant savings can be achieved by automating high-volume, low-value processes. The magazine cited an example of a bank which used AI to handle internal IT requests such as employee requests to reset passwords. The AI handled 1.7 million requests which represented the work of 40 full-time employees.


The World Bank Blogs published an article named “The Fintech revolution: The end of banks as we know them?”  FinTech refers to new applications, processes, products, and business models emerging in the financial services industry. FinTech startups are exploiting AI, machine learning, facial recognition, voice recognition, and distributed ledger technology (blockchain). Predictions of banks becoming extinct may be hyperbole. This reminds me of the famous quote by Mark Twain, “The reports of my death are greatly exaggerated.”  I believe Fintech is in its infancy. However, as discussed, AI has already had a substantial impact on how banks operate. Entrepreneurs and investors will find a multitude of opportunities for improvement ahead.