Loan Interviewers and Clerks

Banks are beginning to use AI and software to do many of the routine parts of loan work. For example, computers can now automatically check and fill forms, copy information across systems, and flag errors. Some banks use “robotic process automation” (RPA) tools that log into systems, move data, and update files just as a person would ^{[1] [2]}.

Chatbots and virtual assistants also answer common questions. Bank of America’s Erica chatbot has already handled over 3 billion customer interactions, helping clients with loan and account questions ^[2]. In the UK, NatWest is piloting generative AI for its customer chatbot, and early results show much faster responses and 150% higher customer satisfaction ^[2].

This means machines can handle many simple tasks – for instance, automatically emailing customers about loan status, sorting documents for closings, or pulling credit data – so people don’t have to do endless typing or filing. At the same time, banks say humans still do the tricky parts. For example, Kasikornbank (Thailand) says its AI will speed up “straightforward credit approvals” so that human underwriters can focus on harder cases ^[2].

In short, many loan tasks are being automated or aided by AI and RPA software, but people remain involved in the complex decisions and personal parts of the job ^{[2] [2]}.

Banks have strong reasons to add AI in lending: it can save time and money. Some reports predict AI might boost bank profits by hundreds of billions by 2028 because it cuts paperwork and routine work ^[2]. Big banks are investing heavily – for example, Bank of America plans to spend \$4 billion more on AI technology ^[2] – and are training staff to use it.

These tools already let a single banker handle many more clients by freeing them from routine data entry ^[2]. On the other hand, adoption is careful and gradual. Adding AI can be expensive to set up, and banks must retrain their workers ^[2].

They also face strict rules: loan decisions affect people’s lives, so regulators require fairness and explanations. For now, many banks say AI cuts the time needed for simple tasks (often 20–30% faster) ^[2], but big tasks still need a person’s judgement and empathy ^{[1] [2]}. In the end, banks hope AI will help employees do better work, not just replace them ^{[2] [2]}.

Young people entering banking may find more data and tech work, while human skills – like explaining options and working directly with customers – remain valuable in loan jobs ^{[1] [2]}.