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With all the focus on artificial intelligence (AI), it can be easy to overlook a far simpler but effective cousin: automation. For community financial institutions (CFIs) watching the rise of AI solutions at big banks, and worried about being left behind, much simpler automation can provide a way to improve processes and profits with a quicker return on investment (ROI).
Simple automation may seem somewhat of a relic in today's fast-moving world. In fact, it is just a step away from AI. While the ROI for automation might be lower, the impact on a CFI's bottom line nonetheless could be big.
For many CFIs that still rely on tedious manual processes for back office functions, automation can help. There are a host of products in the marketplace that can provide such automation. In more elegantly updated terms, this is also known as robotic process automation (RPA). RPA is a fancy way to say you are using programming software to automate processes and communicate with other digital systems.
Compared to AI, RPA programs can be simple, use little to no data, and be very inexpensive. A CFI that still processes lots of paperwork by hand should be able to automate processes fairly quickly and see an ROI in a short time frame of even weeks.
For those who have already deployed some automation, finding more functions to automate now might be a better move financially than trying to jump into AI at this point.
For CFIs that still do most tasks manually, automation can be introduced one step at a time. Start by choosing the simplest repetitive tasks first, and then move on through the organization looking for new processes ripe for automation.
As a CFI fills out its automation opportunities, AI becomes more attractive as the next step. Machine learning can help as this tool finds ways to improve complex processes, like examining invoices under certain criteria. It actually has the ability to recognize and evaluate information to help in functions, such as underwriting.
For those interested in the outer edges of the possible, there is also deep learning. This is AI that is able to sort of think like a human about issues or processes. For example, a deep learning solution might be trained to detect suspicious account patterns, as it works to quickly identify potential fraud.
The payoff for AI deployed in CFIs is expected to be sizable over the next few years. AI and technology augmentation could provide up to $140B in productivity gains and costs savings for the banking industry by 2025. While those big gains from AI may still be a long way off for many CFIs, simple automation can still provide quick returns on investment.