Banks and other financial institutions have always been very good at keeping track of paperwork. Between government regulations, customer expectations, and financial accuracy, there’s enormous pressure to keep paperwork error-free and secure.
Still, managing the data is complex and labor intensive. With accuracy and cost savings in mind, banks have raced toward automating end-to-end processes. Not only is process automation efficient and less error-prone, it also frees up staff time and provides cost savings to the industry.
Digitization can help in other ways, too. As customers increasingly seek online and mobile solutions for everything in life, banks need to keep up with demand by providing better digital experiences.
Financial institutions have adopted a range of use cases for intelligent automation, from simple integrations of cognitive services into process automation systems to, in a few instances, artificial intelligence (AI)-powered decision making. As such, they have also encountered the security risks and governance challenges that arise from intelligent automation sooner than most.
Robotic process automation (RPA) and intelligent automation allows banks to run repetitive processes, like data entry and customer service, more accurately and effectively without overhauling existing systems. This enables them to reduce costs, turnaround times, and manual mistakes while helping employees focus on value-added activities.
What is financial automation?
Automation is about taking processes that have historically been handled by people and letting computer programs do the work. Typically, banks and financial institutions have already deployed at least some level of automation. With the growth of artificial intelligence and computer programming becoming more complex, banks are rapidly transforming their businesses to provide customers with faster, better service.
Robotic process automation (RPA)
Financial institutions can configure computer software to process information automatically. These programs use existing applications to process transactions, manipulate data, communicate with other applications, and trigger responses.
Banks often use RPAs for repetitive processes, including data entry and customer service.
Intelligent automation (IA) vs. Artificial intelligence
The umbrella term for any of these digitized processes is intelligent automation. It’s categorically broad, encompassing all uses of computers and artificial intelligence. As an example of intelligent automation in the financial services industry, AI has been deployed to automate the identification process that verifies customers are real people. That alone has streamlined a process that used to take days or weeks into minutes (or in some cases, seconds). This digital identity verification allows customers to benefit from the convenience of completing the process on their mobile device rather than going to a bank.
Among many other use cases, AI can make chatbots more responsive and useful for customers. Bots can be trained to handle more complex processes as AI learns and improves their processes. For instance, Chatbots can now draw on an RPA to get information to have more detailed conversations with customers.
Why is automation important in financial services?
RPA bots can perform Know Your Customer (KYC) tasks. They can automatically process the data and manage the entire KYC cycle, including receipt of documents, validating identities, managing the documents and archiving them, and generating reports. Automation can also extract data from documents, combine the information with internal documents, and perform due diligence on loan decisions.
Perhaps the most obvious use of digital automation is when banks run repetitive data entry tasks with bots. All data is entered accurately and in the right places without overhauling existing systems. The bots can handle transaction data from multiple programs or apps and bring it into one program for one-stop viewing by bank employees. The RPAs can manipulate the data, generate reports, and distribute them to staffers.
This automation term can encompass everything from simply digitizing tasks that used to be done on paper to creating a complex system that covers every aspect of a bank’s process management. Documents can be tracked at all stages and shared with any employee. This speeds up processes and eliminates human error — from lost documents to employees forgetting steps in the process.
As a rule, banks like to know exactly how much risk they take. Automation helps on multiple fronts. In loan considerations, RPAs use credit scoring models to improve the accuracy of decisions. They can also be deployed to evaluate the stability of the financial institution’s entire portfolio, and the work can be done very quickly, giving banks a real-time look at their risks.
5 use cases of automation in financial services
1. Loan application processing
In addition to collecting data, RPAs share data between the multiple systems needed in loan applications. They can also generate reports and speed the process along. But, they can do much more. For instance, banks can use RPA to automate approvals of some of its loans.
2. Preventing money laundering
The eKYC process includes face verification and government ID checks, just like a brick-and-mortar solution. Financial institutions are required to gather a client’s name, date of birth, address, employment status, annual income, net worth, investment objectives, and identification numbers before opening an account. All of this can be handled with RPAs. This efficiency helps businesses improve their conversion rate by creating an optimized process that gives customers fast access to financial services.
3. Card management
Credit and debit cards can be a hassle for banks, but the tasks are often repetitive, which means they can be automated. A bot can handle replacing lost or stolen cards, reverse charges, or handle billing. Automation provides quick and easy customer solutions and frees employees for other tasks. Credit card companies typically deploy RPAs to flag suspicious transactions, put a hold on accounts, and contact customers to verify charges are accurate.
4. Trade finance
Perhaps no area of finance has been more paper-intensive than trade finance. It’s in its nature to be highly focused on documentation and checking. Since everything is potentially subject to compliance checks, there’s a focus on accuracy. Digitization streamlines a process that used to take up to a week and drastically reduce the turnaround time with the use of automation. Storage and handling costs are also greatly reduced with RPAs, and operational risks can be lessened.
5. Customer service
Automation can simply mean deploying a chatbot on a bank’s Facebook page or website to help customers find the information they’re looking for. Banks have also found RPAs can handle tasks like same-day fund transfers, where an RPA checks to make sure there are funds available, performs the transfer, charges the customer, and notifies the account. An RPA can also close an account — including canceling debit cards — without any human intervention.
How Notarize can help financial services digitize their notarization process
As financial institutions hurry to provide digital solutions and keep customers happy, Notarize makes things easier by setting new standards for security and user experience. Many consumers want the option to complete their financial transactions completely online. Notarize provides a seamless and secure way for your customers to notarize their documents online. Digitizing the notarization process for financial services documents can save you and your customers time and money, while providing an unmatched user experience. Schedule a demo to learn more about how Notarize can help your financial institution today.