According to recent research by Gartner, human error in a financial institution can cost up to 25000 hours in reworks. This translates to more than $850,000 which when extrapolated to the entire sector means billions of dollars every year. It is no surprise, therefore, that the financial sector is keen to adopt robotic process automation to minimize reliance on human effort for processes prone to errors.
Robotic process automation on its own is limited in what it can achieve because it relies on simple logic i.e if this happens then do this. RPA completes tasks without any variation from the set logic. An example would be logging out of the system after a certain period of activity or updating records each time there is a sale. However, when RPA is paired with artificial intelligence, the range of applications in the financial sector are vast.
The Benefits of RPA In the Financial Sectors
Working in the financial sector has historically been associated with working long hours and getting bogged down by paperwork. RPA has helped reduce the stress levels for employees through automation. Robots can obviously work round the clock without errors as long as the setup process was okay. Employees get redeployed to handle more crucial and non-repetitive work.
Additionally, less reliance on human effort can translate to more than 30% cost reductions for financial companies. A good example would be a situation where people are trained to maintain their own RPA assistants instead of calling in the IT department whenever there is problem. One of the good things about RPA is that it works on top of existing IT infrastructure meaning there aren’t additional infrastructure requirements during implementation.
Let us explore a few use cases of Robotic Process Automation in the financial sector today.
1.Report Generation
Report generation is one of the most time-consuming tasks for people in the finance sector and yet it cannot be avoided. Companies need to generate reports both for internal and external compliance needs. Fortunately, because of the repetitive nature of report preparations, it is possible to build bots for automation. As long as organizations can prepare templates and set up proper pipelines for information sourcing, it can ensure that reports are always available on time.
In fact, the level of automation can go further such that natural language processing is used to flag adverse reports for further investigation. Normally, this would require hours of reading reports before noticing things that require investigation.
2. RPA In Accounts Payable Management
Manual handling of accounts payable involves data entry to digitize vendor invoices before comparison with source documents. This process is not only slow but it is prone to error and sometimes deliberate fraud. Automation involves the application of optical-character-recognition to capture information from an invoice. Bots compare the information against purchase orders for verification before payment processing. They then route errors to the right desk for investigation.
In banks OCR technology can help verify checks much faster than before while also reducing the frequency of errors in document handling. A smooth invoice-handling process in any industry improves the nature of relationships between an organization and its vendors.
3. Mortgage Processing
Historically, mortgages have taken more than a month to approve, and closing on a home purchase can feel overly complicated. Credit officers have to perform multiple checks regarding the employment status of a person, and their credit history required of them by the financial institution. An error in filling out any document can delay the process even further.
RPA can help accelerate mortgage processing by automating most of the checks as well as some of the documents preparation. This is possible because the documents to credit officers need to fill are common for all mortgage applicants while information on creditworthiness is likely to be available for authorized credit bureaus. Reducing the amount of manual work relieves bank employees of work-related stress significantly.
4. Better Customer Service
The finance sector is naturally one of the most heavily regulated industries in terms of the number of laws and thresholds that institutions must abide by. RPA helps in adherence to regulatory requirements that would otherwise require massive investment in labour. For instance, chatbots relying on artificial intelligence enable banks to service customers much faster and even during non-official working hours. In fact, customers today can transact from their savings and investment accounts using chatbots. Today, customers can renew or apply for new credit cards without filling any paperwork or interacting with a bank staff. All verification of personal information is automated. Customers can quickly find out whether their application was successful or not.
5. Fraud Detection through Robotic Process Automation
One of the most consequential application of RPA in the financial sector is fraud detection. Because of the sheer nature of the volume of transactions banks handle every day, it is impossible for humans to detect suspicious payments. Banks in the past would only rely on complaints from customers regarding unauthorized transactions before investigating and blocking credit cards associated with that account.
However, the combination of RPA and AI technology can flag suspicious activity with much greater accuracy. AI models are able to consider multiple factors simultaneously to minimize unnecessary flagging of transactions and blocking of customers cards.
Implementing RPA In Your Organization
There are other multiple opportunities to implement RPA in the banking and financial services sector. For instance, it is possible to process account opening and closure requests by setting up rule-based procedures and an interface through which customers can interact with the system. Organizations just need to pick a starting point for their RPA adoption and grow it slowly.
Picking an RPA vendor is an important decision because it determines the capabilities you can unlock. It’s always best when you pick a vendor with experience in implementing RPA solutions in your industry. Integrating RPA on-top of legacy systems can be much more complicated than on modern systems. You should expect automation of processes to happen gradually as opposed to rapidly.
If your organization is seeking to begin implementing RPA to improve internal processes, Transcendent Software can be your partner along the way. We are a fully-fledged IT-services company helping clients implement solutions including RPA. Check out this case study on automation and set up a call with us here.