Many banks are seeing the value of RPA. This has therefore increased the application of robotic process automation in the banking sector. A recent RPA report has shown that the RPA industry will reach a whopping $ 29 billion, transforming major sectors such as financial and banking services.
The trend is that leading banking and financial institutions are now working with partners to leverage RPA in their operations. However, there are still many banks, lending organizations are financial institutions that are still in bewilderment about how RPA can be used to make their banking operations smooth, effective and efficient. The following are seven (7) practical application of robotic process automation in banking today.
1. Credit Application Processing
The advent of e-commerce and online business activities have increased the usage of credit. Many businesses now sell online and offline, using credit cards to process payments for clients. It is therefore incumbent on respective banking partners to streamline operations efficiently with credit cards.
In the past, traditional credit application processing can take weeks to validate, approve and process. But with the application of robotic process automation in credit card processing, banks can now approve or disapprove credit card application in a matter of minutes.
RPA bots quickly talk with multiple processing systems to validate applicant information such as credit score, background identity and personal documents in a couple of minutes. This can mean more business for banks, increasing profitability and bottom line profits.
2. Customer Service Operations
To stay competitive in the banking industry, customer service is mandatory. It is no more an option for banks to have a customer service department, it has become a mandatory operation to provide high user experience to customers. And that means banks need to ensure that they respond to hundreds, thousands and sometimes millions of queries every day.
While customer service staff are required to handle these queries and inquiries, they can be overloaded with many tasks and therefore result in low turnaround time for customer accounts. This can cause problems if those queries required urgent attention. Instead of employing more staff to the already existing one, the management of the bank can simply leverage RPA to process and respond to queries in real-time with a high turnaround.
RPA Chatbots programmed with artificial intelligence can be installed at critical meeting points to handle and process customer queries. RPA chatbots are programmed with various responses to customer queries; they also understand human language and can chat with customers just like a human administrative staff, providing professional customer service for the bank. This will then free up the regular customer service staff to focus on more intelligent and clerical administrative tasks.
3. Mortgage Loan Processing
With demands for housing increasing across the globe, people will always depend on loan programs such as mortgage to purchase the home of their choice. All across Canada, the UK, Asia, and Africa, people are understanding the simplicity and usefulness of mortgage programs.
In view of this, many banks are providing mortgage loan programs to their customers. But what discourages many middle to high-income earners from applying for mortgage loans is the boring, long process of application. In some cases, it can take about two weeks for a mortgage loan application to be approved for financing.
The delayed process can reduce the number of applicants and hence the bank’s profitability. Instead of undergoing the manual information verification for analyzing applicant's identity, background, employment history, credit score, credit history and financial status which takes many days to handle, RPA bots can be programmed to process this information. Additionally, rather than relying on busy IT teams and complex API/integration routines to make disconnected systems speak, RPA software bots can reduce the verification process to minutes or days to increase mortgage applications and customer satisfaction by interacting with front end applications without complex API/integration work.
4. Small Business Loan Processing
Local businesses need operational loans to expand and grow their business. Banks need loan applicants to get a high return on deposit acquired from customers. While both parties benefit tremendously from the transaction, the transaction must be processed on time and managed well for better customer experience.
Business loans are a major source of revenue for many banks. But errors in the processing and application of the loans can lead to tremendous cost for banks. It behooves banks and lending financial institutions to adopt efficient data management and processing during or after loan applications. This will not just enhance loan applications but also help in the management of loan payments for the banks.
Defaults in the payments of loans is another bottleneck issue for most banks. RPA bots can help to quickly process loans for local business people and provide an accurate lending report for each loan application. Instead of using human agents to handle the back-office loan verification, processing and management, RPA bots can be assigned these tasks, reducing human efforts while at the same time ensuring that professional departmental teams are assigned to ensure efficiency.
5. General Banking Ledger Management
Banks are central to the development of economies and countries. Many businesses, organizations, and institutions depend on the financial reports of banks to make various financial decisions. Investors invest based on financial reports and customers use these reports to decipher between the best banking partners to process and manage their banking services.
That means the general ledger, from which information is gathered to prepare financial reports must be accurately updated and well managed. Looking at the volume of data banks handle and process each and every business day, it can sometimes be hard for human agents to update the general ledger accurately without making any errors. Even with the use of sophisticated ERP and other enterprise-grade software, legacy banking software often still requires manual work and therefore are prime for RPA to take over.
Interest incomes, account receivables, account payables, expenses, assets, liabilities, and many other important financial data needs to be accurately updated in the general ledger to help prepare accurate financial statements for the bank.
Managing a huge number of data without making any errors can be tough for humans, but not for RPA bots. RPA bots understand multiple banking systems and applications, they effortlessly and accurately update the general ledger and can communicate with distributed legacy or disconnected system with the required financial data.
6. Accounts Payable Management
Accounts have to be paid for banks to remain profitable. To process accounts payable operations, banking staff are typically required to extract the debtor information, validate with the system information and finally process the payments made.
While this process can seem very simple, many banks are already seeing the monotonous nature of it and hence leveraging RPA in processing their accounts receivable. Robotic Process Automation can be used alongside technical solutions such as Optical Character Recognition (OCR) to increase the processing of accounts receivables.
Optical Character Recognition (OCR) reads the digital copy of the vendor information in the bank's application system and transfers that information to the RPA system. The RPA system continues by verifying and processing the payments. This process can happen in a matter of seconds or minutes, creasing the bank’s efficiency.
7. Cyber Security & Fraud Prevention
One of the major concerns of banks is a fraud. With fraud and cybercrime projected to hit $6 trillion by 2021; banks, lending, and financial institutions have no option than to protect their financial data. Exposing accounts and financial data means granting access to hackers to hack into the bank's database and commit fraud.
To prevent this, many banks are using several application systems to track all their financial transactions, protect vital financial data from hackers and also provide a red flag were necessary to quickly attend to any fraudulent activity. But with a huge volume of data potentially exposable, many banks have fallen victim to cyber crimes and fraud operation from trickers.
RPA software bots can be programmed to track, oversee and provide a quick report on all financial data of the bank. The RPA bots are also able to raise red flags in the event of any suspected fraudulent activity for the department responsible for Cyber Security & Fraud Prevention can take action and outsmart any agent responsible. Whereas there are delays to attending to the red flags raised by the RPA software bots, they can even go ahead to block the fraudulent transactions and safeguard the bank's data.
Looking to use RPA to grow and transform your banking operation? Talk to an Ntansa expert today. We're here and happy to help!