Robotic Process Automation (RPA) is a kind of productivity tool, a business process automation technology, that automates various repetitive tasks without any human intervention. RPA in the banking sector means the use of software robots that understand user actions at the very user-interface levels, automating repetitive, routine tasks that are usually done by knowledge workers in banks. It allows users to configure scripts  (bots) to activate certain specific keystrokes in an automated manner that leads these bots to do mimicking and simulating the tasks selected.

The inherent benefits of RPA in the banking sector are three-fold

1. Creates, tests, deploys newer schemes in few hours rather than days or months
2. It reduces human error by virtually eliminating mistakes of entering the same data into multiple systems
3. Instant output by completing automated tasks in seconds thus delivering high values to customers

 Let’s discuss various real-time use cases of RPA being leveraged by the Banking sector across places!

RPA USES IN THE  BANKING SECTOR

Robotic Process Automation (RPA) has massive benefits in the banking sector as it reduces gaps between various applications by processing and integrating tasks at micro-levels. For instance, RPA, in general, does the following jobs-

• Helps in Accounts Payable (AP)
• Helps in Accounts receivable (AR)
• Helps during financial closing & reporting
• Helps in accounting data reconciliation
• Helps in bank statement reconciliation
• Routine or daily  P&L preparation

Besides the above-mentioned uses of RPA, specific use cases are there within the banking domain. What are they?

1. REPORT GENERATION AUTOMATION

Suspicious Activity Reports or SARS are a general phenomenon in the banking segment. SARS are the general compliance reports that are prepared to check the fraudulent transactions and suspicious activities that happen to be a routine cadence in the work domain. In a conventional method, compliance officers manually do this job, read the reports, fill in the detail in the SARS, and so on. The reports would be generally prone to having errors and redoing them would follow thereafter.

             Robotic Process Automation (RPA)technology has the capabilities to sort out this issue. By using its natural language generation capability, RPA does the rigorous regimen of reading all the documents, the lengthy compliance documents, and then eventually extracting the information required to fill up the SARS.

2. ONBOARDING OF CUSTOMERS IN BANKS

Once again, the manual verification of a large number of documents to decide the credibility factor of customers, for onboarding purposes, is an uphill task. RPA makes this task very easy, accurate, and convenient. The Optical Character Recognition (OCR)technique is the keyword. RPA uses its OCR capability to capture the required data from Customers’ KYC documents and verifying the very same. Thus, the OCR technique capability of RPA helps match the data extracted with those provided by customers. This leads to identifying the loopholes and the verification process becomes a very simple and trusted one.

3. DATA-CENTRIC KYC & AML

As compared with the traditional model of banking solutions, RPA  implementation proves to be a very cost-effective and time-saving model in the process mentioned. Normally, Know-Your-Customer (KYC) and Anti-Money Laundering (AML), are very rich data-centric, and a traditional banking solution cannot handle this job efficiently. RPA due to its inherent capabilities does the automation for the entire manual process and extracts all suspicious transactions in seconds if any.

4. RPA FOR OPENING AN ACCOUNT

RPA efficiently removes any scope of data transcription errors that had existed once between the core banking system and account opening requests. The automation process automatically eliminates all kinds of transcription errors and customers have a smooth account opening experience ultimately.

5. RPA FOR LOAN PROCESSING

Loan processing has always been a tedious, slow process . It used to be completely manual work and involved several stages to get the loans approved and sanctioned. RPA technology has accelerated the loan processing segment, too, in a banking system. RPI implementation means the integration of some front-end application onto the ongoing IT system without causing any disturbance in the current flow of  IT structure. 

Banks form the core of the economy of a country and the role of Robotic processing Automation (RPA) technology is manifold. RPA technology helps increase productivity and ensures the accuracy and efficacy of the entire banking system. Integrating RPA into the banking system is actually a part of the digitalization process involved in the very system.

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The present global crisis or the pandemic, has brought about one major revelation in the financial sector. All those banks that had adopted Information Technology inherently in their operations much before the start of crisis, came out to be absolute resilient when the crisis hit. Although these banks are having a fewer Non-Performing loans (NPLs), they are issuing loans at these times of crisis, too! Fin Tech Lending has become a new norm today and is being considered as an accelerator for financial stability in the market. The crux is, how technology is driving Fin Tech lending? In one word, it is digitalization! It is the Digital Lending that is transforming the financial set-up and enhancing customers’ experience.  

Lots of questions cropping up in mind now? Let’s walk through!

Digital Lending as a Concept

With the onset of Fin Tech in Loan segment, the lending process has changed drastically and for better only. No more cumbersome paper-work.  Loan-disbursement is possible now in a span of mere few minutes. How? Because of Digital Lending platform! The entire process is done through the electronic means.

If you want to buy a car, you apply for a car loan. If your friend wants to buy a property, he will go for a home loan. When your children go for higher studies abroad, education loan is the right choice. Even a personal loan can serve your purpose!

Not only you, your friend, your children but banks & financial institutions lend money to corporates and enterprises so that they (the borrowers) can execute projects and build products. Here, banks & financial institutions are the lenders while all others are borrowers. When the lending process involves information technology, it becomes a Digital Lending.

How IT Is Helping Loan Segment – The Very Digital Lending

We live in the era of Millennial and Generation Z, communication is in their fingertips. When they were born, mobile phone was already there. If they could click memories, share thoughts right from their birth, how could they lag behind in the lending process? Their expectation is naturally high! Let’s navigate the technology that are helping them in the digital lending segment-

RPA 

Robotic Process Automation or RPAis not a cutting-edge technology but increasingly gaining momentum in the Digital Lending process. Lending Management Automation is the RPA being widely used in the segment. As per SSON Analytics, Banking industry, along with Financial Services & Insurance industries, forms the topmost layer for using RPA solutions due to their inherent benefits.

Documentation Automation helps lenders to automatically extract customers’ data from their documents. Enterprise Automation allows customers to fill electronic forms for applying loans. Dedicated portal is available where this form exists. Once the form is submitted, an automated workflow will start operating in lender’s place. Everything in a flash of seconds. Moreover, customers can view status of the process anytime.

Electronic Signature allows customers to sign the documents online. No need of handwritten signature on a paper form. The system allows auditors to examine loan files in a most digital manner.

AI Credit Scoring Models

AI is helping banks to make an effective credit decisions. AI- Credit-Scoring models help banks become a competent estimator to figure out who will repay and who will default. Thus, banks have track records of loan repayment of customers in the granular form. The data are aptly valuable to understand the market dynamics as well.

How AI & ML determine Credit worthiness

As mentioned earlier, banks and other lending companies use AI models for risk assessment. In the past, lenders used to make assessment based on just FICO score & income. Now, they are assessing the entire life of an individual, their vast digital footprints, in order to determine if he can be a defaulter in future. This process is also referred as “Alternative Data” of the future borrowers. It helps to determine the credit worthiness of potential borrowers even without having any credit history.

Shift from 3-6-3 formula to 3-1-0 System

Heard about ANT Financial? It’s all about Digital Lending.

Digital lenders such as banks and Fin Tech companies are allowing customers to have exceptional digital borrowing experience. Digital lenders have to keep pace with customer’s demand and maintaining trust and loyalty is the core of any transaction or business. The ChatBots, using various analytics, are capable of giving relevant insights to customers while AI and ML help banks to know the earning and spending pattern of customers and analyze risks involved. Technologies like biometric-led authentication, e-mandates, e-signatures, AI, ML, Blockchain are using the ‘zero- human- touch’ lending & monitoring process.

According to a recent Boston Consulting Group (BCG) report, Digital Lending is going to become around $ 1 trillion opportunity in the coming five years. Indeed a good news for the Financial Lending Segment. So digital lending is just going to be a smarter, convenient and fastest mode to avail loan in modern ecosystem. Are you a bank, financial institution, Fintech or a startup engaged into loans sector?

Connect with us to uncover the possibilities in digital lending.

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