The spectrum of automation expands from simple rule-based automation to advanced cognitive and artificial intelligence automation. The ability of the tool/solution to automate depends on three factors which are as follows:
- The type of input it can read, 2. The amount of data it can process, and 3. the nature of output it can generate.
Typically, as the variability of the input increases, the amount of data to be processed multiplies and the output moves from being deterministic to predictive, i.e., the solution moves from Robotics Process Automation to Intelligent Automation to Cognitive Intelligence and then to AI on the spectrum.
Robotics Process Automation (often referred to as ‘RPA’) sits at one end of this spectrum.
Robotic Process Automation – Mimics Human Actions
- Used for rules based, simple to complex processes • Faster handling time • Higher volumes • Reduced errors & costs. E.g., UIPath, Automation Anywhere.
Intelligent Automation– Mimics Human Judgement
- Used for Judgement Based processes • Machine Learning capability • Interprets Human Behavior. E.g., Workfusion, Ayasdi.
Cognitive Intelligence – Augments Human Intelligence
- Used for predictable decision-making • Dynamically self- adaptable and managing. E.g., SIRI, Google Self driving car project.
Artificial Intelligence– Mimics Human Intelligence
- Acquires human like thought and decisionmaking capabilities. E.g, HAL 9000.
Since Cognitive Automation is still in early stages, companies are focusing on RPA for Mainstream Automation
Robotic Process Automation(RPA)
RPA is a technology that mimics the actions of a human performing simple rule-based processes. It interacts at the application/interface layer of any application and performs the exact steps just like anyone working across multiple applications.
“RPA is the natural evolution of labor arbitrage, it takes the Robot Out of the Human” It is cost effective, scalable, and easy to implement. This is the biggest difference and advantage RPA has over traditional automation techniques that relied on backend automation requiring massive IT transformation, huge investments and complex decision making/ approval cycles given its susceptibility to security issues.
RPA in Banks and Financial Industry
Banking and Financial industry is seen to be growing exponentially over the past few years with the implementation of technological advancements resulting in faster, more secure and reliable services. In order to remain competitive in an increasingly saturated market – especially with the more widespread adoption of virtual banking – banking firms have had to find a way to deliver the best possible user experience to their customers.
According to PwC, nearly 81% of banking CEOs are concerned about the speed of technological change, more than any other industry sector. Internally, the challenge to maximize efficiency and keep costs as low as possible while also maintaining maximum security levels has also increased. To answer these demands, Robotic Process Automation (RPA) has become a powerful and effective tool.
RPA has been significantly adopted in this sector, for making the time-consuming banking operations more organized and automated.
RPA has a plethora of different applications in the BFSI segment to free up the manpower to work on more critical tasks. Some of these processes include:
Banks deal with multiple queries every day ranging from account information to application status to balance information. It becomes difficult for banks to respond to queries with low turnaround time.RPA can automate such rule-based processes to respond to queries in real time and reduce turnaround time to seconds, freeing up human resource for more critical tasks.
With the help of artificial intelligence, RPA can also resolve queries which needs decision making. With the help of NLP, Chatbot can understand the natural language to chat with customer and respond like human.
A global bank deployed an ATM testing robot to automate the test cases that were earlier conducted manually. The robot came with 5 components:
- Vision system for screen reading and identifying keyboard number, card slot, cash, and receipt identification
- High dexterity robotic arm to reach out to all areas of ATM operations
- Processing unit
The robot tested various aspects including the screen, keypad, card dispensing mechanism, cash and cheque handling mechanism, cash counting mechanism, and debit and credit card differentiator, to deliver up to 80 percent cost and time savings.
Banking being the center of the economy is closely governed and needs to adhere to lot many compliances. RPA increases productivity with 24/7 availability and highest accuracy improving the quality of compliance process.
Accounts payable is a simple but monotonous process in the banking system. It requires extracting vendor information, validating it and then processing the payment. This does not require any intelligence making it the perfect case for RPA.Robotic Process Automation with the help of optical character recognition (OCR) solution can solve this problem.
OCR can read the vendor information from the digital copy physical form and provide information to RPA system. RPA will validate the information with the information in the system and process the payment. If any error occurs, RPA can notify the executive for resolution.
Credit Card Processing
Traditional credit card application processing used to take weeks to validate the customer information and approve credit card. The long waiting period was dissatisfaction to customers and cost to banks. However, with the help of RPA, banks now can process the application within hours.
RPA can talk to multiple systems simultaneously to validate the information like required documents, background checks, credit checks and take the decision of the basis of rules to approve or disapprove the application.
In United States, it takes approx. 50 to 53 days to process mortgage loan. Process of approving mortgage loan goes through various checks like credit checks, repayment history, employment verification and inspection.
A minor error can slow down the process. As the process is based on specific set of rules and check, RPA can accelerate the process and clear the bottleneck to reduce the processing time to minutes from days.
With the introduction of digital system, one of the major concerns of banks is fraud. It is really difficult for banks to track all the transactions to flag the possible fraud transaction.
Whereas RPA can track the transactions and raise the flag for possible fraud transaction pattern in real-time reducing the delay in response. In certain cases RPA can prevent fraud by blocking accounts and stopping transaction.
Know Your Customer (KYC) is a mandatory process for banks for every customer. Considering the cost of the manual process, banks have started using RPA to validate customer data. With increased accuracy, the process can be completed with minimal errors and staff.
Like all other public companies, banks need to prepare report and present to their stakeholders to show the performance. Considering the importance of the report, there is no chance for the bank to make error.While RPA systems provide data in multiple formats, it can create report by auto filling the available report format to create report without errors and minimum time.
Account Closure Process
With such a huge number of customers, it is supposed to get some account closure requests on monthly basis. There can be various reasons for the account closures and one of them is when client has failed to provide mandatory document.
With Robotic Process Automation, it is easy to track such accounts and send automated notification and schedule calls for the required document submissions. RPA can also help banks to close account in exceptional scenarios like customer failing to provide KYC documents.
Mobilizing Tons of Data
As the 10 banks merge in 4 big banks, huge chunks of data will be migrated from different platforms to one single platform.“If here are two or three different entities using different technologies then one common structure has to be designed, this is a right fit for RPA to come in from manual transfer to automated transfer by bots,” said Arup Roy, VP Analyst at Gartner.
Benefits of RPA in banking:
- Cost Savings
Many argue that RPA does not reduce cost but provide more value addition to the overall organizational benefits and efficiency. Whereas, the various implementation show slightly different data.Banks are always looking to cut cost in such competitive industry. Thanks to the RPA. Research shows that implementing RPA drives about 25% to 50% cost savings, improving the output metrics of applied functions.
- Expediting the Operational Efficiency
Banks play a very important role in influencing the economy. If all the banks become more efficient, it’ll have direct and ripple effect on many other industries.
RPA is an extensive solution which requires employee training, governance, comprehensive setup. But once it is in place, research says that banks will save 40-60% in the first year of implementation making processes faster and much more efficient.
- Agile Businesses
With the growing technology penetration in every industry and globalization, banks need to be more agile and flexible than ever. The effect of things happening on the other side of the world can be seen in hours instead of days. With RPA, banks get a chance to prepare for any situation and respond in no time.Also, by freeing up the human resources from daily mundane tasks, more focus can be given coming up with innovative strategies to grow business.
- Growth with Legacy Data
Technology has allowed us to digitize the data from the paper entries making it available for businesses. With RPA, banks are using legacy and new data to bridge the gap between processes. With the availability of data in one system allows creating faster and better reports for the business strategies.
- Reduced Business Response Time
Banks are incorporating Robotic Process Automation for faster process execution and operational efficiency. Research says that banks will be able to save 75% of the cost while retaining the quality output. Banks like HDFC and ICICI are using RPA to bring down process execution time by around 60%. RPA is disrupting the way banks are operating and the adoption will increase with the CAGR.
- Leveraging the Existing Infrastructure
Implementing Robotic Process Automation does not require setting up new infrastructure. The unique quality of RPA technology allows it to integrate with any system irrespective of the development technology making it applicable enterprise wide. Banks are already using RPA in operations, sales, Human Resources, Admin, Finance functions to optimize process with efficiency and reduced cost.
Challenges in Adoption of RPA:
1. Managing employees’ resistance
The “robots will steal our jobs” narrative, often used as a typical robotic process automation objection, is the core reason for the staff’s lack of willingness to accept new technologies.Prior to engaging in the automation project, one should educate them regarding what software robots can and cannot do, and help them understand that the bots are to be seen as helping, and not as hindering, the current work roles. Moreover, one should invest in training employees regularly, as the ‘automation era’ will likely require them to acquire new skills.
2. Inability to automate end-to-end processes
For the more complex processes, RPA tools may be insufficient for directly automating all the process steps. “Divide and conquer” is recommended way to go about this. Redesign these sophisticated tasks, break them into simpler parts, and start automation.
- Insufficient assistance from the all department
Relying solely on the IT department is among the common RPA challenges that should be actively avoided throughout the automation project. Business processes require a Process Design Document for the pilot phase, including workflow diagrams, data-specific business rules (for various types of data), a comprehensive list of technical exceptions that the operations unit may face during manual processing, etc. It is more likely that the pilot paves the way for successful long-term development if the business team gives feedback for bots’ performance.
- Lack of effectively structured RPA implementation teams
As always, lack of structure is a pitfall. But the good news is that it is not too difficult to be fixed. “Effective structure” arises out of clearly specified roles for the team members, sufficient knowledge about the processes selected for automation, as well as not allowing resources to be shared among multiple ongoing projects.