Harnessing AI and RPA to achieve Intelligent Automation in Banking

Overview

i. What is Intelligent Automation?

Intelligent Automation is the combination of Artificial intelligence (AI) and Robotic Process automation (RPA) systems which senses and synthesizes vast amounts of information and streamlines entire processes, their workflows (applications ranging from routine to the revolutionary), learning to adapt as it goes to achieve unprecedented levels of efficiency, quality, and making complex decisions faster.

ii. Why do banks need Intelligent Automation?

The rapid development of intelligent automation is ushering in a new era of productivity and innovation. In recent years, if IA has impacted one industry more than any other, it’s the Banking industry. An increasing number of Banks are gearing to adopt AI and RPA to not just stay competitive, improve efficiency, but also reduce the burden of hiring non-core resources which can be easily automated. According to analysts estimate – AI (Artificial Intelligence) alone will save more than $1 trillion in the banking industry. Financial institutions should expect a 22% cost reduction in operating expenses due to AI, with most of the savings coming from the front office. IA (Intelligent Automation) will also allow banks to offer new features, better user experiences for their customers and enter new markets to grow which have been traditionally quite difficult.

iii. What is Artificial Intelligence?
Artificial Intelligence is an area of computer science that emphasizes the creation of intelligent machines that sense, comprehend, reason and act to emulate human behaviour and overcome some of the barriers of human intelligence (like speed and scalability). Artificial Intelligence can simulate the intelligence of humans into artificial machines with the help of sophisticated machine learning and natural language processing algorithms and overcome such human barriers.

iv. What is RPA?
It is the use of software and machine learning to automate highly repeatable, high volume tasks, thereby enabling the human workforce to focus on high value tasks.
Robotic process automation (RPA) is about to change the way banks conduct business faster than any other new piece of technology available.
For the banking industry, robotics are a new, and completely underutilized way to increase productivity and keep repetitive, manual-labour-intensive processes at a minimum.

v. What is Cognitive Automation?

Cognitive automation is based on software introducing intelligence into information-intensive processes.
It is commonly related to RPA as the conjunction between AI and cognitive computing.
Cognitive computing is the imitation of human thought processes into a digital model.It involves self-learning systems that use data mining, pattern recognition and natural language processing.

vi. What are the key drivers of automation?

Customers: using contextual information to gain insights into customer behaviors and preferences, and creating new interaction experiences models with chatbots, virtual agents and more

Modernization: automating systems and processes to support digital transformation

Efficiency: reducing costs and increasing process capacity

Speed of processing- RPA can process transactions at a much faster pace than humans.

Cybersecurity: digesting and understanding massive flows of network data and making automated judgements to identify cyber threats

High availability- Robots are available for work 24/7

Reduced costs – Robot license costs are much lower than the average cost of human workforce.

Improved accuracy- RPA can significantly reduce errors otherwise caused by manual effort.

Quality – Increasing consistency of service and compliance and reducing human errors.

High flexibility- It is much easier to turn on and turn off capacity, unlike with a human workforce.

Robust traceability- A record can be created for all the activities that robots perform.

vii. What are the uses of AI across in the banking and financial services?

• Customer services. This is one of the most common applications of AI in financial services. Instead of client service executives having to work through hundreds of emails manually, AI can ingest the emails, understand their meaning, and prepare an appropriate answer that the client executive can check and submit with one click.

• Sales and customer intelligence. Again, a fast-growing area, AI is deployed to gather and analyse customer data and intelligence to give business development teams new insights, sales leads and recommendations for the ‘best next action’ to develop the relationship and drive forward a sale. • Operations. Intelligent automation is a potent way to drive efficiencies and improvements across end-to-end processes, such as insurance claims processes.

• IT services. AI can pinpoint whether an application or piece of hardware is likely to fail, massively increasing effectiveness and resilience of IT infrastructures.

• Fraud prevention. AI is increasingly critical to effective fraud management, by detecting and eliminating fraudulent payments or claims.

• Cyber security. As cyber threats grow and get more sophisticated, AI can be used for predictive analytics that can detect cyber attacks, even before they happen.

viii. What are the key benefits of RPA in Banking?

• Flexibility
The artificial intelligence of the new age robots is designed as such that they have the minimal maintenance and coding requirements. To operate such Robotic Process Automation operation in banking is hence a seamless and hassle free procedure. Robots can very flexibly adapt to the operational setup and are completely capable of operating third party software as well.

• Cost Reduction
A software robot license is likely to cost less than a staff member: low costs and fast implementation. Also, It does not require constant monitoring by an IT professional, thus freeing up the latter for other tasks

• Customized Efficiency
With the implementation of the Robotic Automation Process, banking services have the flexibility to employ their full-time employees towards other quality oriented, more complex tasks which require human creativity and intellect. Such employees could work towards creating and offering more customized product offerings for customers, which are tailor made for every consumer’s particular needs.

• Improved Accuracy Another benefit of employing the Robotic Process Automation in the banking industry is the omission of human error related issues. Since the robotic systems are designed only to execute specifically configured operational instructions, they result in a precise, accurate and error free process execution which reduces the time and costs associated with correcting human errors.

• Better Customer Experience
By automating banking business, banks are offered the tools they need to satisfy the specific needs and wants of specific customers. Increasing personalization boosts customer response and conversion rates and increases returns on marketing investment.

• Scalability
RPA is code-free and thus easily implemented in departments because it does not require programming skills and business users can be trained.

• Lightweight RPA software does not require fundamental process redesign usually associated with IT-driven transformation, because RPA addresses the presentation layer of information systems.

ix.What are the key challenges faced by RPA ?

• Expensive – Budgetary restrictions are among the biggest reasons why businesses opt not to implement RPA.

• Lack of Technical Ability – Many people believe that in order to leverage robotic process automation, the end user must possess significant technical know-how. This misconception often holds them back from reaping the many benefits that are available to them.

• Major Change – Adopting a new technology requires change, but with the right tool, the impact of that change is much less noticeable and disruptive than many realize.

• Redundancy – Another common concern of those resistant to RPA is the fear that robots will replace human workers, when its main purpose is to actually support humans in the workplace.

x. What are the use cases of RPA in banking?

1. Customer service
RPA helps in resolving the low priority queries, freeing up the customer support team to focus on high priority queries requiring human intelligence.
RPA also helps in reducing the time taken to verify customer details from disparate systems and onboard them. The reduced waiting period has helped banks in improving customer relations.

2. Compliance
RPA helps in increasing productivity by functioning 24/7, improving the quality of the compliance process, and increases employee satisfaction by eliminating monotonous tasks.

3. Accounts Payable
Accounts Payable is a monotonous process that requires digitizing invoices from the vendors using Optical Character Recognition, extracting information from all the fields in the invoice, validating it, and then processing it. RPA helps in automating this process and automatically credits the payment to the vendor’s account after reconciliation of errors and validations.

4. Credit card processing
Earlier, it took weeks for a bank to validate and approve the credit card application of a customer which resulted in customer dissatisfaction, sometimes even leading to a customer cancelling the request.
However, with the help of RPA, banks are now able to speed up the processof dispatching the credit cards. It takes just a few hours for RPA software to gather customer documents, make credit and background checks, and take a decision based on set parameters on whether the customer is eligible for a credit card or not

5. Loan processing
Reduction of consumer loan processing time from 30 minutes to 10 minutes by eliminating copying and pasting of customer information from one banking system to the next

6.Fraud Detection
RPA can ensure robust processes in the area of cyber risk, where it is being deployed to build anti-money laundering protocols, zero-fault tolerance architectures and faster recovery in events of security breaches.

7. KYC process
Know Your Customer (KYC) is a critical compliance process in every bank. Considering the cost and resources involved in the process, banks have now started using RPA to collect customer data, screen it, and validate it. This helps the banks to complete the process in a shorter duration with minimal errors and staff.

8. General Ledger
Banks have to ensure that their general ledger is updated with all important information such as financial statements, revenue and expenses. This information is used for preparing financial statements of the banks, which is then accessed by the public, media, and other stakeholders.
Considering the enormous amount of details required from disparate systems to create a financial statement, it is important to ensure that the general ledger is prepared without any error. This is where RPA comes to rescue. It helps in collecting information from different system, validating it, and updating in the system without any errors.

9. Report Automation
As a part of compliance, banks have to prepare a report about their various processes and present it to the board and other stakeholders to show the performance of the bank. Considering how important the reports are to the reputation of the bank, it is important to ensure that there are no errors.
RPA helps banks in preparing reports with accurate data. It gathers information from different sources, validates it, arranges it in an understandable format, and schedules it to be sent to different sources.

10. Account Closure Process
Banks receive several requests to close the accounts on a monthly basis. Sometimes, the accounts can also be closed if the client does not furnish the proofs required for operating the account. Considering the high volume of data handled by the bank every month and the checklist they need to adhere to, the scope for human error also increases.
With RPA, banks can send automated reminders to the customers asking them to furnish the required proofs. It can also process the account closure requests in the queue based on set rules in a short duration with 100% accuracy.