Full Automation of Banking Services are not far : RPA Technology a catalyst

?ROBOTIC PROCESS AUTOMATION (RPA) ?USES?IN THE BANKING INDUSTRY

INTRODUCTION

The growth of digital banking usage, the emergence of new technologies, the indistinct ?of industry ecosystems and an amplified focus on innovation are creating encounters and prospects in banking. Consumers are more and more turning to fintech solutions and big tech platforms, disintegrating existing relationships for essential financial services, such as deposits, loans, payments and investments. The importance of developing and arranging new digital services, building new business models, and transforming from a product-centric to customer-centric culture should be the focus for all banks. These initiatives will not be long-term objectives, it has to be skillfully done at digital speed and scale. Recent upsurges in digital banking acceptance and utilization have profited neobanks, product specialist fintech firms, and large big tech platforms. While the preference for digital-first solutions still is stronger for younger demographic segments, the increasing use of alternative financial organizations as a ‘primary financial institution’ should be a concern for all traditional banks.

A remarkable?inclination towards the craving by?organizations that can integrate multiple financial solutions within a single platform, with a higher level of personalization than is evident at most financial institutions today. As the diversification of financial product portfolios across multiple organizations continues, the need to leverage modern technologies becomes even greater. While the pandemic served to escalate the investment in technologies supporting digital banking transformation, most of these investments were fragmented without an overarching plan for execution. As a result, the success of these investments was often uneven. A research?done by Deloitte, observed that almost 89% of financial institutions globally revealed?their organizations had?not fully modernized their core as?there are significant challenges adopting new technologies though aware that??with each major technology needed to succeed in the future. It is disheartening that more?organizations are facing difficulties deploying artificial intelligence (AI) despite an influx of solution providers available to assist.

One of the key reasons for the challenges in installing advanced technologies is the difficulty in finding and developing a more modernized workforce which was confirmed by the Deloitte research which revealed ?that four in ten financial institution executives said their workforce was not yet ready to adapt, reskill or take on new roles, while hiring new employees with niche technical abilities is harder than ever. In many cases, organizations have partnered with third-party providers to assist in upskilling internal teams. To become future-ready, financial institutions will need to deploy modern technologies to support agility, efficiency, security and innovation. Technologies such as intelligent decisioning, open banking APIs, cloud computing, robotics and automation, embedded solutions, and cybersecurity will differentiate banks and credit unions in 2022 and beyond. In each technology deployment, the focus must be to upraise digital customer experiences at speed and scale.

NEED FOR PROCESS AUTOMATION DEVELOPED RPA TECHNOLOGY

Process automation in banking plays a critical role in today’s digital transformation technology stack in order to serve customers in a very easy and convenient ways proving a new customer experience. Robotic Process Automation (RPA) technology has emerged as a consensus means to make available banking process automation. Some of the key factors that drive adoption of RPA solutions is its ability to improve process quality, speed, and productivity. Further, COVID-19 and its aftermath have increased the interest in RPA across many verticals.?Indian banks have been early adopters of RPA, benefitting from productivity gains, higher accuracy and cost-efficiency

??The embracing of Robotic Process Automation (RPA) technology in banking in their core areas of business operation is widely expanding as if at the speed of light as it is demanded by customer as a basic service and this will decide the competitiveness of the global bank.??Fortune Business insights forecasted?an?opportunity of $6.81 billion?in RPA business?by year 2026 which is supported by the world leading experts and observers in view of rapid rate of ?intensification in the market size of?RPA technology. Gartner predicts the same as $2.40 billion by the end of current year 2022 and also ?forecasts that ?the RPA market will grow at double digit rates through 2024 despite economic pressures from the pandemic. However, Forrester’s RPA trends and forecasts, the market for robots in knowledge-work processes would be at ?$2.9 billion by 2021 itself.

?Now RPA has turned out as ?an essential means ?for ?the most businesses, including banks. The banking industry is passing through a rapid turmoil emanated ?by the global COVID 19 pandemic and which crippled the entire global economy along with uncertainty and instability. To mitigate the damage of human lives and livelihoods amidst the COVID-19 pandemic, banks are proactively identifying all the possible ways to prune down cost and drive revenue growth. Thus, we may say RPA in banking industry proving to be a key enabler of digital transformation. It promises to replace repetitive, rule-based, mundane, manual digital tasks with software robots. It also ensures organizations to make their operational processes error-free.

?RPA OTHERS SIGNIFICANT USES EXPLAINED IN DETAILS

?RPA enables increased ?‘automating’ and enabling businesses to automate at scale and to thrive , there is a prerequisite for a breed of no-code SaaS platforms that help in creating useful?RPA solutions?faster.?Low-code platforms use a visual and intuitive approach to development. This can be used to automate tasks, end-to-end processes and workflows. One of the biggest advantages is that with a simple drag and drop, it creates an intuitive interface.

?While finance and accounting remain some of the top use cases for RPA services, process improvements are slated to spread faster into other business uses. From streamlining customer service with automation to automating transactional sales tasks to managing HR processes from end-to-end, there will be a surge in RPA use cases across business functions and industries. As RPA competences progress, so does the need to integrate it with other technologies to build on this strength. This means RPA will be integrated with other tools and technologies with tighter alignment between complementary use cases. For instance, integrating process mining, RPA, and AI disciplines like computer vision. In the aftermath of the pandemic, small and medium enterprises(SMEs) have realized the importance of process automation for their businesses to stay competitive and resilient. During a global survey by Deloitte that interviewed executives, 73% of respondents said that their organizations have embarked on a path to Intelligent automation. In the coming years, SMEs will continue to adopt RPA solutions at a faster pace to streamline their processes and become more efficient.?

?Everything “as a Service “model has a ?wide acceptance and adoption with organizations opting for SaaS, ITaaS, PaaS and other services. Banking on the huge popularity and broad use cases of RPA, many automation system integrators will launch the RPA as a Service (RPAaaS) model. As witnessed in 2020, organizations using SaaS were able to innovate faster to thrive the disruption without extra costs or efforts. The same principle can be applied for RPAaaS. For instance,?RPA as a service was leveraged by Nasdaq?across its finance operations to increase productivity, efficiency, save money and time. It also mitigates risks and manages compliance.

The global RPA industry has made huge advances in 2020-2021. 2022 might just prove to be the game-changer for RPA where it expands into newer terrains adds new capabilities. Automation will continue to strengthen its position as a must-have enterprise technology with RPA at its heart.

RPA Centre of Excellence(CoE) is a core central team that is in charge for?implementing RPA. The RPA CoE may comprise IT experts,RPA consultants, process managers, functional experts representing various teams. The role of this CoE is to establish a governance model, best practices and expertise to optimize the return on investment.?Establishing an RPA CoE has multiple benefits like improving the efficiency of the bot development cycle and integrating RPA with IT.?It also provides RPA training, service and support.

Semantic automation charts a different course from a rules-based approach where robots learn simply by observing an activity or task and emulate it without detailed instructions. Using semantic automation, bots can understand processes, the data that is required and move the pieces required to complete the workflow. Developers or business users will simply have to ask robots to perform a task or workflow. It is all set to revolutionize?RPA solution to make developers efficient and business scalable.

?Some of the early adopters of RPA?with a sophisticated automation program will wipe out the competition. However, to attain this state, enterprises must create a framework to design, execute and govern a hybrid workforce. In fact, Forrester predicts that five percent of the Fortune 500 will adopt this level of automation to fuel?extreme innovation.

According to McKinsey, roughly half of all existing work activities could be automated in the next few decades, as next-level process automation and virtualization become more commonplace. “By 2025, more than 50 billion devices will be connected to the Internet of Things (IoT),” McKinsey predicts. Robots, automation, 3D-printing, and more will generate around 79.4 zettabytes of data per year. This equates to opportunities for greater efficiencies and enhanced data for improved decisioning process automation tools such as robotic process automation (RPA) and digital process automation (DPA) will continue to enjoy healthy growth in 2022 as financial institutions realize the benefits beyond improved efficiency.

APPLICATION OF RPA?IN BANKING

While complete automation is still being explored ?but by partial and targeted automations using RPA, if applied for the right use cases in banking operations, can bring ?substantial value quickly and at a low cost.

There are an array of RPA use cases in banking highlighting some of the most rewarding outcomes as below:

1. Alternate Contact Center for basic customer service

Government has ordered complete lockdown of mobility for a long period ??except for essential services, banking services also comes in this category. The customer calls traffic to call center or branch have congested the networks, and delayed response for any information by the customers became a necessity to create an alternative channel. Intelligent Automation (IA)?integration with RPA and artificial intelligence to empower end-to-end processes and accelerate digital initiatives. The augmentation of ?RPA with AI expand the possibilities of business process automation to cover almost any scenario. Cognitive bots learn continuously from data and make decisions, becoming valuable members of its ?hybrid workforce.

?The Bots Or chatbots or virtual ?assistant, etc has been developed by adoption of RPA technology which are able to ?handling a significant portion of this traffic which requires no financial transactional but some basic information of routine types related to account statements and transactions, and queries which requires human intelligence for making decision are escalated to appropriate knowledge experts. It is now become a permanent medium as its importance is not limited to pandemic period. This has been implemented?by banks successfully, however quality of creating customer experience differs. Soon, it will soon replace customer care center modelled on this technology.

?2. Documentary Trade Finance Related Operations

Banks have leveraged ?RPA solutions to scale-up their trade finance operations and improve their presence in the financial supply chain. A leading bank in India already using ?RPA for automating processes related to issuing, managing, and closing letters of credit – the most preferred trade finance instrument. The automation enabled by?RPA Bots improves the total turnaround time by 70%, enhances process visibility by 80%, and delivers a 50% reduction in operational costs. But, it requires suitable?software development and investment in it to make it possible. It can be possible by augmented RPA technology based on machine learning.?

?3. Customer Onboarding

The customer onboarding process for banks is highly discouraging, primarily due to manual verifications of several identity documents. Know-Your-Customer (KYC), an integral part of the orienting and training process, involves significant operational hard work for such document validations. “Consumers want to stay within an app to research, engage, buy and share experiences.”

As per the recent survey conducted by Thomson Reuters, the cost of running KYC compliance and customer due diligence can be significant, ranging from US$52 million a year (for a bank) to about ?US$384 million.The new built KYC solutions that combine RPA with computer vision (CV) and intelligent optical character recognition (OCR) to abstract relevant information and validate identity as provided by the customer in the application form. The automation not only helps in eradicating manual errors but also saves significant time and effort for the back-office operations team.

4. Anti-money Laundering (AML)

?One of the best examples of RPA in banking is the automation of the complete AML investigation process. The process is highly manual and takes anywhere between 30 to 40 minutes for investigating a single case depending upon the complexity and availability of information in various systems. These repetitive and rules-based tasks can be easily automated with RPA, enabling more than a 60% reduction in process turnaround time.

5. Bank Guarantee Closures

This is a very specific yet highly relevant RPA use case for many banks. The bank guarantee closure process ideally requires a team of knowledge workers to manually record the data between multiple disconnected legacy systems and identify bank guarantees due for closure/termination/discharge. The generation and distribution of notice letters and execution of reversals/closures are also done manually. Besides, there are several manual verifications at each stage that deplete the overall productivity. RPA can be used to successfully automate the complete process. Some leading bank in India has already successfully implemented RPA Bots to automate the entire bank guarantee closure process achieving faster customer communication and a 45% reduction in process handling time.?

6. Bank Reconciliation Process

The bank reconciliation process is highly time-intensive requiring knowledge workers to manually find a huge amount of transactional data involving multiple banks and balance the final figures. RPA Bots can be programmed to replace manual efforts with several rules-based automations, including verifying each payment entry against bank data and other records. If the entries are matched, the records are reconciled. However, in case of any discrepancies, the Bots can send the records for further verification.

7. Loan Application Processing

The loan application process is a very good automation candidate for banks as well as financial institutions. Generally, documents for loan and appraisal requests are received in the form of bundled PDFs via emails. Data extraction from applications and its verification against multiple identity documents and assessment of creditworthiness are some of the key manual tasks. RPA Bots with artificial intelligence (AI) capabilities can be leveraged for intelligent data extraction and automating a range of these manual tasks. Check the following demo video on the?RPA Platform being used for loan origination process automation.?Smart Bots with native AI and machine learning (ML) capabilities are deployed to automate several manual operations involved in the loan application process.?Text classification and entity recognition –?Bots read emails and intelligently classify and assign them to respective agents.?Data extraction from loan/appraisal documents using natively embedded computer vision and human-bot work orchestration capabilities.??Fraud propensity detection using predictive ML models.

?8. Automated Report Generation

Many banks and financial services providers are utilizing RPA to automate manual tasks involved in report generation and are able to realize an immediate return on investment (RoI). Automating the report generation process includes a range of activities such as optimizing data extraction from both internal and external systems, standardizing the process of data aggregation, developing templates for reporting, review, and reconciliation of reports.

9. Account Closure Processing

The end-to-end account closure activity involves a range of manual tasks such as checking documents’ availability in the bank’s records, sending emails to clients and branch managers, and updating the data in the system. RPA Bots can automate all of these manual tasks so that the knowledge workers can focus more on productive operations.

10. Credit Card Application Processing

RPA-enabled automation for credit card application processing is another use case where banks have seen phenomenal results. RPA allows for the issuance of a credit card to customers within hours. RPA Bots can navigate through multiple systems with ease, validate the data, conduct several rules-based background checks, and decide to approve or disapprove the application. Many leading banks have already started to re-strategize their operational models to leverage automation-led disruption and?RPA is one of the key technology enablers?in the current situation.

11. Intelligent Decisioning and Communication

?As opposed to simply producing reports, data, intelligence and analytics must be used to identify opportunities, facilitate innovation, refine decisions and support what’s happening across the organization, why it happened and what will happen next. This enables employees to take actions that can improve back-office operations, reduce costs, save time, improve customer service, loyalty and profits. This can be done faster than ever before, providing flexibility and agility during times contextual communications. AI and advanced analytic algorithms can illustrate of uncertainty. Proactive and dynamic recommendations can also be delivered, at scale and in real-time. Beyond outbound communications, the use of data, AI and applied analytics can facilitate customer access to financial tools, advice, and embedded solutions that can improve trust and differentiate a brand by empowering the customer to partner on their financial wellness journey. This level of sharing also can assist in protecting the customers’ privacy and security.

12. Adoption of advanced software solution Cloud

The majority of banking and financial services organizations have yet to deploy core systems to the cloud due to significant complexity and concerns over security, risk, governance and control. In fact, according to a?2020 IBM banking on open hybrid multi cloud?survey, “While 91% of financial institutions are actively using cloud services today (or plan to in the next nine months), only 9% of mission-critical regulated banking workloads have shifted to a public cloud environment.” This presents a significant opportunity gap. To address the need for capacity and speed, banks and credit unions must look to cloud computing solutions to store data and support applied analytics. The result is increased customer insights, improved efficiency, enhanced innovation, greater agility, and a reduced risk of security or business continuity breaches. As an overarching organizational advantage, cloud solutions can augment human productivity, providing insights that can positively impact both front-office and back-office transformation.

Cloud Computing = Flexibility + Agility + Scalability: cloud-based infrastructure can help banking organizations react to marketplace changes in an instant.

.IBM rightly said , “Organizations have an enormous opportunity to leverage cloud computing to drive innovation and improve their competitive position. Cloud computing – whether private, hybrid or public – enables organizations to be far more agile while reducing IT costs and operational expenses. In addition, cloud models enable organizations to embrace the digital transformation necessary to remain competitive in the future.”

. Expansion of Open Banking APIs

Open banking has become one of the major drivers of digital banking transformation, impacting technology and infrastructure investments, data modernization and decentralization strategies, fintech partnerships, and even reskilling programs. The primary beneficiary of these efforts will be the consumer. To prepare for this shift in the way banking will be done moving forward, banks and credit unions must determine the most appropriate business model that will meet their future business objectives. Then institutions must assess the capabilities required to deploy against the model selected and build partnerships with third party providers to make the strategy successful. 85% of financial institutions believe the greatest impact of open banking will occur in the next 5 years. For some institutions, the decision may be to build a banking-as-a-platform (BaaP) model or a banking-as-a-service (BaaS) model to open doors for selling products and services to an expanded prospect universe. Open banking also provides the opportunity to streamline and automate back-office processes, build a stronger innovation culture and improve customer retention.

14. Increased Focus on Cybersecurity

Cyber threats have dire immediate financial consequences and threaten both the reputation and future business prospects for financial institutions. Security breaches can come from anywhere inside or outside the organization, with the use of mobile technologies and online data transmission creating increased threats of hacker attacks.

While cyber attacks increased significantly during the early days of the pandemic, the real damage occurred as financial institutions hurried to implement remote working and doubled down on digital banking transformation initiatives. Once-in-a-decade breaches (SolarWinds, Colonial Pipeline, Verkada, JBS foods, Kaseya) hit almost every news cycle. The importance of protecting customer information and critical infrastructure from cyber threats is only getting more urgent, while also becoming more difficult to counter. One major trend that may gain traction will be the elimination of passwords. Humans are not prepared to generate and remember dozens (or hundreds) of unique combinations of characters that don’t resemble any spoken language. Authenticator apps, Windows Hello, and SSO solutions are all reducing the need for passwords. Recently, Microsoft has allowed users to go passwordless by using their Authenticator app. While this won’t stop cyber criminals, it will certainly provide an added layer or protection as biomentrics are increasingly used.

CONCLUSION

List of Top Key Players in Robotic Process Automation (RPA) Market Report Are: -

● Automation Anywhere (U.S.)

● Blue Prism (U.K.)

● Celaton Ltd (U.K.)

● Ipsoft (U.S.)

● Nice Systems Ltd. (Israel)

● Pegasystems (U.S.)

● Redwood Software (U.S.)

● Uipath (Romania)

● Verint (U.S.)

● Xerox Corporation (U.S.)

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Robotic Process Automation (RPA) Market by Applications:

● BFSI

● Healthcare and Pharmaceuticals

● Manufacturing and Logistics

● IT and Telecommunication

● Retail

● Travel

● Hospitality

● Transportation

● Others

Robotic Process Automation (RPA) Market by Types:

● Automated Solution

● Decision Support And Management Solution

● Interaction Solution

Robotic Process Automation (RPA) Market report provides comprehensive analysis of

● Key market segments and sub-segments

● Evolving market trends and dynamics

● Changing supply and demand scenarios

● Quantifying Robotic Process Automation (RPA) market opportunities through market sizing and market forecasting

● Tracking current trends/opportunities/challenges

● Competitive insights

● Opportunity mapping in terms of technological breakthroughs

We may see that RPA is very cost competing tools and quicker customer service delivery swiftly and error free. The future of this technology is tremendous. ?