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Cognitive RPA the Future of Automation January 2019 Foreword 2

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Cognitive RPA The Future of Automation January 2019 Foreword 2 The NASSCOM Research report titled “Cognitive RPA – The Future of Automation” aims to highlight the state of Robotic Process Automation (RPA) and how it would evolve with advancements in cognitive technologies. In this report we have presented the trends and drivers that are shaping-up RPA growth, and have covered use cases of RPA across various business functions and sectors. In addition, we have also showcased RPA solutions offered by various IT-BPM firms and enterprises in India. Hope you enjoy reading this report. Debjani Ghosh President, NASSCOM Acknowledgement This report has been developed by NASSCOM Research through a comprehensive study to understand the RPA landscape in India. The preparation of this report has been possible with support from various information sources including market insights from representatives from different IT-BPM, GCC firms and enterprises in India who have extended great help to the research team. We wish to sincerely thank all of them for their valuable contributions without which this report would not have been possible. NASSCOM NASSCOM Rakesh Kumar Kshitiz Arora Director - Research Sr. Manager - Research Table of contents Objective of the Report 04 Research Methodology 05 Executive Summary 06 RPA Landscape 07 Case Studies 26 Appendix 41 Objective of the report 4 Highlight key business functions and sectors with highest RPA adoption Explore the evolution and impact of Identify key market trends and drivers cognitive technologies on current RPA solutions To develop an understanding of Present case studies highlighting RPA landscape RPA innovations and use cases Research Methodology 5 Desk-based research across databases, reports, Interviews with industry publications and news experts articles NASSCOM Analysis RPA case studies from the IT-BPM firms and enterprises Executive Summary 6 Global RPA software RPA finds highest RPA adoption is driven Enterprises are moving With advancements in and services market is adoption in BFSI and by factors such as cost from experimentation cognitive technologies expected to grow BPM sectors, and in reduction, stage to early adoption RPA would be able to 29% (CAGR) between Finance & Accounting high accuracy, with a focus on adding handle end-to-end task 2017-21 to reach and Contact Centre 24/7 availability, and cognitive components automation with real- USD 1.2 billion functions revenue enhancement to RPA solutions time exceptions Introduction to Robotic Process Automation 7 RPA is the technology that allows enterprises to configure computer software, or a “software robot” that automates human activities, partially or fully Structured data Rule- No / minimal based human intervention Low complexity tasks High Repetitive volume Key Features RPA Bot: A software robot is located on virtual / physical client environment where it interacts with various business applications 8 Detailed code / instructions that Developer Tools replicate human steps Houses robots in virtual / Assign jobs to robots physical client environment and monitor their activities Robot Controller Client Environment Store code/instructions Review and resolve any exceptions or Business Users Applications escalations Robots interact with range of enterprise applications Source: Deloitte RPA has advanced significantly over the years and is now becoming more mainstream 9 Hype Cycle for Artificial Intelligence, 2018 Prescriptive Analytics Deep Neural Nets (Deep Learning) Graph Analytics VPA-Enabled Wireless Speakers Digital Ethics Intelligent Applications Machine Learning Conversational User Interfaces NLP Smart Robots Robotic Process Automation Software Deep Neural Network ASICs Virtual Assistants AI PaaS Cognitive Computing Chatbots FPGA Accelerators Natural-Language Generation Speech Recognition Human-in-the-Loop Computer Vision Plateau will be reached: Ensemble Learning Crowdsourcing Predictive Analytics AI-Related C&SI Services Autonomous Vehicles Less than 2 years Neuromorphic Hardware GPU Accelerators 2 to 5 years Knowledge Graphs Commercial UAVs (Drones) AI Developer Toolkits 5 to 10 years Expectations Virtual Reality Artificial General Intelligence More than 10 years Knowledge Management Tools AI Governance Augmented Reality As of July 2018 Peak of Innovation Trough of Slope of Plateau of Inflated trigger Expectations Disillusionment Enlightenment Productivity Time • RPA solutions are being implemented by an increasing number of enterprises, resulting in becoming more mainstream and moving further along the curve • With introduction of AI / cognitive technologies such as ML, NLP, etc., RPA is expected to gain further traction Source: Gartner Enterprises have adopted RPA for large-scale and multi-process use case implementations 10 HR • Candidate management Finance and Accounting • Recruitment • Accounts receivable • Payroll • Accounts payable • General ledger IT • Monitor infrastructure/ application • File and folder management Web-based Procurement • Fill forms • Scrap screen • Invoice processing Contact Center • Website testing • Inventory management • Customer data • PO processing management • Contact processing RPA has evolved from being a cost reduction measure to a revenue enhancement tool… 11 RPA Advantage Ability to respond to growth Track and monitor all Reduced operational cost events (e.g. organic, Reduced operational Operate autonomously automated tasks and capture beyond labor arbitrage; acquisitive) with speed, errors and better 24x7, driving real-time related data which can be Rapid return on agility and resiliency with regulatory compliance transactions analyzed to make better investment little IT expertise business decisions Cost reduction Scalability Quality and compliance 24/7 Availability Improved data analytics Employee and customer Value focused talent Revenue enhancement Speed to value and low risk satisfaction Increased employee Shift in priorities towards Quick time to delivery, avoids satisfaction through focus Shorter cycle time to service innovation, strategy and invasive traditional system on higher value activities customers resulting in other business integration; Implemented in and eventually more increased revenue growth development activities weeks or months, not years satisfied customers …and is now considered as an enabler for value-centric drivers such as compliance, analytics, etc. 12 Trends Increasing number of enterprises across different industries are adopting RPA for large-scale and multi-process use case implementations There has seen a shift from cost reduction as an enabler for value-centric drivers such as compliance, shorter cycle times, autonomous processing, etc. Increased verticalization, as process agnostic RPA tools are evolving into industry-, process- and platform-specific solutions Enterprises are moving from experimentation stage to early adoption with a focus on adding cognitive component to RPA solutions RPA service providers started combining RPA tools with AI and analytics engines to offer intelligent automation solutions RPA adoption is further driven by their quick deployment without disrupting the existing legacy systems 13 Drivers Self-sufficient & sustainable Software robots operate in self- managing, self-diagnostic, self-healing and self-sustainable mode Quick payback on RPA investments Headcount savings from RPA range from 10-25% Reliable and accurate RPA error rates are almost zero and processes are compliant, secure and Easy transition easier to audit RPA transition requires low levels of investment and can delay replacement of legacy IT Systems Improved customer experience RPA enables employees to focus on more valuable, productive and customer facing roles, thus translating better Faster deployments customer experience Proof of value can be delivered within 3-6 weeks and takes 3-4 months for deployment With technological advancements software robots would be able to create and manage robots to handle variations in the workload 14 Market prevalence RPA 4.0 Cognitive RPA High Low • Cloud, on-premises and hybrid deployment RPA 3.0 Autonomous RPA • Enhanced automation with capability to develop and manage robots • Cloud, on-premises and • RPA integrated with AI RPA 2.0 hybrid deployment technologies such as ML, Unassisted RPA • End-to-end task NLP, text analytics, BusinessImpact automation with real-time computer vision RPA 1.0 • Server (VM) deployment exception handling Assisted RPA • End-to-end task • Scalable and flexible virtual automation workers • Workstation deployment • Scalable virtual workers • Limited automation • Limited scalability Technology Advancements Source: Everest Group Banking, financial services and insurance companies have been the early adopters of RPA, driven primarily by revenue and cost pressures 15 Illustrative Banking and Financial Services Manufacturing • Credit underwriting • Bill of material generation • Fraud discovery • Vendor data management Insurance Healthcare • Claim adjudication • Report automation • Claim processing • System reconciliation Telecom Retail / e-commerce • Bill generation / invoicing • Fare audit • SLA monitoring • Passenger revenue accounting BPO Public Sector • Management reporting • Audit intelligence systems • Data management • Tax calculation Global RPA software and services market is expected to reach USD 1.2 billion, growing at 29% CAGR between 2017-21 16 Global RPA Software and Services Market, 2016-21, USD million RPA Software RPA Services • Americas (~46%) accounts for highest RPA adoption,
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