How can Financial Institutions Achieve Optimal Customer Experience during & after Covid – 19?

Over a last couple of months, we have been witnessing an overwhelming humanitarian crisis unfold.

A crisis, likes of which the world has not seen in the modern digital world. The analysts globally are quick to acknowledge the detrimental impact this event may potentially have on the world economy. According to a report by McKinsey, countries across the globe are staring at GDP degrowth of 6 to 12% and for most a countries recovery is estimated to happen not before 2021 Q2. At the ground level, people’s ability to pay bills and their loans on time will get impacted

Amidst extended global lockdowns aimed at stopping further spread of the virus, economic activities are severely impacted at an unprecedented scale. We all do see an array of prompt and proportional response to the impending economic crisis at all levels: the governments are infusing Trillions of $s worth bailout packages, the federal reserve are reducing their target rates / guidance values, the regulators are offering leniency to the lenders / banks in terms of reporting delinquent debts.

In this time of dire need, a measured response from the lenders is going to define lenders’ relationships with their customers and can potentially generate a lifetime of loyalty.

Governments across the world are issuing relief packages e.g. CARES Act (approved by US congress) that aim to provide timebound protection against foreclosures action and offer right to forbearance for federally backed Mortgages and Student loans. Reacting to the situation, many lenders have declared that they would work constructively with the borrowers to assign suitable assistance programs based on specific needs. While this is a great gesture, a few operational challenges lay ahead of them:

Given these daunting challenges how can lenders convert a potentially adverse situation into customer delight?

Customer needs, A good place to start!

As a side effect of this disastrous event, people’s earning capacities will be impacted. However, this is unlike any other situation that we have witnessed in past, both in terms of severity and proportions.

To be able to assign a suitable assistance program, lending institutions need to first look at broad segmentation based on the magnitude of impact on their earning capacities. Here’s an example of segmentation based on industries where customer is employed and the amount of time it will take to bounce back for pre-Covid-19 times:

Engage customers and offer right assistance program

Identifying the customer segmentation is the first step in the right direction to offer personalized help to the borrowers. Once an incumbent account is segmented, the assignment of assistance program can be done based on the alignment of the internal business and legal teams.

A sample segmentation and their program assignment is illustrated in the table below

Customer Segment Past Behavioral / Propensity Score Past Credit Risk Assistance Required Industry Risk Recommended Remedial Action
Segment 1 High Low During the lockdown period Low Deferred payment, Fee waivers etc.
Segment 2 High Low 0 – 6 Months Medium Moratorium, Deferred Payments / Payment plan
Segment 3 High / Medium Medium / Low 1 year of longer High Restructure / Go through regular collection process
Segment 4 Low High NA NA Go through regular collection process

Looking to Artificial Intelligence (AI) to rescue

Correct Identification of such customer profiles requires evaluating a large number both traditional and nontraditional user attributes. In addition, it is fair to assume that there will be large volumes of such requests coming in. Processing all such request manually is going to be humanly impossible.

As shown above, propensity to pay (behavioral score) is an important element in recommending the right remedial actions, especially for the customer segments 1, 2 and 3. Traditional risk models, are incapable of sifting through the Giga bytes of unstructured data and extract the behavioral profiles of the customers.

Advanced text analytics and machine learning techniques have proved to be highly effective in evaluating and quantifying qualitative aspect as such. Swift assignment of appropriate programs to assist the borrowers in this time of need will enable lenders to build a strong and lasting bond with their customers

Accurate risk segmentations using AI models can also benefit lenders and collection agencies in identifying self-cure customers, who form the large part of the delinquent portfolio. This allows the call calories to be directed to the riskier account and result in higher resolution of more difficult accounts. Furthermore, advanced text analytics techniques can automatically pick important follow-up actions that an operator may forget to note due to the pressure of handling spike in inbound call traffic.

FinXEdge offers a suite of AI based business applications that are specifically built to solve the problems mentioned in this blog. Download our whitepaper to understand how to collect effectively without affecting the customer experience, by embracing AI

For more details visit – or schedule a consult to engage with an expert (Link –

Enterprise Personal Bots in The Education Space — How Can Enterprise Personal Bots Transform the Education Space?


An interesting version of the personal bot that we have talked about earlier is the Enterprise Personal Bot1, which is a type of personal bot that can be used in an enterprise scenario to automate various repetitive tasks. Unlike the regular personal bot, in this version, the enterprise controls the definition, i.e., centralized configuration, and the individual controls the execution on-demand, i.e., distributed execution. While most sectors would benefit from this version of the personal bots, one of the areas where we can see significant potential benefits is the education sector. In the education sector, time, funds, and resources are usually very limited. Many of the activities that teachers, professors, or administrative users execute are repetitive tasks that take up a considerable amount of time and effort, thereby steering them away from focusing on actual learning-related activities. Imagine if an Enterprise Personal Bot could take up all these manual, repetitive tasks, freeing the staff to spend time on using their creativity in designing the course materials, and imparting knowledge.

Use cases of Enterprise Personal Bots in Education

Let’s look at a few of the possible use cases of EPBs that can be introduced in the Education sector:

Assisting an Administrator

The Enterprise Personal Bot could work as a perfect assistant to an educational administrator who is flooded with repetitive work on a day-to-day basis. All administrators in a university or an academic institute perform activities like — accepting applications, and sending email receipts for the same, filling forms, receiving tuition fees, answering repetitive questions and providing admission.

Enterprise Personal Bots for each of these activities could be centrally created and managed for the use of all the administrators in the institution. From time to time, each administrator could then provide personalized inputs wherever required in each of these activities. The EPB could be configured with a standard set of answers to help the administrators provide quick replies to hundreds of similar questions regarding:

Having an EPB would, therefore, help substantially reduce the time, cost, and effort of the administrator and free him/her from performing repetitive tasks to executing something more meaningful for the organization.

Efficient Teaching Assistants

The shortage of teachers is real in the world2 and is only getting worse3 with passing time. Apart from memorizing lessons and staying updated on new curriculums and standards, teachers end up spending a considerable amount of time on repetitive student queries, taking attendance for every class and routine grading, thereby making their schedules extremely hectic.

Enterprise Personal Bots could be designed to answer frequent questions on lessons, deadlines, and curriculums. EPBs could also assist teachers in the various repetitive data entry and data review kind of activities. The other significant support that teachers could get from EPBs with Intelligent AI capabilities is in grading student assignments and essays. Whether we’re looking at a high school class with 40 students per class or an open university course where hundreds of students would submit assignments, teachers spend hours of their time individually assessing, grading, and then providing feedback to each of the students. It is an extremely slow and repetitive effort. Instead, an EPB with Machine Learning and AI capabilities could significantly help the grading and feedback mechanism. ML models could be provided with test data and be trained to grade papers and offer feedback. In some instances of low confidence, individual teachers could then intervene to complete the task.

Thus, having an EPB at their disposal would allow teachers to concentrate on establishing a stronger relationship with students, providing them with personal guidance, and helping enhance the curriculum with their interests. This way, teachers can be relieved of their hectic schedules that have increased the problem of teacher shortage and make their position more appealing to others considering becoming teachers. This would enable the existing teaching fraternity to provide more and improved mentorship.

Assistance to Students

EPBs could be of much assistance to students in an institutional setup. They could provide students with all the necessary information about their courses, modules, faculties, and facilities. The EPBs configured on the campus could act as campus guides and help the students as they arrive at the university/school. They would help find more information about the hostel facilities, scholarships, curriculums, schedules, and library memberships, thus not only saving the students’ time but also reducing the burden of the institutions in responding to repetitive questions.

An EPB would be a great addition in a library where it could be configured to help the students with well-curated information for different topics. This would save a lot of time for students, where they could avoid going through multiple websites, various searches as well as huge volumes of books to pull out the required information. Also, as the students interact with them, EPBs could collect a vast amount of data from the students. This data includes information about students’ search preferences and their behavior on the information that they cannot find. This could act as a feedback mechanism for the EPB, and it could utilize this data to track the students’ queries and then identify the areas where it needs to improve. EPBs could also help students in assignments as well as project work. For instance, during project work where a simulation or processing needs to run time and again with different data points, EPB could do the processing for the students and therefore come very handy and save time.

Feedback is an essential mechanism for improving the learning process. Just as teachers’ feedback is vital for students to identify points of improvement, the students’ feedback provides an opportunity for the teachers to identify gaps in their teaching. An EPB could be configured to analyze the feedback, compile the points mentioned by the students, and send them to the respective teachers. Thus, we can see how handy an EPB can be in assisting the students.

Assistance during Exams

Enterprise Personal Bots could be configured in systems with grading criteria for different questions in different exams. While exams are taken by students on these systems, the EPB could authenticate and authorize the students and then immediately mark the students based on the answers they are providing. They would grade the students based on the configurations done and park the answers where the teacher needs to provide manual intervention.

EPB could also be used to help in data analytics to understand and interpret the exam/test results in a meaningful manner, i.e., whether the paper was hard, which questions in which category could be answered or not, and so on. Furthermore, an EPB could also be used to email the report cards to the students and guardians as well as upload the results of the students on the university website. Thus, having an EPB assist during exams would save a lot of time and effort in authorizing, grading, classifying, and delivery of the results for an examination.

Cautions while implementing Enterprise Personal Bots in Education

As with any technology, Enterprise Personal Bots come with their cautions and challenges. And as with any sector, the Education sector is no exception to this rule. Since the EPB would be configured centrally with the execution controlled on-demand, ensuring the privacy and security of personnel data as well as student data is paramount. Also, since feedback and grading are fundamental functions that are going to be delivered by the Educational EPB, the EPB must be implemented with precision. Partnering with an experienced automation leader like EdgeVerve AssistEdge can help achieve this.

What Does the Future Hold for Enterprise Personal Bots in Education?

As seen in the different use cases above, we can see that the introduction of the Enterprise Personal Bots which combines the power of attended automation and personalization of intelligent bots with the control and discipline of the organization would be a big help in freeing up significant time and effort of the employees. Enterprise Personal Bots would play an important role in the revamping of the Educational space, with more cheerful teachers and administrators leading to happier students and better and more relevant learning.


Unlocking the potential of RPA through Complementary Technologies – Intelligent Document Processing

Robotic Process Automation (RPA) is the fastest-growing enterprise technology across industry segments, and its pace will continue to be substantial in 2020-21. It’s a style of automation where a software program mimics human actions to accomplish various tasks following a set sequence or flow. RPA is revolutionizing the way operations are run across the industry segments, be it Financial Services, Manufacturing, Logistics, or Healthcare. RPA robots can work 24*7, generating output with higher consistency and control, thus providing higher predictability in terms of outcomes. It has found its application across functional areas of the businesses, be it customer support, finance, HR, or purchase department. RPA helps take away the mundane and repetitive work from the human workforce, thus allowing them to focus more on the tasks which require human qualities like empathy and judgment.

Evolution of RPA

RPA has been around us in some shape or form since the 90s; initially, it was more a web scraping technology used for simple data extraction from web-pages. Later it obtained the elements of workflow embedded in it with the advancement of workflow technologies. In recent years with the emergence of Artificial Intelligence (AI) and Machine Learning (ML), RPA is moving to become more of a cognitive technology, which can not only mimic human actions but can also apply basic intelligence to deliver the results. Today, RPA has made rapid inroads into an organization’s technology roadmaps by virtue of being low code, easy to adopt, and faster to deliver technology solutions.

The emergence of Document Processing as a key force multiplier

As the adoption of RPA increased across industries, most of the organizations began piloting RPA projects in the areas where they already had legacy automation through Excel Macros or other older assisted automation technology. These RPA implementations helped them validate the compatibility of RPA technology within their organization setup. Post success of initial implementations, technology and operations teams moved quickly to identify more areas for RPA and started running multiple RPA processes across different functional areas, using core RPA capabilities of automating tasks.

Organizations across the globe still have many processes that involve the handling of documents, like Know Your Customer (KYC) in banking, claim processing in insurance or invoice processing in manufacturing. It was critical for the success of RPA that it go beyond automating the process, dealing with just interactions and data manipulation between multiple applications, and include the element of document processing.

As per Gartner’s latest report, by 2022, 80% of RPA-centric automation implementations will derive their value from complementary technologies. These complementary technologies include process mining, intelligent document processing (OCR, Computer Vision), Machine Learning & User experience. Gartner refers to the collective functionality as “Complemented RPA” (CoRPA).

Out of these complementary technologies, one of the fastest adaptations are in the area of Intelligent Document Processing. When it comes to converting documents into a machine-readable format, Optical Character Recognition (OCR) is the answer. OCR refers to the process of converting different types of data, including PDF files, printed documents, or images into editable, accessible, and searchable formats for computers. OCR can help in reading bank statements, purchase agreements, or any other business document and deliver it in a machine-readable format for consumption by another software like RPA.

The integration of Artificial Intelligence (AI) and Machine learning (ML) in OCR has resulted in the emergence of technologies such as Computer Vision, Intelligent Character Recognition (ICR) & Natural Language Processing (NLP). These new technologies contribute to making document processing more efficient and reliable. Now with intelligent document or image processing capabilities, RPA can extract information from any complex document which contains unstructured data, with a higher level of confidence in the output generated and then use it as an input for further processing. Organizations can easily automate processes involving documents like invoices\agreements\statements utilizing a combination of intelligent document processing tools and RPA to achieve end-to-end automation.

Let’s look at an example to understand the implementation better. A leading manufacturer works with multiple suppliers to source the input for its products. All the suppliers have entered into a contract with the manufacturer, which is then sent to the manufacturer’s purchasing department over emails (as PDF attachments). The purchase department has automated the process of inputting the contract key data from the contract into its SAP-based purchase management application. The organization has deployed Infosys Nia Computer Vision along with AssistEdge RPA Albie Decision Workbench to achieve this automation. As the contracts received from the suppliers are not in a standard format, Infosys Nia applies its computer vision capabilities to extract the key data elements from the contracts. Post data extraction, a confidence score is generated, which is pushed as input to AssistEdge RPA Albie bot. AssistEdge RPA Albie bot, based on the confidence model threshold, either sends the contract information directly to the SAP system or moves it to decision workbench as a task for the human worker to review and approve it to be fed into the SAP system. This brings in the element of “Human in Loop” in the automation, thus making it a more resilient and controlled implementation.

The above process creates a viable ecosystem for human-empowered automation, thereby helping the enterprise attain ‘Automation Singularity Led by Humans.’

Automation Singularity refers to a highly customer-centric and agile oriented state of constant improvement and optimization through the future workforce, opening an expanded horizon of possibilities. Human specialists drive customer orientation using their creativity and empathy and are complemented by digital workers with extreme productivity and consistency.

Thus, the future of RPA-driven automation lies in taking it beyond vanilla task-based implementation, to one incorporating human-empowered complementary technologies.



Computer Vision:

Gartner Predicts 2020: RPA Renaissance Driven by Morphing Offerings and Zeal for Operational Excellence

Automation Singularity:

Re-assessing your contracts with an AI based solution during COVID-19 Crisis

What began as whispers of a new deadly virus from Wuhan has now become a global crisis. On 11th March 2020, the World Health Organization declared COVID-19 a pandemic. As nations of the world are going into a lockdown and closing their borders, economic activity has come to a screeching halt. The COVID-19 Pandemic will cost the global economy trillions of dollars this year alone and that is just the tip of the iceberg. With supply chains drying up, the impact on business will be substantial and long lasting.

Due to this disruption, many companies are re-assessing their contracts to understand the extent of their rights, remedies and obligations with respect to their business partners. This pandemic has brought to fore a set of critical clauses related to force majeure, liability, insurance, and termination etc. that normally never go into effect until unforeseen circumstances as the world is experiencing now. This will result in multiple amendments and contract rescheduling that puts your business at risk. We ourselves are observing a lot of action in procurement contracts of late. Our contract review and analysis solution Nia Contracts Analysis is seeing a huge uptick in requests targeting clauses related to business continuity, force majeure, obligations, rights, liabilities. Businesses are looking for help in the areas of:

A common legal clause, but usually hidden in your contract documents, is the force majeure. It is not triggered until there is an unprecedented and extraordinary circumstance or event. It allows either party to limit their liability in the face of such an unforeseeable event (sometimes referred to an Act of God) that hampers their performance.

As a result of COVID-19, we are already seeing force majeure, non-performance, and termination rights clauses getting triggered across industries for procurement and sales contracts. However, force majeure isn’t restricted to pandemics and can be triggered during wildfires, floods, hurricanes, and other natural disasters or unprecedented events like terror attacks.

Assessing Risk in Contracts

One of the key questions facing business leaders today is the contractual risk that force majeure presents to their business. If a supplier invokes this clause, do they have a fallback option? What, if any, are potential remedies to non-performance? Is there a timeframe for avoiding cost overruns and losses? What are the other rights and obligations? Is there an impact on the cost? Is there an insurance component and if so, what is the process for filing claims? What happens if force majeure continues for an extended period of time?

Take for instance a car manufacturer who depends on an OEM for spark plugs. That OEM in turn depends on a supplier for materials. In the present situation, if the OEM invokes force majeure citing pandemic conditions and their inability to deliver spark plugs due to material shortage, the car manufacture’s business suffers. In this case the car manufacturer needs to review their contract to identify alternative means to perform contractual obligations or proactive steps that can be taken or enforce specific performance of contract.

So, if the reason force majeure is triggered is because the OEM is not able to get materials from the supplier, the car manufacturer can ask the OEM to look for another source of materials or renegotiate the terms of the contract if the parts have become expensive due to the shortage, or review alternative remedies to contain the business impact.

Another example is insurance. Do your contracts adequately cover losses arising out of another party’s inability to fulfil contractual obligations due to the pandemic? Do you have specialized insurance that covers business interruptions due to force majeure or trade disruption? Companies must quickly evaluate insurance contracts for specific terms and conditions to determine coverage and ensure they are filing the claims within required notice provisions.

For the sell side as well, the risks are high. To invoke the clause, specific force majeure events have to be explicitly mentioned in the contract, creating a grey area. Refusing to perform a contract, even during the COVID-19 crisis, without a valid legal reason comes with its own set of risks. Fulfilment has to be viewed as an impossible feat, and not just impractical – so fear of safety and raised prices do not qualify. If not legally sound, the refusal could see you burdened with substantial damages and loss of business due to potential termination for breach of contract.

Similarly, businesses need to undertake contract analysis to understand rights and obligations, liabilities, notice requirements, and analyzing potential causes of breach etc. There are many legal angles that need to be vetted and any oversight could come with a high cost.

Business contracts worth millions of dollars are not easy documents to navigate and are high risk ones. Apportioning the risk, getting the required intelligence by manually reviewing a large number of contracts quickly, creating appropriate amendments or deciding termination, suspending performance, or for that instance drafting a perfect contract manually can take months – time that businesses in the present situation just can’t afford to waste. And even then, the probability of human oversight is high.

Mitigate Contractual Risks like Force Majeure with Nia Contracts Analysis (CA)

Nia Contracts Analysis is an enterprise-grade AI offering that leverages advanced Machine Learning (ML) techniques such as vision, semantics, language sequence to help customers across industries to derive insights from their contracts and legal documents. Nia Contracts Analysis makes it easy for business, procurement, and legal teams to read and interpret the contract documents, navigating the complex hierarchy between the contracts, their sub-agreements, and related documents with ease.

Given the current crisis our clients are facing, we have created a Nia Contracts Analysis solution for them. It is backed by 500+ legal AI experts with deep industry domain expertise, and our advanced AI & ML technology stack. Nia Contracts Analysis can quickly and accurately digitize and identify all force majeure and related clauses in a contract, enabling our clients to take appropriate action/decisions to ensure business continuity. Nia Contracts Analysis performs AI based abstraction of key clauses across various contract types, capturing variations in language by simulating human cognitive functioning, performing various tasks with a combination of technology and human intervention.

We can help you identify and mitigate risks in your supplier contracts to ensure that you complete your contractual obligations by helping you:

Click here to take a look at our solution in action.

A Quick Round Up

Are you looking to understand the risk force majeure and other clauses in your contracts poses to your business? Click here to reach out to us and request a callback.

Evolving the Future of Enterprise with Hyperautomation

We are at a point in our civilization where the real impact lies in evolving the future, not just being a part of it. Counterintuitively, enterprises in a race to survive, struggle. Those looking to be at the bleeding edge of innovation, on the other hand, build a robust foundation for success. To this effect, automation, led by RPA, has become the most crucial growth lever. When combined with other smart technologies, automation is a tool to create unprecedented value across the enterprise, delivering creativity, efficiency, and intelligence at scale.

The focus on augmentation over incremental productivity gains is where we see the most significant shift in how enterprise approach automation. Topping Gartner’s list of the top technology trends for 2020 is the idea of hyperautomation, where augmentation is no longer optional, but essential to digital transformation initiatives. Gartner defines hyperautomation as the discipline that “deals with the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans. Hyperautomation extends across a range of tools that can be automated, but also refers to the sophistication of the automation (i.e., discover, analyze, design, automate, measure, monitor, reassess).”

Approaching automation as a holistic intelligence-driven exercise central to enterprise growth, creates a range of advantages. The rise of the digital twin, an idea that EdgeVerve has been bullish about, will be a defining moment as enterprises start to trade on imagination and hyper-personalization at scale. By combining the efficiency and accuracy of a digital worker with the empathy and creativity of human counterparts, the human-digital twin doesn’t just support decision-making, but could even help automate the process. At EdgeVerve, we believe that this concept will drive the future, and that’s why it is a critical component of our overarching solution design philosophy – Automation Singularity.

In a paper published last year, we defined Automation Singularity as “a highly customer-centric and agile oriented state of constant improvement and optimization through the future workforce, opening up an expanded horizon of possibilities. Human specialists drive customer orientation using their creativity and empathy and are complemented by digital workers with extreme productivity and consistency. Automation Singularity serves as a beacon for enterprises to conceive, design, structure, and deliver products and services. The idea of Automation Singularity is a journey where a variety of automations (including attended and unattended automation) along with AI capabilities will unleash unprecedented value touching every process, every employee, and every system in the enterprise.”

Our experience of working with large enterprises across the globe pointed us to the need for an enhanced vision of automation that drives expansion and profitability. By bringing human and evolved digital workers closer together than ever before, Automation Singularity creates a transformative blend of advanced capabilities to build the enterprise of the future. It is a journey that broadly comprises three stages – Deterministic Automation, Intelligent Automation, and Human-empowered Automation. As companies progress along this continuum, they will move from:

At EdgeVerve, we believe that our vision for Automation Singularity, including ideas like hyperautomation, signals the next era for enterprises. However, the quality of execution is every bit as important, perhaps even more than an understanding of the idea. Consequently, our model of the enterprise road to Automation Singularity features three key disciplines – Discover, Automate, and Orchestrate – ensuring maximum effectiveness at every stage of automation maturity. We drive this model through AssistEdge, our cohesive automation platform, and our consulting capabilities that allow us to create custom solutions for highly specific needs.

To reap the maximum benefits from their intelligent automation program, enterprises must be ready to evolve and adapt rapidly. Alignment with business needs, evidence of business impact, and scalability are critical for an enterprise-wide impact. Enterprises looking to thrive, not just survive, will lead this wave of change as we move into an era where extreme agility and seamless experience become the norm. Our white paper on Automation Singularity offers detail on how they can begin their journey, build on the idea of hyperautomation, and address areas such as people, technology, risk management, governance, and interoperability. Download the paper and get in touch with one of our experts to discuss your enterprise’s automation needs.

Why should Hyperautomation be your #1 Strategic Priority to Scale Automation?

The ultimate goal of technology should be to unobtrusively augment human potential – to give us the support and freedom to rise above the mundane and focus on more creative and strategic pursuits. These people-centric technologies are the cornerstone of the modern workplace and key enablers of the new ways of working. Automation is one such area that helped humans realize this objective. But task based automation isn’t nearly enough! And so, the new trend that’s topping the charts this year in Gartner’s ‘Top 10 Strategic Technology Trends for 2020’ is Hyperautomation.

Gartner defines Hyperautomation as “the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans. Hyperautomation extends across a range of tools that can be automated, but also refers to the sophistication of the automation (i.e., discover, analyze, design, automate, measure, monitor, reassess.)”

Think of it like an ecosystem of tools and technologies (such as RPA and AI) that are working together seamlessly (with humans) to create an intelligent, agile, and data driven organization. It is only when automation opportunities are continuously identified across the enterprise, enriched by intelligence (AI, ML, CV, OCR), aided by analytic tools and supported not only by RPA developers, but the business users, analysts, subject matter experts, that automation reaches its maximum potential. It’s then that automation dynamically scales across the enterprise with much more efficiency and speed. Hyperautomation is indeed the future and will be a key pillar for enterprises to scale their automation program.

At EdgeVerve we’ve always believed that automation in isolation, for specific tasks/functions alone, is suboptimal and that a more holistic approach is needed to scale automation and its benefits across the enterprise. That approach as defined by us in the recent past has been, Automation Singularity. To elaborate, Automation Singularity is a highly customer-centric and agile oriented state of constant improvement and optimization through the future workforce of humans and bots, opening up an expanded horizon of possibilities.” The road to Automation Singularity has fundamentally three stages — Deterministic Automation, Intelligent Automation and Human-empowered Automation. In this state, human specialists drive customer orientation using their creativity and empathy and are complemented by digital workers with extreme productivity and consistency. This unified human-digital workforce will represent a powerful blend of advanced capabilities that will drive growth for the enterprise.

Realizing the full potential of Automation

To derive the most out of their intelligent automation program, enterprises must create an environment conducive to rapid change. Automation cannot be successful if seen as an end state or a purely technology-driven initiative. The first port of call would be a Center of Excellence (CoE) managed by both business and IT leaders. The CoE should create an automation roadmap that sees the creation of a cohesive platform where automation, AI, and ML capabilities work in sync to drive exponential change. It should feature clear end-to-end customer journeys followed by an automation strategy that impacts the most crucial touchpoints in those journeys.

Additionally, since this shift needs both a top-down and bottom-up approach, enterprises should look to build a clear change management plan to ensure smooth progress, addressing areas such as employee reskilling, performance measurement, process redesign, and IT landscape management.

Paving the way for Automation Singularity

With 30M+ transactions processed every month for a single customer in North America and automating booking process for a shipping giant across 130+ countries, we have been enabling scalability for our customers with AssistEdge, an end-to-end automation platform. We’re invested to work closely with our clients to make them realize the vision of Automation Singularity with AssistEdge powered by the underlying three key disciplines – Discover, Automate and Orchestrate.

Organizing the journey into these disciplines brings specificity to assessment and implementation. Discover is primarily a business-process led activity concerned with redesigning customer journeys and identifying process automation opportunities. It helps align business priorities to specific areas that need work. Automate deals with identifying and implementing the right technology stack and will eventually influence every part of the employee-process relationship. Orchestrate aims to ensure that there is coordination in the allocation, prioritization, and management of tasks in an environment powered by a unified workforce of human specialists and digital workers. The data captured through this process is critical to driving process visibility and feedback for continuous optimization through human insights and algorithms.

As enterprises develop the capability to deploy future workers, i.e., human-digital twins working in sync, at scale, they will realize immense potential alongside several complexities that need to be navigated. It is our experience with multiple enterprises that has cemented our belief that Automation Singularity should not be regarded as just an end state or only from a technology perspective. This is a journey that will require collaboration, organic change, and a unified platform where Automation, AI and ML capabilities all work in sync with each other. Read more about Automation Singularity in a whitepaper published by us last year.