Finding the edge in automation

RPA software company AutomationEdge exists in a fast-paced world where financial institutions are seeking to improve customer experiences and business efficiency. IBSi FinTech Journal talks to CEO, Uday Birajdar, about the company’s plans.

Megha Bhattacharya  Market Analyst, IBS Intelligence  

Describe your typical day at AutomationEdge RPA is very relevant to the current world.

It’s a fast-paced life as we are building new technologies, updating new products and solving innovative challenges put forth by customers. Our time overlaps with the US and involves shuffling between product roadmaps and management. It also involves brainstorming about solution building. Thought leadership, client meetings, marketing and co-creation of solutions form a considerable part of my daily life. What is your geographic focus? Everyone out there would like to improve customer experience and business efficiency, and that makes us go global rather than limiting to a specific geography.

But if I must pinpoint, then the top four regions would be Americas, Europe, Middle East and India. From a customer perspective, we find a mix of on-cloud and on-premise consumers in the Americas and Europe, whereas ME and India have mostly an on-premise RPA consumer base. The greatest number of cloud consumers are in the Americas. The outlook for cloud-based RPA solutions in the Middle East is limited in the near future; however, for the Indian market, one of our ‘big four’ partners is creating a strong strategy for enabling on-cloud adoption among Indian consumers.

What is AutomationEdge Process Studio? How does it complement AutomationEdge’s offerings? AutomationEdge Process Studio (AEPS) is the development studio for AutomationEdge.

There are a number of ways it eases development:

  • Workflow design: Processes are developed as a workflow, which makes it easy to visualise and map the process to business flow
  • Modular drag-and-drop approach: AEPS workflows are built by using various steps together and connecting them using the required business logic. Changes in business processes can be accommodated by simply changing or replacing a step in a workflow
  • Spy applications: Different spy applications allow developers to easily fetch relevant data about the target system elements to enable bot interaction with those systems
  • Advanced ready action: AEPS has a large library of ready connectors to various IT systems, service desks, monitoring tools and so on, which allows developers to easily connect. These connectors talk to the target system without using a back-end approach, giving developers control over the action performed
  • Scripting support: AEPS is a NoCode -> Low Code -> ProCode platform that can be used by people of various skill sets. For instance, it supports scripting in various languages such as Python, R, Java, JavaScript and VB natively, allowing developers to fine-tune their automation
  • Rapid API integration: AE has exposed REST-based APIs as well as ready actions to consume different APIs seamlessly; hence developers don’t have to write code for API consumption

Which customer segments do AutomationEdge’s products serve? How important is the banking, financial services and insurance (BFSI) segment?

AutomationEdge helps bring enterprise-wide digital transformation across the IT function, but also in other areas including HR, procurement, finance and accounting, operations, sales and marketing and administration. We offer ready workflows for banking and finance verticals and IT horizontals, focusing on mid to large size banks, insurance and credit unions. The BFSI segment has experienced the greatest adoption of RPA and AI technology and it remains the primary vertical for AutomationEdge.

What is the product roadmap for AutomationEdge?

We have been building cloud-native products from the very beginning. Multi-tenancy was built into our solution and we were one of the initial cloud-based RPA providers. We have been able to upgrade our customers across different models seamlessly and continuously invest in our cloud strategy. Our product designs revolve around RPA, data integrations, cognitive AI integrations and ready bots. The next product releases include Computer Vision, which is a next generation image recognition technology and we are continuing to invest in that technology.

It is based on detecting scripted elements in a complex image-based interface in a complex application, which a traditional RPA approach will not be able to detect. Like OCR, it forms one aspect of the image automation solution. Some of the use cases include automating core applications that aren’t available to the users and automating complex pages built through legacy technologies. In AI, we have prediction and classification products. The next releases will focus on self-learning and self-healing systems. Then follows the Bot Stores, comprising of connectors for different systems and ready themes for different verticals. Some of the use cases include an initial release of the Ready Bots for the BFSI sector as well as for IT automation purposes.

What is AutomationEdge’s partner strategy?

We have three categories of partners: global outsourcers and the ‘big four’. Following that are the technology alliance partners with their own solutions. They either bundle their technology with ours or they develop a joint go to market strategy with deeper integration of their technologies. For example, BMC software bundles our automation tech along with its Salesforce cloud-based solution. The third category is boutique partners that are focused on certain geographies or verticals. There are about 30 partners globally that are boutique partners or valueadded resellers.

What is AutomationEdge’s strategy for the Ready Bot Store?

Our approach is different from traditional RPA vendors. Our workflow bots and connectors provide drag-and-drop integrations or they add a significant functionality in a particular vertical, aiming to automate processes and lower costs. Our bots are not RPA-based because such bots need to be changed according to companies, application versions and industries. RPAbased bots are costly to maintain. Therefore, we developed API-based connectors; there are connectors to the Salesforce System, ServiceNow as well as other industry applications and IT systems.

Another type of ready bots are AI-related bots that provide an easy to use AI functionality. These bots are used for risk assessment, cross-sell and upsell, complaints management and AML, for example. These help users to either build a quick integration or provide a ready to use business functionality.

What are the main challenges in implementing RPA solutions?

First is identifying the right use case; a bank’s IT and business departments will need to work together to identify a portfolio of use cases that deliver business benefits. The level of automation is set to expand in the future, with increasing evolution toward intelligent process automation combining tools such as RPA with optical character recognition (OCR) and machine learning that will extend use cases beyond simple rule-driven activities. The second challenge is that many banks choose the wrong RPA solution because they don’t have the guidance and skills to judge which is the best for them. Knowledge of all the processes is crucial and will be helpful.

Sometimes the wrong RPA has been chosen because a bank is concerned about costs. Another challenge is a lack of buy-in from team members. RPA implementation is a change management exercise as much as any other business transformation and therefore staff must be provided with the information they need to understand what RPA will mean for them, their work and their colleagues. Setting up channels through which your team can be educated on the changes and give feedback is critical to avoiding failure. A happy and informed workforce will feel ready to embrace RPA. RPA involves many responsibilities and these must be properly managed. Finally, realistic expectations must be formulated. Deployment and implementation of RPA are the tough tasks. All of the processes go through different functionalities and individuals throughout a bank’s hierarchy.

What growth do you expect for RPA in the next five years and where will it come from?

Most RPA adoptions are limited to transactional rules-based processes, organisations that combine RPA with additional digital technologies, such as dynamic workflow, machine learning, and NLP, computer vision, and biometrics will realise greater value by achieving intelligent automation. Enterprises will look at robot utilisation in a critical way and use RPA platforms that allow robots to shift between processes during lean periods. Businesses managing large virtual workforces can consider creating a centralised control to manage bots, monitor performance and track benefits.

Over time, RPA capabilities are likely to become more closely integrated in other enterprise software products. Industry acquisitions in the RPA space are set to continue, while broader enterprise software companies will integrate RPA into their offerings and build a software library of intelligent automation use cases to enhance the customer experience. APIs will play a big role in enabling the exchange of information across technologies. The tighter integration of these technologies will lead to less custom development work and even higher levels of productivity.

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