Intelligent automation – the next game-changer?

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Robotic Process Automation (RPA), artificial intelligence and machine learning are all current ‘buzz-phrases’ in this era of cognitive computing. Pure RPA has been around for quite some time – interactive Voice Response Systems (IVRS), for example, have been in existence for years.

RPA enables organisations to create their own software robots to automate business processes and these bots are non-disruptive, non-invasive, with configurable software that is controlled by humans. This disruptive technology can create smarter business processes through flawless performance of repetitive tasks at a fraction of the cost of traditional processes – leading up to 25 to 40% labour cost reduction.

However, there are other more ground-breaking technology capabilities like artificial intelligence, machine learning, computer vision and cognitive automation, that when converged with RPA can produce augmented automation capabilities with the potential to amplify business value and competitive advantages for organisations.

Transitioning to intelligent automation

Today, organisations are increasingly aware that the integration of the execution capabilities of RPA, combined with the cognitive capabilities of machine learning can take business benefits of automation to the next level.

RPA differs from artificial intelligence in that software robots must be provided with a set of instructions as they are not ‘naturally’ intelligent. While robots may be good at executing specifically defined tasks, RPA tools have a limited capability in the sense that they cannot learn from experience or adjust to new conditions. This is where artificial intelligence capabilities can be harnessed by organisations.

Artificial intelligence is an umbrella term used to describe the ability of machines to carry out “smart” tasks and mimic human mental capabilities like cognition and reasoning. Machine learning is the most common way of applying artificial intelligence by providing machines access to data and letting them learn for themselves. The advantage is that an AI algorithm can adapt to a new environment, learn from the outcomes of decisions and improve over time.

Organisations are increasingly harnessing the potential applications of RPA and machine learning synergy.

Examples of uses include for insurance claims and customer service. In the insurance sector, organisations are deploying computer vision applications that can integrate AI capabilities to assess the context of how an accident occurred to enable remote review and approval of minor claims.

AI can also be harnessed to provide a more seamless experience for customers.

An example is improved speech recognition and call routing in contact centres through the use of AI to facilitate a more seamless experience for customers. AI can also help customer service representatives by providing them more information to help handle complicated challenges that self-service cannot resolve. Today, AI software that can listen to calls and decode their impact on customers is available which means AI can help understand how the issue was resolved, gauge if the customer’s loyalty would increase in future as a result of the call, and even flag at-risk customers.

Organisations are increasingly transitioning to intelligent automation that is an combination of both RPA and forms of machine intelligence.

Smart and intelligent automation at Firstsource

At Firstsource, we are continuously innovating and investing in next-generation tools, technologies and frameworks to enable clients to become future-ready. We understand the importance of harnessing RPA along with AI as it can drive significant efficiencies and generate new sources of revenue for organisations.

We have set up the ‘Firstsource Automation Centre of Excellence’ (FACE) that comprises a dedicated team of experienced global automation experts, responsible for roles ranging from automation consultants to scripters. The exact technology, approach and scoping is determined by this team and a detailed due diligence phase with clients is usually conducted initially to identify automation opportunities.

Harnessing the power of AI, ML and deep learning

At Firstsource, we have a heritage of being associated with automation technologies, and this has allowed us to naturally progress into employing AI as a means to address unstructured data inputs and dynamic scenarios with clients. Some of our capabilities include:

  • ML Hybrid Data Extractor – ML Hybrid Data Extractor is a machine learning-led data extraction and classification platform that excels at extracting data from structured as well as unstructured documents. Conventional Optical Character Recognition (OCR) technology is usually not powerful enough to be able to accurately extract data from scanned documents. Our data extraction solution features Intelligent Character Recognition (ICR), word recognition and machine learning algorithms to improve the fidelity of results achieved in data extraction. The platform is compatible with different formats like a fax, PDF, email, etc.
  • NLP-led chatbots and deep knowledge search – We leverage NLP-powered knowledge management and knowledge automation tools to enable contextual agent guidance and help. We use chatbots to focus on chatbot functionality, with practical potential to solve end user problems. We are currently exploring synergies between chatbot technology and RPA processes.
  • AI Constellation – AI constellation is our ambitious approach to use deep learning in processes that cannot be conventionally automated. Deep learning algorithms applied to computer vision is opening doors, ranging from facial recognition to home appraisal, in our mortgage back office estate.
  • Hybrid chat bots – Our hybrid chat bots allow chats to be handled by AI-powered chat bots. Our chat bots can be configured to hand over chats to human agents if a scenario becomes too complicated for the bot or if human intervention is required.
  • Knowledge automation – We leverage knowledge automation through on-demand, interactive desktop widgets that replace the need for a bloated knowledge base. Our knowledge automation capabilities allow content curation, discovery and search powered by machine learning that allows agents to rapidly find knowledge articles, templates or relevant customer information.

Assisted RPA

Firstsource leverages Assisted RPA to eliminate redundant process steps. Voice, chat and email processes are difficult to automate with traditional RPA due to the dynamic nature of inputs received by an agent. Our proprietary FirstSmartomation methodology has evolved to enable RPA in dynamic processes through multiple means depending on the scenario:

  • Assistance combined with RPA – Agents are provided real-time, interactive guidance in addition to options for triggering specific tasks.
  • Hotkey-based RPA triggers – These help in launching specific RPA tasks via console or defined hotkeys.
  • Unified desktop – This helps in combining multiple screens or applications into a single interface by using automation at appropriate steps of using the interface. Unified interfaces would positively impact agent performance by reducing the number of transfers between screens and redundant copy-pasting of data.

While organisations that leverage RPA implementations will reap significant cost, operational and strategic benefits, it will be the potent combination of AI and other technologies that will be the truly transformative technology of the future.

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