Transforming Legacy Systems with TCS Cognitive Automation Platform

Leverage public records, handwritten customer input and scanned documents to perform required KYC checks. For example, an attended bot can bring up relevant data on an agent’s screen at the optimal moment in a live customer interaction to help the agent upsell the customer to a specific product. “The whole process of categorization was carried out manually by a human workforce and was prone to errors and inefficiencies,” Modi said. This assists in resolving more difficult issues and gaining valuable insights from complicated data. In this situation, if there are difficulties, the solution checks them, fixes them, or, as soon as possible, forwards the problem to a human operator to avoid further delays.

Because AVA is self-learning, you will also benefit from a continually growing resource of valuable customer information. By automating between 40-80% of customer requests, you raise the quality of client satisfaction while radically reducing the cost of routine request management. Please be informed that when you click the Send button Itransition Group will process your personal data in accordance with our Privacy notice for the purpose of providing you with appropriate information. Data governance is essential to RPA use cases, and the one described above is no exception. An NLP model has been successfully trained on sufficient practitioner referral data.

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A new connection, a connection renewal, a change of plans, technical difficulties, etc., are all examples of queries. Intending to enhance Bookmyshow‘s client interactions, Splunk has provided them with a cognitive automation solution. The integration of these three components creates a transformative solution that streamlines processes and simplifies workflows to ultimately improve the customer experience. The cognitive automation solution is pre-trained and configured for multiple BFSI use cases.

Based on this, we describe the relevance and opportunities of cognitive automation in Information Systems research. Unlike other types of AI, such as machine learning, or deep learning, cognitive automation solutions imitate the way humans think. This means using technologies such as natural language processing, image processing, pattern recognition, and — most importantly — contextual analyses to make more intuitive leaps, perceptions, and judgments.

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But combined with cognitive automation, RPA has the potential to automate entire end-to-end processes and aid in decision-making from both structured and unstructured data. In another example, Deloitte has developed a cognitive automation solution for a large hospital in the UK. The NLP-based software was used to cognitive automation solutions interpret practitioner referrals and data from electronic medical records to identify the urgency status of a particular patient. First, a bot pulls data from medical records for the NLP model to analyze it, and then, based on the level of urgency, another bot places the patient in the appointment booking system.

By leaving routine tasks to robots, humans can squeeze the most value from collaboration and emotional intelligence. This is why robotic process automation consulting is becoming increasingly popular with enterprises. IA is capable of advanced data analytics techniques to process and interpret large volumes of data quickly and accurately. This enables organizations to gain valuable insights into their processes so they can make data-driven decisions. And using its AI capabilities, a digital worker can even identify patterns or trends that might have gone previously unnoticed by their human counterparts. Intelligent virtual assistants and chatbots provide personalized and responsive support for a more streamlined customer journey.

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This approach ensures end users’ apprehensions regarding their digital literacy are alleviated, thus facilitating user buy-in. Itransition offers full-cycle AI development to craft custom process automation, cognitive assistants, personalization and predictive analytics solutions. AI and ML are fast-growing advanced technologies that, when augmented with automation, can take RPA to the next level.

• Although Robotic Process Automation (RPA) thrives in almost every industry and is growing fast, it works well only with structured data sources.
• This results in improved efficiency and productivity by reducing the time and effort required for tasks that traditionally rely on human cognitive abilities.
• AVA allows you to offer instant, round-the-clock response to both spoken and written customer enquiries.
• The foundation of cognitive automation is software that adds intelligence to information-intensive processes.

TCS’ Cognitive Automation Platform (see Figure 1) helps BFSI organizations expand their enterprise-level automation capabilities by seamlessly integrating legacy systems, modern technologies, and traditional automation solutions. The platform leverages artificial intelligence (AI), machine learning (ML), computer vision, natural language processing (NLP), advanced analytics, and knowledge management, among others, to create a fully automated organization. Intelligent automation simplifies processes, frees up resources and improves operational efficiencies, and it has a variety of applications. An insurance provider can use intelligent automation to calculate payments, make predictions used to calculate rates, and address compliance needs. Intelligent/cognitive automation tools allow RPA tools to handle unstructured information and make decisions based on complex, unstructured input. Cognitive automation (also called smart or intelligent automation) is an emerging field that augments RPA tools with artificial intelligence (AI) capabilities like optical character recognition (OCR) or natural language processing (NLP).

“One of the biggest challenges for organizations that have embarked on automation initiatives and want to expand their automation and digitalization footprint is knowing what their processes are,” Kohli said. Cognitive automation may also play a role in automatically inventorying complex business processes. Processors must retype the text or use standalone optical character recognition tools to copy and paste information from a PDF file into the system for further processing. Cognitive automation uses technologies like OCR to enable automation so the processor can supervise and take decisions based on extracted and persisted information. Karev said it’s important to develop a clear ownership strategy with various stakeholders agreeing on the project goals and tactics.

With the automation of repetitive tasks through IA, businesses can reduce their costs as well as establish more consistency within their workflows. The COVID-19 pandemic has only expedited digital transformation efforts, fueling more investment within infrastructure to support automation. Individuals focused on low-level work will be reallocated to implement and scale these solutions as well as other higher-level tasks. Middle managers will need to shift their focus on the more human elements of their job to sustain motivation within the workforce.

Cognitive automation enhances the customer experience by providing accurate responses, round-the-clock support, and personalized interactions. This results in increased customer satisfaction, loyalty, and a positive brand image, ultimately leading to business growth and a competitive advantage in the market. By automating tasks that are prone to human errors, cognitive automation significantly reduces mistakes, ensuring consistently high-quality output. This is particularly crucial in sectors where precision are paramount, such as healthcare and finance.

For customers seeking assistance, cognitive automation creates a seamless experience with intelligent chatbots and virtual assistants. It ensures accurate responses to queries, providing personalized support, and fostering a sense of trust in the company’s services. Cognitive automation is an extension of existing robotic process automation (RPA) technology. Machine learning enables bots to remember the best ways of completing tasks, while technology like optical character recognition increases the data formats with which bots can interact. Cognitive automation adds a layer of AI to RPA software to enhance the ability of RPA bots to complete tasks that require more knowledge and reasoning.

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KlearStack is a hassle-free solution to a reliable automation experience. It gives businesses a competitive advantage by enhancing their operations in numerous areas. Cognitive automation involves incorporating an additional layer of AI and ML.

For example, if they are not integrated into the legacy billing system, a customer will not be able to change her billing period through the chatbot. Cognitive automation allows building chatbots that can make changes in other systems with ease. In sectors with strict regulations, such as finance and healthcare, cognitive automation assists professionals by identifying potential risks. It ensures compliance with industry standards, and providing a reliable framework for handling sensitive data, fostering a sense of security among stakeholders. It can seamlessly integrate with existing systems and software, allowing it to handle large volumes of data and tasks efficiently, making it suitable for businesses of varying sizes and needs.

The Cognitive Automation system gets to work once a new hire needs to be onboarded. These processes need to be taken care of in runtime for a company that manufactures airplanes like Airbus since they are significantly more crucial. Let’s see some of the cognitive automation examples for better understanding.

For example, Digital Reasoning’s AI-powered process automation solution allows clinicians to improve efficiency in the oncology sector. With the help of deep learning and artificial intelligence in radiology, clinicians can intelligently assess pathology and radiology reports to understand the cancer cases presented and augment subsequent care workflows accordingly. Facilitated by AI technology, the phenomenon of cognitive automation extends the scope of deterministic business process automation (BPA) through the probabilistic automation of knowledge and service work. By transforming work systems through cognitive automation, organizations are provided with vast strategic opportunities to gain business value.

Cognitive automation tools are relatively new, but experts say they offer a substantial upgrade over earlier generations of automation software. Now, IT leaders are looking to expand the range of cognitive automation use cases they support in the enterprise. A cognitive automation solution is a positive development in the world of automation.