The worldwide adoption of automation technology is just increasing with every passing year. We all have seen the impact of RPA in banking, healthcare, IT, insurance, and many other industries so far. Right from customer onboarding to KYC, RPA has been able to do it all for enterprises. But now enterprises are going beyond the RPA to transform their business process and that’s where hyperautomation comes in. So do you want to boost the process efficiency and scale up operations? Then let’s learn more about hyperautomation and its potential use cases across industries.

What is Hyperautomation?

Hyperautomation is an advanced automation approach that integrates artificial intelligence (AI), machine learning (ML), robotic process automation (RPA), and other technologies to automate and optimize business processes across an organization comprehensively. The concept of hyperautomation was popularized by Gartner, an IT research and advisory firm. As per Gartner, the enterprises will lower operational costs by 30% using hyperautomation technologies.

In simpler terms, hyperautomation goes beyond traditional automation by combining technologies to automate repetitive tasks and tackle more complex cognitive functions that previously required human intervention.

Top Hyperautomation Use Cases to Look for in 2024

Hyperautomation can be implemented in multiple business processes to make sure instant service is provided to customers. Some of the hypermutation examples across industries are:

Top Hyperautomation Use Cases to Look for in 2023

  1. Customer Service

    When it comes to customers, offering top-notch service is essential to retain and attract new customers. However, by using RPA enterprises can automate customer interaction with pre-defined workflow and AI chatbot for instant response to service tickets and queries. But, what if you want more from these interactions? Using hyperautomation solutions enterprises can gain insights from employee communications to understand customer preferences and create personalized customer experiences. With hyperautomation in customer services, the enterprise can also route the customer service ticket to the right agent and make a data-driven decision.

  2. Claims Processing

    Using a hyperautomation platform infused with NLP, OCR, and machine learning, businesses can extract claims data from multiple sources,& formats, verify the claims data with the database, and then evaluate policy coverage for the claims. Once this whole process is done, the claims processing can be further initiated and information can be shared with customers using chatbot autonomously. Also, hyperautomation solutions in claims processing can detect fraud in real time and generate alerts to help in decision-making.

  3. Anti-Money Laundering

    The RBI requires compliance with the Bank Secrecy Act, making it mandatory to implement Anti-Money Laundering (AML) rules. These rules aim to detect and report suspicious activities, including predicate offenses like securities fraud and market manipulation, which could lead to money laundering.

    Hyperautomation streamlines customer information management in CRM by automating data collection, validation, and compilation. AI bots can gather data during onboarding and from public databases, validate it across various sources, and compile a comprehensive customer history. Using a hyperautomation platform businesses can perform customer screening against standard databases, improve customer service through intelligent bots, and ease regulatory monitoring and data collection. Additionally, it facilitates risk assessments and account closure for high-risk customers.

  4. Underwriting

    Underwriting, the process of evaluating and assessing risks associated with insurance or financial products, can be significantly improved and streamlined through hyperautomation. Hyperautomation in underwriting automates data gathering from various sources, such as social media, public records, and credit reports, enabling AI and NLP analysis for precise risk assessment. Machine learning algorithms expedite decision-making, personalize insurance products, detect fraud, and enhance customer experience. Also, using a hyperautomation platform businesses can continuously learn, and make sure compliance adherence is ensured, with the ability to integrate with existing systems.

  5. Customer Onboarding

    Customer onboarding in banking is a document-intensive process, mainly due to know-your-customer (KYC) regulations. The process includes identity verification, screening, customer due diligence, scoring, reporting, and account activation.
    Automation of customer onboarding is achieved through pre-trained bots that extract information from documents, input data into systems, and utilize machine learning to develop risk profiles. Additionally, human-in-the-loop and machine-learning models enable verification and validation of information. Intelligent bots are continuously trained using historical data to enhance their accuracy in handling the onboarding process.

  6. Accounts Payable

    It is a critical function in organizations, responsible for managing and processing payments to suppliers, vendors, and creditors. Hyperautomation in accounts payable refers to the integration of advanced technologies, such as artificial intelligence (AI), robotic process automation (RPA), machine learning, and other intelligent automation tools, to streamline and enhance the accounts payable process.
    Using hyperautomation in accounts payable businesses can automate invoice data extraction through AI-powered OCR, streamline workflow with RPA for routing and approval, match invoices to purchase orders, detect fraud using ML, optimize payment schedules, and centralize vendor management. It also can be integrated with ERP systems to ensure compliance and create detailed audit trails. This enhances efficiency, accuracy, and compliance while reducing manual effort and costs, empowering businesses to make strategic decisions.

  7. IT Infrastructure

    Hyperautomation in IT infrastructure automates multiple processes involved in infrastructure management like provisioning, monitoring, maintenance, security, disaster recovery, data management, and performance optimization. Automating the process involved in IT infrastructure, it also enables proactive actions, self-healing systems, and streamlined workflows, empowering IT teams and driving business growth.

  8. KYC and fraud Detection

    Hyperautomation offers immense potential for the banking sector’s success. Various areas, including regulatory reporting, marketing, sales, distribution, bank servicing, payment and lending operations, back-office tasks, and corporate support, can benefit greatly from hyperautomation.
    For instance, intelligent character recognition enables seamless data entry into KYC portals from manually prepared forms, streamlining processes. AI-powered smart automation systems effectively detect and prevent fraud and criminal activities. Advanced AI-based machine learning models predict harmful transactions, reducing risks. Anti-money laundering (AML) technologies further contribute to the hyperautomation innovation stack, enhancing prediction and risk management capabilities.

  9. Loan Processing

    Hyperautomation streamlines loan processing through intelligent bots that extract data from application documents. Also, by using AI chatbots enterprises can monitor customer interaction in real time and offer risk assessment. With hyperautomation in banking, leaders can review loans and, and detect fraud for compliance management. It also offers personalized loan offers, real-time updates, and automated documentation, enhancing efficiency, reducing errors, and improving customer experience. Also with hyperautomation businesses can continuously learn and ensure ongoing improvements for financial institutions, driving faster approvals and increased competitiveness.

  10. Policy Administration

    Hyperautomation streamlines financial reporting by automatically collecting data from diverse sources like accounting systems, ERPs, spreadsheets, and external databases. AI-driven algorithms also validate and cleanse the data, ensuring accuracy and completeness. Also, AI-driven bots generate financial reports in real time, based on predefined rules, and customize reports to suit stakeholders’ preferences. Hyperautomation ensures compliance and creates an audit trail for transparency. This further reduces manual effort, minimizes errors, and empowers informed decision-making for business success.


Hyperautomation is making waves across industries. With its potential to significantly increase the bottom line of companies, offering benefits such as increased productivity and more efficiency, hyperautomation is surely the game changer. Interestingly, a study conducted by Salesforce states that “by 2024, 80% of organizations expect to have hyperautomation on their technology roadmap.” The future holds a lot of potential for this hot technology.