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Top Five Hyperautomation Trends for Accounting & Finance Teams in 2022

October 29, 2021

Hyperautomation has been a buzzword for many while doing the rounds across CIO discussions. 2021 wasn’t the first time Gartner included Hyperautomation as an essential strategic technology trend to foster a digital journey across enterprises. According to the “Top 10, Strategic Technology Trends for 2020,” report published by Gartner in 2020 – Organizations are required to augment different technology adoption process with human-centric design to realize the tangible business impact, and Hyperautomation seemed to be the way ahead.

Hyperautomation deals with the application of advanced technologies, including AI and 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) – According to Gartner

Across most organizations Hyperautomation is a mindset having the same purpose and bearing different names: Gartner refers to it as Hyperautomation, Forrester calls it Digital Process Automation (DPA), and IDC calls it Intelligent Process Automation (IPA).

Organizations are often dragged down by "Operational Debt" - the intrinsic issue can be traced back to legacy systems, suboptimal processes, and bottlenecks, disharmonized human touchpoints, unstructured data residing in silos, lack of centralized data architecture, and security gaps. Which have led business processes to be a patchwork of technologies – not optimized, coherent, or consistent.

Considering Hyperautomation to be an extension of Robotic Process Automation (RPA) can be misleading. The approach builds a cognitive layer above automation. As a result, it effectively calibrates data processing with real-time business decisions.

Hyperautomation software solutions are shaped by keeping automation at the core - flanked by new cutting-edge technologies: artificial intelligence (AI), machine learning, process mining, data analytics as part of the broader arsenal that Hyperautomation offers.

“As a result, Hyperautomation initiatives become the single source of technology adoption truth for enterprises.”

Hyperautomation has emerged as an effective mindset for organizations to improve efficiency, save costs, and increase productivity. In this article, we introspect the major Hyperautomation trends influencing financing and accounting teams globally.

Business Data Democratization

Business data generated across finance and accounting processes often reside in silos and across different systems. Hyperautomation often integrates various data sources with data storage systems and builds an analytics layer on top of it.

Business owners can now democratize business data and generate insights by building a system that provides a single source of truth – across business processes.

Hyperautomation initiatives bring together fragmented data residing across isolated systems and data lakes. Business now can realize unmatched value through its ability to integrate modern and old systems seamlessly.

AI-driven document Processing

Accounting and finance teams process multiple documents having business-sensitive information daily. As business scales and increases its operations – it becomes imminent to ramp up operations with rising demand. This leads to the appointment of multiple resources and, in turn increases costs multiple folds.

Hyperautomation integrates OCR with multiple AI technologies, which can recognize and extract data from all types of documents. It eliminates manual, repetitive, time-consuming tasks involved while processing documents. Computer vision comprehends a document just like a human would do – for processing, NLP can process documents in multiple languages, and ML models can detect errors and possible fraudulent intentions.

Automated Reporting

Automating manual activities across and finance and accounting processes ensures compliance. In addition, automation reduces data processing errors and improves data quality. Through Process Mining - large sets of data can be mined from business processes. Data generated when humans and systems interact and are associated with event-based timestamps is extracted.

Business owners can now generate automated reports - by analyzing process performance from the event log to identify trends and new patterns. The analysis is used to generate live actionable insights that can help increase process efficiency and performance.

Prevent Financial Frauds

According to the “2020 Report to the Nations,” published by the Association of Certified Fraud Examiners (ACFE), organizations lose an estimated 5% of annual revenue due to fraud.

Financial systems across enterprises have always been the victim of scammers and malicious attacks. People or hostile organizations are devising creative means to find loopholes across finance and accounting departments – As a result, there is a constant threat that the departments face.

Hyperautomation combines multiple technologies to mitigate threats associated with financial fraud. Automation and a combination of AI/ML address fraud prevention through – automated invoice review workflows, employee malintent monitoring, and tracking, and advanced vendor match capability. automated approval workflow, and digital solutions to enforce compliance.

Learn More about how to prevent Accounts Payable (AP) Fraud.

A Human Centric Automation Attitude

Hyperautomation yields a much higher adoption rate across business process, when designed and implemented with human-centric approach.

A human-centric approach to automation is mostly overlooked; yet being highly essential towards ensuring success. Such strategies prioritize users’ needs, requirements and empower users to complete tasks effectively. Most organizations have realized the importance of user experience and focusing more on building user-centric design to automation cores – intending to make task completion seamless.

Learn More - Beyond Automation: The Hyperautomation Edge vs Conventional RPA [Whitepaper]

About the author

Aritro Chatterjee, Product Marketing (

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