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Hyperautomation in Finance for Mid-Market Businesses

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Hyperautomation is a business-driven, disciplined strategy to quickly discover, validate, and automate as many business and IT activities as possible.

What's Inside?

  • Experts predict that every business will employ hyperautomation in some capacity within the next two years
  • It is crucial to keep a track of accounts receivable to prevent unforeseen cash deficits
  • Accounts reconciliation demands a great deal of attention to detail and data gathering
CONTENT

Chapter 1

Executive Summary

Chapter 2

What is hyperautomation?

Chapter 3

Hyperautomation vs AI vs intelligent automation

Chapter 4

Use cases of hyperautomation for mid-market finance teams

Chapter 5

Hyperautomation trends

Chapter 6

Next steps: How to get started with hyperautomation
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Chapter 01

Executive Summary


Hyperautomation is a business-driven, disciplined strategy to quickly discover, validate, and automate as many business and IT activities as possible. Automation frees people from monotonous, low-value work so they may concentrate on more important duties.

Experts predict that every business will employ hyperautomation in some capacity within the next two years. While some businesses have embraced it, others are still experimenting with it at the periphery to see how it will best impact their businesses.

Hyperautomation is the rapid rise of digital employees who work alongside humans to deliver superior customer experiences and lower operating expenses. It’s important to keep in mind that this is not a replacement for human workers; rather, it frees people from monotonous, clerical work.

Chapter 02

What is hyperautomation?


The idea of hyperautomation is to automate everything within an organization that is automatable. Organizations employ hyperautomation, a business-driven, disciplined strategy, to quickly discover, validate, and automate as many business and IT activities as they can.

Hyperautomation entails the coordinated employment of several technologies, tools, or platforms, including robotic process automation (RPA), artificial intelligence (AI), intelligent business process management suites (iBPMS), integration platform as a service (iPaaS), low-code/no-code tools, packaged software, event-driven software architecture, digital twins, etc., to automate as many processes as possible and minimize human intervention between workflows.

With traditional work processes being ranked by business leaders as the #1 workforce issue, hyperautomation is quickly shifting from being an option to a condition to thrive. Gartner lists hyperautomation as one of the top 10 important technology trends. In a recent study, it was found that over 85% of participants planned to “either enhance or sustain their organization’s investments in hyperautomation over the next 12 months, and over 56% already had four or more concurrent hyperautomation activities.”

It’s critical to remember that hyperautomation is not intended to completely replace humans. Instead, automation frees people from monotonous, low-value work so they may concentrate on more important duties. Automation and human participation work together to enable businesses to deliver superior customer experiences while lowering operating expenses and increasing profitability.

An essential element of hyperautomation is the capacity to include people in the digitalization process. Robotic process automation(RPA) was a major component of the initial wave of automation technology. RPA uses bots to simulate repetitive human jobs. These processes are rule-based and carry out tasks using structured data. RPA only focuses on human behavior, unlike artificial intelligence, which aims to mimic human intelligence. Hyperautomation enables digital employees to work side by side with humans to achieve unparalleled efficiency.

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Chapter 03

Hyperautomation vs AI vs intelligent automation


Hyperautomation, AI, and intelligent automation may seem similar but there are differences that sets them apart. Let’s find out how these terms are different in implementation and how they relate to each other.

Hyperautomation, also known as digital process automation or intelligent process automation, deals with the application of advanced technologies including artificial intelligence (AI) and machine learning (ML) to increasingly automate different processes. Hyperautomation refers to both the range of tools used for automation as well as the level of automation—discover, analyze, design, automate, measure, monitor, and reassess.

As no single tool can complete all the workflows, hyperautomation involves the use of a combination of tools—robotic process automation (RPA), intelligent business process management software (iBPM), and AI—with a goal of increasingly supporting AI-driven decision-making.

HighRadius’ Autonomous Receivable is the world’s only AI-powered accounts receivable solution to create working capital impact.

Now, let’s talk about artificial intelligence or AI. AI is like a machine that can organize your wardrobe just as you like it or serve every member of the house a customized cup of coffee! These machines are artificially incorporated with human-like intelligence to perform tasks as we do, by using complex algorithms and mathematical functions. AI is used in smartphones, cars, social media feeds, video games, banking, and many other aspects of our daily life. AI as a standalone technology isn’t used much but there are many AI-driven technologies, hyperautomation being an example.

Intelligent automation can gather and process both structured and unstructured data, enabling businesses to utilize data to make smarter decisions in a way that was not previously possible. Intelligent automation can process tasks beyond what humans are capable of. For example, organizations can improve service speed, handle large volumes of data, increase efficiency and accuracy, and complete tasks that before were not deemed possible.

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Chapter 04

Use cases of hyperautomation for mid-market finance teams


The use of hyperautomation has increased more quickly than ever in the post-COVID environment as companies from all industries compete for digital transformation. In a McKinsey survey, respondents said that their organizations were able to embrace digital innovations at least 25 times quicker than they would have anticipated in the pre-pandemic situation.

In the area of remote working solutions, respondents said that hyperautomation solutions were deployed 40 times faster. Let’s take a look at some of the mid-market finance specific use-cases for hyperautomation

1. Accounts payables

Receiving, processing, and disbursement of invoices from vendors that supplied the business with goods or services are all included in the accounts payable (AP) process.

Traditional AP processes are manual, expensive, time consuming, and immensely error-prone. But, businesses can transform their payables process with the help of automation. Businesses may automate most AP process operations by combining RPA with machine learning and document extraction technologies like optical character recognition (OCR).

2. Accounts receivable

One of the most crucial financial tasks is keeping track of accounts receivable to prevent unforeseen cash deficits. A number of time-consuming tasks are involved in keeping track of unpaid invoices and applying cash once payments are received.

Knowing days sales outstanding (DSO), which is the length of time it takes to collect payment, is also useful. With RPA, there is no chance of forgetting anything, so you can effortlessly produce invoices, monitor their progress, and speed up payment.

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3. Accounts reconciliation

Account reconciliation and intercompany reconciliation are two common use cases for process automation. Whatever kind of reconciliation is being carried out, it demands a great deal of attention to detail and data gathering.

To find out if there are any differences between general ledgers and subledgers and outside paperwork, data may be analyzed quickly and precisely with RPA. If reconciliation is required, software robots can notify your staff and let them know immediately. This makes account reconciliation a perfect use case for  hyperautomation.

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4. Reporting automation

The decisions made by executives and stakeholders depend on the reports that finance departments produce. However, creating and delivering these reports can be time-consuming. The data may have changed during the time it took to manually construct a report, which could have an effect on the choice that is ultimately made.

Tools for robotic process automation can combine data from different sources to provide reports. RPA solutions may handle the procedure for everything from regulatory filing to annual investor reporting.

5. Travel and expenses

Hyper automation can be used to automate the paperwork and repetitive operations involved in travel and expense (T&E) processes. Here are some of the travel & expense processes that can be automated:

  • Obtaining paper receipts for employee travel expenses
  • Data extraction from receipts
  • Verifying receipts to see if they comply with the company’s expenditure policies
  • Restricting approvals and payments for products that do not comply with cost standards

6. Lending

Eliminating  paper procedures would considerably improve the efficiency of day-to-day operations. Customers will have more knowledge of their borrowing options and be able to self-serve. RPA can minimize the amount of labor-intensive human effort by gathering pertinent data from loan paperwork.

  • Customer management: Filling out paperwork and compiling client data the old-fashioned way requires a lot of time and effort. Even manually entering updated client data into the system is prone to human mistake, necessitating data entry and re-entry. By automating loan processing, inconsistencies and unwelcome delays in manually gathering financial data and other necessary consumer information can be readily reduced.
  • Credit assessment: Never process a loan without first checking the customer’s credit report. However, the conventional method of credit analysis requires manually entering the client’s financial information onto a spreadsheet and adding it up using various formulae to produce the credit score. On the other hand, modern loan origination software enables lenders to easily extract from accounting software, tax returns, and other documents the pertinent financial data required for credit risk assessment.
  • Loan monitoring: Allocating or initiating the loan process is followed by constant asset monitoring—monthly, quarterly, or even yearly. Manual data tracking is hardly error-free, particularly when hundreds of loan covenants are kept track of on spreadsheets. This conventional method causes an endless wait in loan processing. Hyper-automation in loan processing can be a boon for all parties involved, especially for clients and executives who have to cope with millions of spreadsheets full of data.

7. Other manual operations

Businesses can hyperautomate all the aspects of their processes and reduce the overall time, effort, and cost that goes into managing the tedious work. Automation can help in revamping the whole organization by optimizing various processes. Some examples include:

  • Process account-based documents by email, media download, or other types of automation, and automatically load documents into an internal system that users can easily access by account
  • Support compliance by automatically downloading updates from a variety of sites and loading data into specific tables for review.
  • For security, forward suspicious emails for URL scanning and alert users if URLs appear malicious
  • Automate IT audits including password strength tests. If a user’s password fails a strength test performed by the robot, the user receives an email requesting a password update that complies with password rules.
Chapter 05

Hyperautomation trends


The term hyperautomation essentially refers to combining advanced technologies to strategically automate as much of a business as possible. Hyperautomation, first presented in 2019, has developed into more than a passing fad; by 2024, it is expected to accomplish 69% of the job presently done by managers.

While some businesses have fully embraced hyperautomation, others are still experimenting with it at the periphery to see how it will best impact their businesses. Experts predict that every business will actively employ at least three of the twenty odd fundamental processes that support hyperautomation within the next two years.

So, let’s look at some key hyperautomation trends:

1. The proliferation of AI-powered low code tools

Low code platforms make it easier to build applications through visual design elements like think-point-click and dropdown, by skipping the time consuming and costly custom coding steps. In turn, this accelerates the delivery speed of some very critical applications such as business process management (BPM), and enterprise content management (ECM) when required.

Why low code?

  1. It lowers the technical aspects of any application for line users and provides the the flexibility needed to make their applications responsive to their requirements
  2. The IT departments do not have to get involved in the day-to-day customization of these applications and can focus on other strategic projects
  3. The development cycle is very short and gives a better ROI

2. Increased use of digital twins for successful hyperautomation of complex workflows

A digital twin duplicates the operations in the digital realm. It helps to understand the impact of your decisions on various processes in changing scenarios. For example, how increasing the production will affect the machinery or how increasing the speed of a machine/vehicle will increase the fuel costs.

Why digital twins?

  1. Helps in predicting the outcome of any decision without the expense of actual resources
  2. The vast amount of information is best utilized here as it helps in making better predictions for organizations
  3. Helps mimic real-world scenarios and processes

3. Process mining and discovery to drive data insights and more accurate predictions

Process mining studies the efficiency of current processes by examining event data and applying pattern recognition techniques to create workflow models.

Process discovery, however, answers how the processes are happening and combines digital tools and the human element to model how processes and employees interact within the organization.

Why process mining and discovery?

  1. Collects useful information from the past and predicts future potential of all the existing processes expansively
  2. Gives a complete picture of what’s happening and all the shortcomings
  3. Prepares the organization better to withstand disruptive forces

4. Intelligent document processing makes workflows faster and streamlined

Intelligent document processing combines the power of ML, optical character recognition (OCR) and intelligent automation (IA) to get the best out of the content and find the right person at the right time to deliver this information.

Why intelligent document processing?

  1. Finds and extracts useful data from the incoming documents in the organization
  2. Captures data with little to no error and it moves efficiently throughout the organization
  3. Speeds up the whole process
Chapter 06

Next steps: How to get started with hyperautomation


Since RPA and AI are widely used in the financial services industry, it’s likely that your company has already implemented a number of automation projects. However, in order to achieve scalability and agility with hyperautomation, a concerted, corporate-wide effort is needed.

1. Designated automation center of excellence

An organization’s hyperautomation programme should be supervised and guided by an automation CoE, which is a business unit made up of technical and business professionals. A CoE for automation will:

  • close the gap between the adoption of technology solutions and corporate decision-making
  • choose which procedures to automate
  • make a plan for implementing the hyperautomation program
  • establish a shared vision and a set of standards for behavior

2. Establish proper management strategy

In order to successfully implement hyperautomation, a company’s culture must be robust. Organizations ought to

  • Offer employees the chance to re-train and gain new skills. In 2017, 33% of the employment abilities listed in the average job description were no longer required in 2021. This pattern is anticipated to persist as the scope of hyperautomation expands. Offering online training courses can help employees re-skill as needed.
  • Increase top-down communication on the need for hyperautomation, to assist the employees and stakeholders understand what will change, and what to anticipate from staff.

3. Check out fintech vendors you can partner with

Partnering with experienced fintech vendors is key to implementing hyperautomation use cases successfully. HighRadius offers autonomous finance solutions that are easy to implement and affordable. Our range of solutions include autonomous receivables, autonomous treasury, and autonomous accounting solutions.

What’s special about these solutions?

  • Real-time credit risk management
  • Automated customer onboarding
  • Automated invoicing
  • Self-service buyer portal
  • Automated remittance aggregation
  • Automated dunning
  • Automated dispute management and deduction coding, and much more

To learn more about us, schedule a demo today or talk to our experts.

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