Accounting as the technology leader: Accounting has always been an early adopter of new technologies. From mainframe computers maintaining the general ledger on punch cards to the introduction of automated spread sheets, to the development of home tax software, the accounting profession has adopted new technologies.
The 4th Industrial Revolution. We are looking at the next Industrial Revolution. According to Forbes (https://www.forbes.com/sites/bernardmarr/2018/08/13/the-4th-industrial-revolution-is-here-are-you-ready/#2234536c628b) the 4th Industrial Revolution’s focus on cyber-physical systems and the internet of things will result in the disruptive, exponential change in our relations to work and life.
The Accounting Technology Revolution. Brings accounting data, modern analytical tools and statistical analysis together to provide the best possible business intelligence. The introduction of Artificial Intelligence in all accounting disciplines; Robotics; Blockchain; Cryptocurrency; and Data Analytics revolutionize the accounting industry and changes its focus to understanding what underlies the financial transactions that drive business operations.
How to join the Technology Revolution. Advanced technologies will be incorporated into all your accounting courses. Consider this your first stop to understanding how current technologies are impacting the Accounting Profession.
The Accounting Technology Revolution
The Accounting Technology Revolution is divided into the following components:
- What Created the Revolution—the foundational documents in accounting
- Key Terms—Artificial Intelligence, Big Data, Parallel computing, Cloud Computing, Internet of Things (IoT)
- Robotics—using technology to reduce reoccurring accounting tasks
What Created the Revolution—
The World Economic Forum1 described the 4th Industrial Revolution as:
“…We stand on the brink of a technological revolution that will fundamentally alter the way we live, work, and relate to one another. In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before. We do not yet know just how it will unfold, but one thing is clear: the response to it must be integrated and comprehensive, involving all stakeholders of the global polity, from the public and private sectors to academia and civil society….”
If the first industrial revolution was mechanization, the second mass production, the third computerization, the fourth is convergence, where the lines blur between technology, intelligence, and analysis. Key concepts related to the fourth industrial revolution include artificial intelligence, big data, robotics, and evolving technologies.
The World Economic Forum continues with:
“…There are three reasons why today’s transformations represent not merely a prolongation of the Third Industrial Revolution but rather the arrival of a Fourth and distinct one: velocity, scope, and systems impact. The speed of current breakthroughs has no historical precedent. When compared with previous industrial revolutions, the Fourth is evolving at an exponential rather than a linear pace. Moreover, it is disrupting almost every industry in every country. And the breadth and depth of these changes herald the transformation of entire systems of production, management, and governance…”
The Accountant’s role is changing. Robotics will support standard financial transactions.
First an introduction to the 4th Industrial Revolution Key Terms. These terms will be used throughout this discussion and in your coursework.
Key Terms that form the basis for the 4th Industrial Revolution:
Robotics
Ernst and Young define Robotics as3
“…What is robotic process automation? • Robotic process automation (RPA) is the use of software that mimics human interaction with core systems, web and desktop applications to execute processes. • RPA is an effective cost and time enabler, complementing any digital transformation journey to streamline business processes, achieve profitability and maintain a competitive advantage….”. Further, they state:
“…The best tasks for (Robotics) automation are the tasks that: • Are rules-based, to allow decision flows to alter dynamically • Are consistent, with the same step being performed repeatedly • Are template-driven, with data entered into specific fields in a repetitive manner…”
Artificial Intelligence:
Deloitte defines Artificial Intelligence as:4
“…1. Artificial Intelligence (AI)
In general terms, AI refers to a broad field of science encompassing not only computer science but also psychology, philosophy, linguistics and other areas. AI is concerned with getting computers to do tasks that would normally require human intelligence. Having said that, there are many points of view on AI and many definitions exist. Below we’ll list some definitions of that highlight its key characteristics.
Some general definitions
- “Artificial intelligence is a computerized system that exhibits behavior that is commonly thought of as requiring intelligence.” (3)
- “Artificial Intelligence is the science of making machines do things that would require intelligence if done by man.” (4)
- In these definitions, the concept of intelligence refers to some kind of ability to plan, reason and learn, sense and build some kind of perception of knowledge and communicate in natural language…”
In the same article, Deloitte provides a definition of Machine Learning and Cognitive Analytics. Both are Artificial Intelligence, but both operate in different ways.
- Machine Learning is training a machine to perform tasks by “training” through repeated exposure to test data. It looks for patterns and the applies what is has “learned” to new data to identify similar patterns. It may identify patterns but not know their significance.
- Cognitive Analytics extracts information from non-structured data, can infer new data and can communicate with humans.
Big Data
IBM defines5 Big Data as:
“…Big data is a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage and process the data with low latency. Big data has one or more of the following characteristics: high volume, high velocity or high variety. Artificial intelligence (AI), mobile, social and the Internet of Things (IoT) are driving data complexity through new forms and sources of data. For example, big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media — much of it generated in real time and at a very large scale.
Analysis of big data allows analysts, researchers and business users to make better and faster decisions using data that was previously inaccessible or unusable. Businesses can use advanced analytics techniques such as text analytics, machine learning, predictive analytics, data mining, statistics and natural language processing to gain new insights from previously untapped data sources independently or together with existing enterprise data…”
Parallel Computing6 as defined by Techopedia:
Parallel computing is a type of computing architecture in which several processors execute or process an application or computation simultaneously. Parallel computing helps in performing large computations by dividing the workload between more than one processor, all of which work through the computation at the same time. Most supercomputers employ parallel computing principles to operate.
Parallel computing is also known as parallel processing.
Cloud Computing
Deloitte provides a definition of Cloud Computing7: by transferring software and hardware management to a third party provider:
With cloud computing, you eliminate those headaches that come with storing your own data, because you’re not managing hardware and software — that becomes the responsibility of an experienced vendor like salesforce.com. The shared infrastructure means it works like a utility: you only pay for what you need, upgrades are automatic, and scaling up or down is easy.
Cloud-based apps can be up and running in days or weeks, and they cost less. With a cloud app, you just open a browser, log in, customize the app, and start using it.
Businesses are running all kinds of apps in the cloud, like customer relationship management (CRM), HR, accounting, and much more. Some of the world’s largest companies moved their applications to the cloud with salesforce.com after rigorously testing the security and reliability of our infrastructure.
As cloud computing grows in popularity, thousands of companies are simply rebranding their non-cloud products and services as “cloud computing.” Always dig deeper when evaluating cloud offerings and keep in mind that if you have to buy and manage hardware and software, what you’re looking at isn’t really cloud computing but a false cloud.
The three types of cloud computing
Infrastructure as a Service (IaaS)
A third party hosts elements of infrastructure, such as hardware, software, servers, and storage, also providing backup, security, and maintenance.
Software as a Service (SaaS)
Using the cloud, software such as an internet browser or application is able to become a usable tool.
Platform as a Service (PaaS)
The branch of cloud computing that allows users to develop, run, and manage applications, without having to get caught up in code, storage, infrastructure and so on.
There are several types of PaaS. Every PaaS option is either public, private, or a hybrid mix of the two. Public PaaS is hosted in the cloud and its infrastructure is managed by the provider. Private PaaS, on the other hand, is housed in on-site servers or private networks, and is maintained by the user. Hybrid PaaS uses elements from both public and private and is capable of executing applications from multiple cloud infrastructures.
PaaS can be further categorized depending on whether it is open or closed source, whether it is mobile compatible (mPaaS), and what business types it caters to.
When choosing a PaaS solution, the most important considerations beyond how it is hosted are how well it integrates with existing information systems, which programing languages it supports, what application-building tools it offers, how customizable or configurable it is, and how effectively it is supported by the provider.
As digital technologies grow ever more powerful and available, apps and cloud-based platforms are becoming almost universally widespread. Businesses are taking advantage of new PaaS capabilities to further outsource tasks that would have otherwise relied on local solutions. This is all made possible through advances in cloud computing.
Traditional business applications have always been very complicated and expensive. The amount and variety of hardware and software required to run them are daunting. You need a whole team of experts to install, configure, test, run, secure, and update them.
When you multiply this effort across dozens or hundreds of apps, it’s easy to see why the biggest companies with the best IT departments aren’t getting the apps they need. Small and mid-sized businesses don’t stand a chance. The affordability of cloud-hosted data makes it an essential tool for these types of situations. Here are some other benefits of cloud computing.
Adaptable
- Cloud computing allows for adaptable programs and applications, that are customizable, while allowing the owners control over the core code.
Multi-tenancy
- Cloud software provides the opportunity to provide personalized applications and portals to a number of customers or tenants.
Reliable
- Because it is hosted by a third party, businesses and other users have greater assurance of reliability, and when there are problems, easy access to customer support.
Scalability
- With the Internet of Things, it is essential that software functions across every device and integrates with other applications. Cloud applications can provide this.
Secure
- Cloud computing can also guarantee a more secure environment, thanks to increased resources for security and centralization of data.
Internet of Things
Forbes describes the Internet of Things (IoT) as:8
“…is the concept of basically connecting any device with an on and off switch to the Internet (and/or to each other). This includes everything from cellphones, coffee makers, washing machines, headphones, lamps, wearable devices and almost anything else you can think of. This also applies to components of machines, for example a jet engine of an airplane or the drill of an oil rig. [As I mentioned,] if it has an on and off switch then chances are it can be a part of the IoT. The analyst firm Gartner says that by 2020 there will be over 26 billion connected devices... That's a lot of connections (some even estimate this number to be much higher, over 100 billion). The IoT is a giant network of connected "things" (which also includes people). The relationship will be between people-people, people-things, and things-things…”
With a common nomenclature, the next step is understanding Robotics, and, much like the 2nd Industrial Revolution mechanized production, Robotics applied to accounting, eliminates the repetitive, error prone accounting processes for general ledger and auditing functions.
Robotics
McKinsey 9, when interviewing Leslie Wilcox of the London School of Economics, provides the best definition of Robotics Process Automation (RPA) in accounting:
“…RPA takes the robot out of the human. The average knowledge worker employed on a back-office process has a lot of repetitive, routine tasks that are dreary and uninteresting. RPA is a type of software that mimics the activity of a human being in carrying out a task within a process. It can do repetitive stuff more quickly, accurately, and tirelessly than humans, freeing them to do other tasks requiring human strengths such as emotional intelligence, reasoning, judgment, and interaction with the customer… RPA deals with simpler types of task. It takes away mainly physical tasks that don’t need knowledge, understanding, or insight—the tasks that can be done by codifying rules and instructing the computer or the software to act…”
KPMG discusses RPA in different levels:10
- Basic automation where RPA works with the current business, sits on top of the current information technology architecture and mimics human transactions. They are easy to implement but may not be the most effective option.
- Data extraction using unstructured information and relying on machine learning.
- Cognitive Automation, where data is ingested and analyzed, reasoned and problem solving. While it does remove human errors, it does not remove humans from the process.
Ernst and Young (E&Y) considers RPA as a continuum with different levels of sophistication and associated cost savings:11
- Basic –10-20% savings
- Enhanced (data extraction) 35-50%
- Cognitive Automation >60%
E&Y states that RPA, among other benefits, can work 24/7 with no errors, ensure adherence to regulations, and improve customer satisfaction. It can be used across any number of industries and relies on the ability to identify and clearly articulate the business processes to develop systems.
Deloitte, compares of how humans and robotic processes would process the same task.12
The client ran a comparative analysis of 10 employees preparing work in progress (WIP) reports vs a robotic system using the same data. Employees took 10-15 minutes to prepare each case: the robotics system ran at an average of 4 minutes per case, with a .02 error rate, due to missing data. The robot would direct the missing data request to the employees for resolution. By removing the tedious WIP reports, the employees could focus on the analytical tasks.
Deloitte further defines robotics as suitable for: seasonal work with unpredictable peaks and valleys; repetitive error prone work; high volume, and is rule based not requiring additional analysis.
Strategic Finance 13 provides tips for how to manage the robotic process:
- Analyze the current state of end to end processes;
- Design the future state;
- Optimize and automate processes;
- Review outcomes and controls;
- Continuously improve the new current state.
Strategic Finance also sees the general ledger function as moving from repetition to analysis:
- Data Import. First, the process-oriented robots pull and aggregate data from all connected sources: enterprise resource planning (ERP) systems, bank files, credit cards, point of sale (POS) software, and the like.
- Data Processing and Verification. After pulling in data from multiple sources, the robo-accountants perform data manipulations and calculations such as matching transactions between different systems, identifying fees, performing depreciation adjustments, certifying balances, and identifying suspicious fluctuations.
- Exception Management. Next, the robo-accountants identify exceptions. If the task robots can’t solve discrepancies, data is forwarded to a human accountant for further investigation.
- Reporting and Analysis. Robots then use the data to create reports and perform preliminary analysis. Humans perform secondary and more in-depth analysis.
- Auditing. Because the robo-accountants have performed most of the manual work, human accountants now have plenty of time to focus on ensuring integrity, accuracy, and audit functions instead of looking for and correcting human errors.
According to the CPA Journal, for auditing, robotics is applicable to processing important but repetitive functions, such as revenue account reconciliations.14 Automating, removes the repetitive task and allow the audit focus on analyzing the audit results.
1https://www.weforum.org/agenda/2016/01/the-fourth-industrial-revolution-what-it-means-and-how-to-respond/
2https://commons.wikimedia.org/wiki/File:Industry_4.0.png
3https://www.ey.com/Publication/vwLUAssets/ey-faas-finance-function-automation/$FILE/ey-faas-finance-function-automation.pdf
4https://www2.deloitte.com/nl/nl/pages/data-analytics/articles/part-1-artificial-intelligence-defined.html
5https://www.ibm.com/analytics/hadoop/big-data-analytics
6https://www.techopedia.com/definition/8777/parallel-computing
7https://www2.deloitte.com/mt/en/pages/technology/articles/mt-salesforce-what-is-cloud-computing.html
8 https://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-things-that-anyone-can-understand/#157272cb1d09
9https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/the-next-acronym-you-need-to-know-about-rpa
10https://home.kpmg/in/en/home/services/advisory/management-consulting/robotic-process-automation.html
11https://www.ey.com/Publication/vwLUAssets/ey-robotic-process-automation-white-paper/$FILE/ey-robotic-process-automation.pdf
12https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/finance/deloitte-uk-finance-robots-are-coming.pdf
13https://sfmagazine.com/post-entry/november-2017-are-you-ready-for-your-robots/
14https://www.cpajournal.com/2018/07/02/how-robotic-process-automation-is-transforming-accounting-and-auditing/