Question

Discuss thoroughly at least 3 benefits and 3 risks of the fast-paced move to automation in accounting using at least one specific technology. Please do not include topics already discussed by you in this quiz or the last one.

Answer 1

3 benefits and 3 risks of the fast-paced move to automation in accounting using at least one specific technology: -

One specific technology is AI

AI allows machines (bots) to learn from experience, interpret information, make adjustments and apply what they “know” to perform human-like tasks.

• Machine learning (ML) gives computers the ability to recognize and apply patterns to develop algorithms that they can then fine-tune based on feedback; an example is HotStar that can offer you suggestions of what to watch based on your viewing history.
• Computers develop the ability to identify relationships and associations through deep learning.
• Machines first “understand” information and then they actually “think” of the implications of that data and analyze it with machine reasoning.
• Based on the understanding of human speech, natural language processing is used by computers.
• They “recognize” people, activities and objects, and “view” images with computer vision, an example is the iPhoneX that can recognize the face of its user.

AI Can Be Applied To Accounting

Finance should become a better strategic partner and value creator to the business – yet it tends to spend a majority of its effort processing transactions.

Artificial intelligence has the potential to transform the finance and accounting industries with advancements that eliminate tedious tasks and free human finance professionals to do higher level and more lucrative analysis and counseling for their clients. Yet, organizations hesitate to employ AI in their workforce due to uncertainties around the business case or return on investment.

3 benefits : -

1.) Machines Imitate The Human Brain

Automation, AI chatbots, machine learning tools, and other AI technologies are playing a leading role in the finance sector. Accounting and finance companies are making them a part of their business by investing heavily in these technologies.

According to researchers, AI apps and ML apps are impacting the accounting & finance professionals and their everyday jobs. Using AI and ML, finance experts can improve productivity and deal with new clients.AI can replace humans from the monotonous job of extracting, organizing, and structuring the data. But those same accountants and auditors working with AI can perform different tasks. First, they teach the AI what data to look for and how to organize it. Then they investigate anomalies. Thus, AI can take on the tedious work that takes up so much time – data entry and reconciliation – and also eliminate errors, reducing liability. With the mundane tasks handled, accountants will be free to engage in more advisory roles

2.) Fighting Misrepresentation

With the help of machine learning algorithms, payments companies can analyze more data in new and innovative ways to identify any hoax activity. Every consumer transaction includes uniquely identifiable information. With AI and machine learning, payments companies can search rapidly and efficiently through this data beyond the standard set of factors like time, velocity, and amount.

AI helps in efficiently processing huge amounts of data from different sources, look out for problematic transactions and relationships, and report them in a visual tool that, in turn, will allow the compliance team to handle such types of suspicious cases more effectively.

3.) AI Machines Perform Make Accounting Tasks Easier

According to a consulting firm Accenture, “Automation, minibots, machine learning, and adaptive intelligence after becoming a part of the finance team at lightning speed.”

Artificial intelligence machines automate accounting procedures far and wide. It ensures operational efficiency while reducing costs. As automation is accessing every corner of a company, the financial companies also adopt the digital transformation that will gain from the technology developments. The accounting and finance leaders who deployed AI will be ranked in the future of digital transformations.

For example, Xero, an accounting firm, has launched the Find & Recode algorithm that automates the work and finds common patterns by scanning code corrections. Using the algorithm, 90% more accurate results were found while analyzing 50 invoices.

Risks

Some of the main risks associated with AI include:

• Algorithmic bias: Machine-learning algorithms identify patterns in data and codify them in predictions, rules and decisions. If those patterns reflect some existing bias, the algorithms are likely to amplify that bias and may produce outcomes that reinforce existing patterns of discrimination.
• Overestimating the capabilities of AI: Since AI systems do not understand the tasks they perform, and rely on their training data, they are far from infallible. The reliability of their outcomes can be jeopardized if the input data is biased, incomplete or of poor quality.
• Programmatic errors: Where errors exist, algorithms may not perform as expected and may deliver misleading results that have serious consequences.
• Risk of cyber attacks: Hackers who want to steal personal data or confidential information about a company are increasingly likely to target AI systems.
• Legal risks and liabilities: At present, there is little legislation governing AI, but that is set to change. Systems that analyze large volumes of consumer data may not comply with existing and imminent data privacy regulations.
• Reputational risks: AI systems handle large amounts of sensitive data and make critical decisions about individuals in a range of areas including credit, education, employment and health care. So any system that is biased, error-prone, hacked or used for unethical purposes poses significant reputational risks to the organization that owns it.