Data Management: Enhancing Processing Abilities

Time is money. Imagine being able to complete a week’s worth of work in an afternoon. This newly found freedom could be used to serve more clients, learn a new language, or simply destress. Artificial Intelligence (AI) has the capability to perform at that speed and manage data like never before.

The Big 4 accounting firms are constantly affected by data management and inconsistencies, that is why they are investing large amounts of capital into AI. These technologies are reducing manpower needed by providing tools to make employees work faster and smarter.

Increased Efficiency

An example of how AI is already proving its value to the accounting industry is through a process called Natural Language Processing (NLP) for document review (Zhou, 2017). This technology examines high volumes of legal documents, like contracts, and ensures compliance with any new regulations that have been put into place. Deloitte’s company-wide utilization of this feature has enabled the firm to shorten the process of compliance review from half a year, to only one month.

Increased Effectiveness

While Deloitte’s focus is on creating a more efficient way of completing data-heavy yet repetitive tasks with the fewest human labour hours, KPMG is using AI to create a dynamic and interactive experience. The creation of KPMG Clara, an AI platform that analyzes data and predicts trends visually, adds more value to the client relationship. This is because it provides information in a more practical way, allowing for greater learning for those utilizing it. Also, its ability to use predictive analysis to gauge risk and other future outcomes will give KPMG an edge in the services they offer.

The Benefits of Big Data

Accounting firms will also use AI for big data, which are extremely large datasets that can be combed for trends, patterns and associations (Oracle, 2018). Accountants will have access to more information than ever before. Hence, they will be able to diversify their services to address problems that could not have been solved before. All the various ways that AI has been introduced reflects well on the accounting industry and boosts the reputation of CPABC as an accepting and innovative governing body. With the continued positivity of these results, and through the support of CPABC, accounting can take advantage of this emerging technology to create a more enhanced and efficient professional service.

Responsibilities Associated with Data Management

While firms will have enhanced data analytics and processing abilities, increased ability comes with greater responsibility. More specifically, firms will be dealing with managing larger reserves of client data that their existing IT infrastructures may not be adept to handle. This presents a significant concern for CPABC as the regulating body preserving interests of clients, employees and the firms.

Since 2011, the financial sector in North America has already seen a 377% increase in the number of data breaches annually. Adoption of new technologies continue to place accounting firms in vulnerable positions prone to data breaches. Therefore, while automation reduces the risk of human error, it also introduces risks associated with data management. As larger reserves of data will be utilized, the due diligence performed by firms will need to be intensified and data security and privacy will become increasingly important. During this time period, CPABC will need to revisit the standard of care expected from existing IT infrastructures in accounting firms and the overall industry. CPABC will be faced with the tradeoff of supporting innovation within the accounting industry and protecting the best interests of clients.

 

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One thought on “Data Management: Enhancing Processing Abilities

  1. The article examines effective data management. While AI like ChatGPT can regurgitate information, truly understanding data requires human judgment. As tools advance, retaining nuanced analysis skills remains vital. Overreliance on artificial convenience risks losing sight of contextual interpretation. Achieving the optimal balance continues to be an ongoing human-AI challenge requiring ethical considerations.

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