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The Importance of Big Data in Accounting

Big data and AI are transforming the accounting industry, with 62% of accountants claiming that current accounting training programmes will not suffice to run a successful practice by 2030 . Data-driven accounting has the potential to greatly improve decision-making and profitability for businesses across the world.

This is done by leveraging insights from the analysis of big data to influence positive outcomes through a deeper understanding of clients’ businesses. Through the analysis of big data, businesses can ultimately improve risk management and compliance to gain a competitive advantage in today’s market. 

In this blog we take a look at the importance of big data in accounting and how utilising it can prove beneficial for the future of the finance sector.

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What is Big Data?

Big Data is frequently used as a buzzword referring to the vast quantity of data generated every minute as people use the internet. American computer tech giant, Oracle, defines big data as “data that contains greater variety, arriving in increasing volumes and with more velocity”. 

Also known as the 3 V’s of big data (volume, velocity and variety), volume refers to the huge amount of data available, velocity refers to the speed of data processing and variety refers to the different types of data available. These factors make up the three defining properties of big data, and they’re crucial in understanding how we can measure data, and how much they differ from ‘old fashion’ data we’re used to collecting.

In today’s digital world, there’s tons of data being created by diverse sources, which can be a great benefit for data-driven businesses. Generally, any organisation which stores its customers’ data can employ big data analytics to identify new business opportunities or develop targeted sales and marketing campaigns. 

Most social media platforms also employ this to provide users with more targeted content by collecting large amounts of user-generated content relevant to their online activity. This data is then used by the platform's algorithm to create more personalised content feeds and make ad suggestions based on each user’s interests. 

However, by nature, big data is unstructured, unorganised and just way too complicated for past technologies to process effectively. This, therefore, brings to the forefront modern technological developments, including AI concepts, such as machine learning and natural language processing. These concepts have the capacity to develop advanced data analytics technologies to effectively gather, organise and analyse big data, drawing out trends and themes easier. 

But, what does big data mean for accountants?

Analysing big data allows accountants to gain a deeper insight of the clients’ businesses to make more informed decisions ultimately leading to improved financial forecasting, enhanced risk management and more accurate financial reporting. 

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How can big data improve accounting practices?

1) More accurate auditing

Currently, accounting firms are utilising “audit sampling”, where a representative sample of data from a larger data pool is selected in order to identify potential issues or trends in a company’s transactions or invoices. While this type of auditing can help cut costs and time compared to conducting a full audit with all available data, this method is not as accurate but rather more representative. 

Big data however, outperforms “audit sampling” by a mile when it comes to detecting outliers within a greater trend, with outliers referring to data points that are significantly different from other observations in a given data set. With big data analysis, these exceptions are taken on for further analysis to better understand and define the issues. 

McKinsey & Company identified that companies which make intensive use of data analytics are 23 times more likely to gain new customer acquisitions, outperforming their competitors, while they’re also 19 times more likely to be profitable. 

It’s worth noting that identifying outliers helps companies focus on areas that are deemed more high risk and make predictions that will improve forecasting. Not only that, but by automating auditing through big data analysis, the risk of human error is significantly minimised, leading to outcomes with increased accuracy and compliance. 

While eliminating a large effort of manual labour by employing the use of algorithms, machine learning and AI, auditors and accountants alike can access huge volumes of unstructured data such as emails, company statements etc to draw such accurate results.

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2) Tracking business performance

Companies can utilise big data analysis to aggregate their performance metrics, comparing them to those of their competitors, as it has the capability to do so across an entire industry. This can help understand why the competition might be outperforming their own metrics, through tangible, evidence-based data. 

This, in turn, enables companies to define new KPI’s to stay on top of the competition and stay relevant in the industry, through the identification of market trends and gaps. According to a survey conducted by ACCA and IMA, 62% of companies globally support that big data is “hugely important to the future of businesses”, with the potential of gaining “ an edge on their competitors”. 

Recognising trends in customer behaviour can also enable companies to hone into consumer expectations, allowing them to take action in improving the customer experience with better and more accurate services, increasing customer satisfaction and loyalty as a result. 

Sales divisions, in particular, can greatly benefit from this, as it enables them to identify how they can target their customers more effectively. According to a 2020 sales operations survey performed by Gartner, Inc, 42% of sales leaders rate the ROI of their sales analytics significantly higher than expected. 

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3) Improved risk management

It goes without saying that a huge part of a company’s success in today’s industry hugely relies on its ability to identify and rectify potential risks to the company early on to avoid any hazards pertaining to mergers and acquisitions, fraud, supply-chain risks and so on. 

Through the utilisation of big data analysis, risk management can be significantly improved, providing real-time insights with regards to customer behaviour changes, as well as foreseeing shifts in economic trends and cash flow. 

With companies getting ahead of potential hazards, they now have the ability to draft action plans that will effectively manage external shifts and reduce internal risks. By engaging with big data, this can be achieved quickly and accurately, and when it comes to risk management, the sooner it’s identified the better the chance of alleviating the risks is. 

4) Informed decision-making 

Since the introduction of advanced computing systems and softwares, accountants have steered away from mundane and repetitive tasks such as creating balance sheets or opening and closing accounts. They are now taking on business advisory roles where they’re liable for creating financial plans and providing valuable insights. 

By employing big data analysis, companies can identify potential business prospects in real-time. Considering that market trends frequently change , what a product or service offers at a given time, may no longer be relevant with market demands once auditing has been finalised. So, having the opportunity to extract such data rapidly can help cut costs, lead to better market performance and boost customer engagement and retention.

Leading European analyst firm BARC identified in their own research that 69% of worldwide companies perceived better strategic decisions to be a top benefit of big data analysis, while 52% stated that having a better understanding of customers was also a huge benefit. 

Access to real-time data essentially puts a company in sync with the industry trends calendar, enabling them to make better business decisions, while also establishing useful and accurate performance benchmarks.

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What does the future of the accounting profession look like?

With AI and automation becoming increasingly integrated in industry practices, much uncertainty appears to remain regarding the future of the accounting profession in the digital era. There is no doubt that accountants will still be in demand in the future, however, the role will change and different skills and capabilities will be called for, such as:

  • Analytical thinking
  • Critical thinking
  • Creative thinking
  • Problem-solving
  • Communication
  • Collaboration 

Automation, as already mentioned, will reduce the demand for repetitive tasks such as data entry and analysis to be performed by accountants and instead will be taken over by AI systems. Sage’s Practice of Now 2020 report suggested that 45% of accountants intend to automate repetitive and time-consuming tasks, freeing up time for them to take on more business advisory and strategic roles that can impact their organisation’s decisions. 

For that reason, accounting skills will evolve to become more creative and innovative, calling for accounting professionals to train and upskill in order to stay on top of industry demands and expectations. 


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