What is Accounting Data Analytics – Benefits, Challenges

Priya Naha

Senior Writer

Accounting Data Analytics

Accounting and data analytics go hand in hand in the finance sector. Recently, the word big data has been quite a buzz. But do you even know what big data is?

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Big data is the collection of large and complex data that is hard to be analyzed using any traditional database or tool. It is also often referred to as data analytics or analysis. Today, we have access to an unprecedented amount of data. About 2.5 quintillion bytes of data are produced daily.

As per the IMA report, 62% of companies globally claim that big data plays a significant role in deciding the future of business.

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Expert Advice

Companies must use data analytics in accounting to gain valuable insights into their financial performance and identify opportunities for growth. By leveraging data analytics tools, companies can analyze financial data in real time and make informed decisions based on accurate information. Data analytics can also help companies identify trends, patterns, and anomalies in their financial data, which can inform strategic decision-making and improve overall business performance. In today's data-driven world, companies that fail to adopt data analytics in their accounting processes risk falling behind their competitors and missing out on valuable opportunities for growth.


Technological advancement has enabled us to quickly analyze and derive new insights from the data. The manufacturing, retail, and services sectors are already trying to capitalize on big data to increase work efficiency and assess risk factors.

However, it has now spread to the accounting and financial sectors too. But what role does it play in accounting with data analytics? Let’s read on to know more about data analytics in accounting.

What is Accounting Data Analytics?

Accounting data analytics is extracting financial data for insights using cutting-edge technologies and analytical methods. Modern firms depend on data analytics in accounting to enhance their financial management and decision-making procedures.

Accountants utilize data analytics to evaluate market behavior, spot patterns in consumer spending, foresee trends, and forecast regulatory responses. Accountants with expertise in data analytics control, examine, and mine various data streams.

Role of Data Analysis in Accounting

The rise of big data is a real game-changer. Gone are the days when accounting professionals were only responsible for making and filing entries.

The finance team is now also responsible for extracting insights from financial data to help strategically plan business moves and drive operational efficiency. It’s safe to say that bookkeeper has now evolved into a strategic business partner.

Before big data, finance departments used to analyze the data using software or known techniques to calculate profitability and return on investment. It was done using traditional tools such as spreadsheets

However, now they are required to analyze semi and unstructured data from other departments with the help of predictive analytics software. 

An accountant is accustomed to organizing and summarizing data to give an overall view of the company’s performance. They summarize the details of each transaction, which qualify them to understand data analytics skills better.

Besides, they can easily study the statement and see the larger context while drawing the company’s performance status.

Use of Data Analytics in Accounting and Finance

In other words, they can make decisions after drawing insights from data analysis. They understand your business’s context in-depth, which allows them to reach a business implication. 

Most importantly, they understand the different types of data analysis involved –from descriptive to predictive and prescriptive analytics.

They can easily jump from descriptive analytics to predictive ones and provide the necessary information to make key business decisions. Essentially, they have the mindset of a data scientist, studying your business data and reaching a conclusion.

How does Accounting Data Analytics Work?

The process of utilizing statistical tools and methodologies to draw conclusions and trends from financial data is accounting data analytics. Large amounts of financial data are gathered, handled, and analyzed to aid organizations in making wise decisions.

Gathering financial data from numerous sources, including systems for accounting, financial statements, and other pertinent documents, is the first step in data analytics in accounting.

How does Accounting Data Analytics Work?

 It is subsequently processed and cleansed to ensure the data is reliable and pertinent to the analysis.

Following data cleaning, several statistical approaches, including regression evaluation, variance analysis, and trend analysis, are used to analyze the data. The financial data can be analyzed using these techniques to find patterns and trends that can help guide decisions.

Accounting data analytics may be utilized to find insights and trends that can be leveraged to enhance financial performance, lower expenses, and spot risky areas.

What are the Benefits Of Data Analytics in Accounting?

The financial sector is one of the most data-intensive sectors in the global economy. So the impact of big data in accounting is naturally enormous. The global big data market is expected to reach $273.4 billion by 2026, with a CAGR of 11% from 2021 to 2026.

Benefits Of Data Analytics in Accounting

1. Data-driven Audits

One of the best data analytics in accounting examples is how it is evolving the auditing process.

Auditing is now much more than analyzing the income statement and the balance sheet. Moreover, in the past, an auditor might have had to manually scan through big files to monitor for risks. However, the advent of technology and data analytics has revolutionized auditing. Using technology, an auditor can now easily assess a large volume of unstructured data, such as emails, formal company records, and more.

2. Risk Identification and Management

Companies must regularly identify and assess the risk factors affecting their business performance.

Risks in financial services are generally associated with mergers and acquisitions, fraudulent activities, supply-chain risks, and much more. The advantage of big data analytics in accounting and finance is that it can significantly improve risk management by analyzing customer behavior, predicting shifts in economic trends, and much more.

Some examples of risk management include liquid risk management, credit risk management, card fraud detection, and more.

For instance, by analyzing the card transaction patterns, which include the amount, timing, location, and more, an accountant can identify fraudulent transactions and block the card.

In the case of liquid risk management, big data can give deep insights into the incoming and outgoing cash flow. The insights can be used to optimize liquidity management, which can greatly help the overall management of the bank.

Similarly, banks can reduce credit risk by analyzing transaction history and public information like companies’ annual reports. Based on these analyses, banks can improve credit models for individual and corporate customers and help them better manage the collateral of credits.

The sooner the accountants can identify these risks, the better the chance of mitigating them.

3. Provide Real-Time Reporting

Another significant impact of data analytics in accounting is the advent of cloud technology and real-time reporting tools.

Integrating big data and cloud technology has enabled accountants and auditors to provide real-time customer insights. They aren’t limited to analyzing financial records monthly, quarterly, or annually. With the availability of big data in real time, accountants can now provide timely insights.

Real-Time Reporting

Besides big firms, even small firms are trying to leverage the benefits of big data in accounting. Companies like Xero are providing cloud accounting software to small businesses to help them tap into the possibilities of big data in accounting.

4. Increase the Efficiency of Acquisition 

We often use mass marketing campaigns to promote business offerings. However, in today’s time, every marketing channel is overloaded with campaigns. So how do you make your campaign effective? 

Big data can target the right set of audiences through the right channel and message. You can easily segment prospects using big data based on the existing customer base. It allows you to target the right audience. And based on the segmentation of the prospect/target audience, you can determine the best media channel for the marketing campaign. It could be via email, radio, social media, and more. 

Besides, it can help you personalize messages and identify influential customers that can spread awareness about your financial services.

5. Improve Client Experience

The role of big data in accounting is not limited to creating future strategic planning but also optimizing customer relationships.

Data analysis in accounting gives you a clear view of the customer information, including their family information, bank details, history of their transactions and inquiries, and more. These insights can help you build an in-depth conversation with them, leading to a strong customer relationship.

Furthermore, you can create targeted offers for your existing customers. This will help you enhance your customer loyalty

Analyze their spending habits or buying behavior, and partner with popular retailers to offer incentives. You can also create a premium service for your high-value clients and provide attractive offers to retain them. 

What are the Challenges of Data Analytics, and How to Fix Them?

There’s no denying that data analytics in accounting has much to offer. It has helped large enterprises grow revenue and optimize their performance. 

However, regarding data analytics in accounting, some challenges still need to be addressed. Let’s take a look.

Challenges of Data Analytics

1. Lack of Expertise 

The biggest challenge is that most accountants are not trained to study and analyze data. This is why several firms struggle with data analysis.

However, this challenge can be easily mitigated by providing the right training to your accountants. Emphasize the analytical ability during the hiring process so that an accountant focuses on upskilling their analyzing capabilities.

2. Inaccuracy of Data

When data entry is done manually, there is a high risk of error. It can lead to faulty analysis, resulting in some bad decisions. 

That’s why it’s essential to resort to a centralized database whereby all data from different sources are stored. And with the help of an application, data gets analyzed, allowing accountants to derive some insights from the same.

This will ensure that the information imparted is corrected without risking the organization’s future.

3. Lack of Support

There needs to be proper coordination among all departments to properly collect data. If the organization’s support is missing, it can be difficult to generate actionable insights.

Accountants and risk managers will be clueless without support from the top to lower-tier employers and employees. Executives need the ability to act on this data. By emphasizing the value of accounting data analytics and the benefits it brings to the table – they are more likely to cooperate. Communicate value to efficiently achieve the trust of various stakeholders involved.

4. Visual Representation of Data

For a proper understanding of data, there’s the need to present data in easy-to-grasp visual formats. It could be in the form of pie charts or graphs. Building these visual formats manually is impossible – pulling data from multiple sources and putting it together more so when a large amount of data is involved.

Thus, there’s a need to implement data analytical tools that automatically import data from multiple systems and generate reports at the click of a button. Most advanced systems even offer real-time analytics views to make some immediate decisions.

However, implementing a data analytical tool might have another challenge – budget. 

5. Inadequate Budget 

Another challenge involved in accounting data analytics is budget. Data analytics tools can prove to be costly, and at the same time, employees aren’t skilled in using these modern applications. Thus, getting approval for this substantial purchase of accounting software gets difficult. 

Accountants need to measure the return on this investment and make a strong business case to get approval. 

Latest Trends in Global Accounting Data Analysis

Much has been said about the importance and challenges of accounting data analytics. It’s time to look at some trends associated with a global accounting system.

Accounting software comes equipped with various tools that help with various accounting and financial functions, including accounts payable, ledger maintenance, billing, and invoicing modules. With technological advancement, modern solutions come with AI-driven data analytical tools – enabling you to collect, store, and organize data to derive meaningful insights for smart business decision-making. Here are some statistics involved. 

1. Trends of Big Data Analytics in Accounting

The growth of the global accounting software market has been on an upward trend since 2010. The actual numbers have surpassed the projected market growth numbers every year.

Big Data Analytics

 The year-on-year growth has been phenomenal because of the increasing need for firms to automate routine accounting tasks and bookkeeping so that financial and accounting professionals have more time to focus on decision-making and scientific analysis of financial data.

2. Deployment Practices

The popularity of on-site or on-premises accounting software has dropped significantly. Nearly 70% of the accounting software used today is cloud-based or web-based.  Many companies are shifting from on-premise to web-based cloud accounting software for better collaboration, connectivity, accessibility, and security. 

3. Advanced Functionalities

Artificial Intelligence, machine learning, and advanced analytics are finding increased application and will soon be widely used, as with most other software.

4. Industry-wise Popularity

Accounting software is becoming increasingly important for better inventory management and point-of-sale transactions in established fields such as retail and manufacturing. Small and medium enterprises are also witnessing considerable growth in their usage of accounting software. 

With automation, more firms want to save on manual labor and cut out mundane, repetitive tasks. And in tasks like bookkeeping and record-keeping, accounting software has been immensely helpful to users.

However, security and cost inefficiency remain major threats to accounting software worldwide. Due to increasing cyberattacks, accounting software builders must beef up their security offerings to provide a robust accounting solution to firms as the software handles sensitive financial data.

Cloud and mobile-based applications have been the most widely accepted trends for accounting software in the past year. Quickbooks, Freshbooks, Zoho Books, Sage, and Odoo, remain the top sellers in the accounting software market, their popularity driven by adapting to the cloud model.

Here’s a detailed infographic for an easy understanding of global accounting software usage.

Final Words

Big data in accounting is all about creating values. Accountants and financial professionals are designing the movement of data, external and internal, for the betterment of the organization. However, everything comes with its challenges.

As more data becomes accessible, its value can depreciate rapidly. Furthermore, only access to this technology and information is not enough. Companies will need to make sure that it is properly implemented and used. Professionals must develop the skills to transition from an accountant to a data-savvy planner or analyst. 

Of course, it would mean imbibing a completely new mindset and skills. The sooner these firms embrace the shift in big data, the better they will be able to capitalize on the opportunities that accounting big data analytics will bring.

Frequently Asked Questions

Raw data is analyzed in accounting. Data analytics examines raw data to identify trends, patterns, and insights that provide valuable information about an organization's domain. The insights are then used to make informed decisions.

The common data analytics techniques used in accounting include:

  1. Descriptive analytics
  2. Diagnostic analytics
  3. Predictive analytics
  4. Prescriptive analytics

Accounting firms can get important insights, forecast potential outcomes, and automate accounting tasks by using data analytics on big data.

A prepared accounting job prospect requires expert financial and data analytics abilities.

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