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Big data

5 Ways Accountants Can Effectively Utilize Big Data

Jun 3rd 2019
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Big data has been so frequently discussed across industries and in the media that it feels like the most prominent buzzword of the last decade. Professionals are constantly promoting and emphasizing its benefits and value, but few seem to truly understand what it is or how it works.

Simply put, “big data” refers to large sets of data and information in which valuable insights can be pulled by external analysis.

For accountants, big data has the potential to glean valuable insights to make tax preparation more efficient, discover new methods of detecting fraud and help prevent identity theft. Additionally, analytics help accounting professionals see previously unnoticed or undiscovered patterns that can be used to determine better sampling processes for audits, predict which individuals are at a higher risk of identity theft and help improve forensic accounting procedures.

The challenge comes from figuring out how to effectively reap the benefits of big data.

Like many accountants, I hold expertise in several specialized fields. I possess a breadth of knowledge about auditing and forensic accounting, while others may be experts in fields like tax preparation and government or corporate accounting. We can speak extensively and enthusiastically about the benefits of big data, but we are still not data scientists ourselves.

This can generate uncertainty among accountants on how to incorporate big data within their firms or how to determine which steps to take when crafting an effective analytics strategy to meet their objectives. Here, I offer five key tips to accounting professionals on actions to take when approaching and utilizing big data:

1. Focus on Outliers and Unexpected Patterns

A forensic accountant with data analysis skills is trying to detect fraud by combing through a massive dataset of 100,000 individuals who have donated money to a charity. The accountant uses an algorithm to find individuals who have donated more than 25 percent of their annual income to the organization. As they go through the information, the accountant notices an intriguing outlier: an individual who donated $100,000 to the charity, despite reporting no annual income for that year.

Outliers can initially seem troublesome within datasets, but they often reveal more insight than what accountants may have been searching for in the first place, like the above donor who was potentially committing fraud.

Additionally, by focusing on patterns that may arise through analytics, like frequently used methods of payment, specific recurring amounts or common time periods when transactions were made, accountants can make better predictions about future financial activity.

2. Create Visuals that Emphasize Insights

The biggest value of big data is its ability to illuminate previously unseen insights, but that data is effectively useless if people don’t understand the insights they are seeing.

Several analytics software programs can offer the ability to immediately view data in chart or graph form to give you a clearer picture of specific insights. These visualizations also help you explain what certain data represents to clients and other members of your firm.

One thing to keep in mind is that the accountant who is ultimately creating these charts should use visualizations that are appropriate to that particular dataset. Building a bar graph when a scatter plot would have been more effective will only lead to insights and the overall data being misconstrued.

3. Anticipate Additional Initial Costs

It will cost more than a yearly license for Microsoft Excel when your firm decides to adopt a big data strategy. You will likely have to hire more employees, spend more on outside vendors and firms and invest in more robust technology, all of which can come with a hefty price tag.

In light of this, make sure your firm can make the necessary monetary investment into big data in the first place by evaluating and projecting initial costs and how they may fluctuate over time.

4. Prioritize Security

Stories of data breaches and hacks at major companies have dominated the news cycle over the past few years, echoing the difficulties in maintaining effective cybersecurity.

As your firm gathers and analyzes big data, it is of the utmost importance that proper cybersecurity protocols are in place to ensure that your data is secured, even if it seems like information attackers would not be interested in. These protocols can include external consulting with cybersecurity firms, as well as establishing internal best practices for handling sensitive data.

5. Make Sure You Have the Right Team

Most accountants do not have a data analytics background. If firms want to adopt a big data strategy, they will likely need to hire accountants fresh out of school who currently possess that knowledge or train existing ones to obtain that skill set. If there isn’t anyone on your team who can analyze the data you possess, start planning for this deficit now, before implementing your new strategy.

Not able to hire anyone else? Figure out when you’ll have the time to take the training yourself. The key here is to prepare before rather than scramble to learn after.