How Big Data Impacts Accounting?

In recent years, Big Data has carved its way into becoming a household lingo in both technical and industrial world along with their contemporaries. Every year, sheer voluminous amount of data is generated from a wide set of sources ranging from applications to organizations. This data is usually accessible to personnel working in big data analytics functions in a wide range of operations. Thanks to the advancement in technology, one can quickly analyze and extract valuable insights from the data. These insights are an excellent opportunity for businesses to use it to create strategies for their future planning.

Given the enormity of the data, its prioritization loosely focuses on the certain crucial factors, viz,

•  Variety: sources that accumulate data from multiple points like devices, sites. The data can be in structured, semi or unstructured format.

•  Velocity: rate at which it can be identified and collected

•  Veracity: reliability of the sources to check for inconsistency, vagueness and incorrect information

•  Volume: the quantity of the data that can be handled and processed.

Hence, it is a no-brainer that emphasis leans towards excellent variety, with high velocity and veracity paired with ginormous volume.

Exploring the scope in Accounting

Gone are the times when big data analytics was an uncharted territory. Now there is a rising reliance on it to streamline better outcomes as it presents an opportunity for expansion and great service provision. Accounting is one of the major patrons where objectivity lies in minimizing budgetary costs, providing improved accuracy all while saving time to maximize productivity.

Earlier the accounting firms had to undergo a tedious routine of collecting data in person or via machines then analyzing a local set of data to calculate profit and return on investment much like a traditional bookkeeper.

Now, accounting firms typically use the concept of audit sampling to detect issues or trends in transactions or invoices and potential risk factors. Additionally, big data analytics can excel at identifying exceptions and outliers within a larger trend. Accounting firms can then focus their efforts on those exceptions for further analysis.

Smaller firms do not have access to resources like their larger counterpart, however, cloud computing makes it is possible to extract the data and records from anywhere, at any time on a monthly, quarterly, or annual basis. This real-time availability enables to transcend in numerous ways such as decision-making, locating problem point, monitoring performance, trends prediction, understanding market competition by authorities, which was previously deemed impossible.

In scenarios involving mergers and acquisitions, fraudulent activities, supply chain risks, and much more, big data can help by introducing liquid risk management, credit risk management, card fraud detection, etc. this is achieved by studying the credit inflow and outflow, peak hours, transactional status and previous suspicious  activities, etc. This meticulous contemplation can then identify any occurrence of fraud or illegal activities and thus mitigate the perils associated.

Big data can also build analytical models that support a variety of product or operational improvements. This is largely useful during campaign programs. Agencies can evaluate the existing consumer behavior and demands, inspect the mannerism of their competitors by studying aggregate performance metrics. Based on this observation, organizations can devise a plan that will ease targeting the 'perfect audience' or subject and then reach them via various channels to bring feasible results coupled with long-term loyalty. Sometimes this information can be utilized in figuring out the influential factors or users, which may assists in bringing an economical shift towards them, thus giving an edge over competitors through brand awareness.

Backed by statistical expertise, qualitative accuracy and strategical experience, clients can look into opportunities to reap benefits of big data for making an informed decision. Such instances can equip themselves to delve into options that will be significant in taking the firm or companies forward, as it helps them grasp what will bring desired outcomes and what would not, instead of considering hypothetical situations and imaginary steps. This is crucial in shaping the economy of a company at the domestic and at international levels.

Conclusion

Accounting is a data intensive sector. It requires skilled personnel with ability to understand data and analyze them to produce tangible solutions. Big data tries to fuse industry specific data with strategy. As a result, it is the need of the moment to leap on this opportunity lest one does not wish to miss the wave while it is hitting the technologically advanced shores.