In today’s wired world, literally, everything is connected and every single communication of information is recorded as ‘data’. With the generation of massive volumes of data, commonly known as Big Data and increasing availability of low cost technologies to access and process such data, ‘Analytics’ seems to be pervading all facets of life, both in the public and private sectors.
Analytics is the discovery, interpretation, and communication of meaningful patterns in data. This is done by the application of statistics (including visualisation), computer programming and operations research to quantify business performance. Many organizations apply analytics today to the business data to describe, predict, and improve business performance.
Analytics include predictive analytics, prescriptive analytics, enterprise decision management, retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix modeling, web analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and fraud analytics.
Retailing and banking sectors were the early birds and was followed by other areas like medicine, social media. Assume a retail supermarket scenario, where by enrolling a particular customers as members, every single purchase of the customer is recorded, over a period of time. By applying analytics on this data, customer behavioral patterns could be drawn. These insights can be used to improve the overall service deliveries and to come up with individual customer specific offers for better advertisement and sales. Similarly, with the availability of past consumer datasets, a banking firm can actually predict future defaulters or profitable consumers, thereby improving profitability. Such is the potential of Data Analytics.
Public sector also, is soon realising the potential of Big Data and its Analytics. Big Data and Analytics are words nowadays normally being used in public sector across the globe. The Supreme Audit Institutions (SAIs) of various countries are no exception to this. Data Analytics is opening up new opportunities and challenges in the field of Public Audit.
Data analytics enables auditors to work on 100% of the transactions instead of a sample. With visualisation, even a non-specialists can quickly view the results graphically, easily, and have a better understanding of the audited entity. This enables auditors to improve the risk assessment process, substantive procedures and tests of controls, thereby improving audit quality. Data analytics, though often involves very simple procedures it also includes building complex models that produce high-quality projections. The challenge here is the auditors using such models need to understand them, and to exercise significant judgment in determining when and how they should be used, which is a challenge in every sector.
The challenges, however seem to be the need for balancing the requirement of good quality audit evidence from the analyses, considering the quality of the analysed data. Another challenge is to decide on the most suitable analytics model for providing the best audit evidence and the uncertainty regarding regulatory challenge, in this regard. However, it is an accepted fact that the auditor has to keep pace with the changes in the audit environment; and hence Data Analytics is to be ingrained into the audit discipline.
SAI India, i.e., the institution of Comptroller and Auditor General of India (CAG), realizing the potential of data analytics in the transformation of audit processes came out with the Big Data Management Policy of the Indian Audit and Accounts Department in 2015. The policy addressed identification of data sources, establishing data management protocols, digital auditing, data analytics and visualization strategy and infrastructure, capacity building and change management.
In line with the policy, CAG also set up a task force to prepare a plan of action for implementation of the policy in the organization. Based on the task force’s recommendation data analytics is being introduced across the department as a discipline. This includes empowering the auditors with data analytic techniques and encouraging them to use open source tools. A Centre for Data Management and Analytics (CDMA) has also been established in the office of the CAG of India. Separate data analytic groups have been set up in all jurisdiction/sector specific audit offices of the SAI. The SAI is now involved in capacity building on data analytics in the department in a big way.
Data Analytics is an emerging field world over, which involves a lot of trial and errors. Though there is increasing move towards Data Analytics, concrete case studies are important to demonstrate the utility of Data Analytics in improvement of service delivery, in the public sector. Hence, the CDMA is experimenting the application of data analytics on a few data rich audit assignments, identified by the SAI, India.
Data Analytics begins with access to data. It also includes tapping the potential of linkages between multiple datasets. The importance, necessity and methodology of mapping and managing the relevant internal (SAI India) and external (Audited entities and third parties including NGOs and private institutions) sources of data, as described in the Big Data Management policy forms one of the cornerstones in use of data analytics by SAI, India.
SAI India foresees an orbital change in the way external audit functions, with the introduction of Data Analytics. This initiative will play a catalytic role in enhancing the efficiency and accuracy of evidence in the audit process and be a game changer in the field of public audit.