source : KPMG Internal Audit

 

As companies continue to navigate rapidly changing business models, regulatory requirements, technology disruption, and more, the opportunity for Internal Audit (IA) to identify and help companies respond to risks is ever-increasing. In fact, IA can play an important role in helping organizations manage the risk environment while also making progress on strategic and growth priorities. To provide the greatest value, IA must find opportunities to challenge the status quo to reduce risk, improve controls, and identify potential efficiencies and cost benefits across the organization.

To help IA functions achieve these goals, we present KPMG Internal Audit: Top 10 in 2020, which outlines areas where IA should focus so it can effectively add value across the organization and maximize its influence on the company.

 

2. Data analytics and insights

As companies continue to optimize the value of and insights arising from the tremendous amount of data housed in the business environment, ensuring proper controls around the use and storage of data is critical. Effective data governance enables a top-down, enterprise-wide view of big data.

It addresses questions over data ownership and ensures adherence to policies that govern which data is important and how data is created, stored, aggregated, warehoused, analyzed and used. Data governance is critical to maintaining data privacy and helping the business turn data into insights.

Although IA must maintain an adequate degree of separation from management responsibilities, opportunities exist to work with management to expand the use of data analytics in the business and within the IA process. Those responsible for operations, compliance, and financial reporting have generally increased their use of data analytics in executing their responsibilities. IA can often leverage these platforms or assist in a consulting role to help improve related processes and controls.

Using data to perform analytics in the internal audit process can enable expanded risk coverage and audit scope as well as improve testing precision. Repeatable and sustainable data analytics can help IA simplify and improve the audit process, resulting in higher quality audits, increased value to the business, and more precise control evaluation. By enabling IA to evaluate a greater number of controls, resulting in greater coverage, data analytics can help IA respond to audit committees and stakeholders that are asking them to do more with less.

 

How internal audit can help:

— Use data analytics to identify current and emerging risks as part of the risk assessment process
— Perform automated auditing focused on root cause analysis and management’s response to risks
— Assist in the formation or review of data governance policies and processes
— Review the data model and points of control, including data classification issues, to identify security gaps
— Assist in creating automated extract, transform and load (ETL) processes, along with repeatable and sustainable analytics and dashboards, enabling auditing or monitoring against specified risk criteria

 

Drivers:
— Leveraging advanced big data tools and techniques to adapt quickly to rapidly evolving business demands
— Complying with global business and regulatory data requirements
— Leveraging big data technology and methodologies to improve audit quality and precision, reduce audit costs, and expand risk coverage and audit scope
— Enabling real-time identification of risks and remediation of control weaknesses

 

 

Date of Input: 23/01/2020 | Updated: 23/01/2020 | nurmiera