Voices from the Field

OBJECTIVE CENTRIC RISK AND UNCERTAINTY MANAGEMENT IN THE PUBLIC SECTOR: OPTIMIZING RISK MANAGEMENT AND ACCOUNTABILITY

by Tim J. Leech, FCPA, FCA, Founder and CEO, Risk Oversight Solutions

This article outlines four significant change drivers that support implementation of a new form of governance, Enterprise Risk Management (ERM), and internal audit: Objective Centric Risk and Uncertainty Management.

Objective-Centric Risk and Uncertainty Management integrates risk considerations into the overall strategic planning and decision-making processes, aligning risk management activities closely with the organization's mission and vision. This approach aims to enhance the organization's ability to proactively address challenges and uncertainties in pursuit of its objectives while optimizing the allocation of resources. ERM solely based on building risk lists does not accomplish that goal.

AUTOMATING INSIGHT

by Mourad Nizar, CISA, Director, Professional Practices and Data Analysis Division, Canada Revenue Agency; Jasbir Singh, CISA, Project Leader, Data Analysis Innovation, Canada Revenue Agency; and Francis Hamel, Director, Data Services and Analysis, Public Service Commission of Canada

The digital age has created an abundance of raw data, which could potentially be turned into a useful asset for organizations. The biggest challenge to leverage this fabulous asset is unstructured textual data like interview notes, web articles, and text within any document or email. To extract value manually from unstructured data could be labor‑intensive and time‑consuming.

The Canada Revenue Agency uses a form of artificial intelligence — natural language processing — to analyze high volumes of this unstructured, textual data and can turn it into valuable audit tools and information.

AUDITING ORGANIZATIONAL CULTURE: EMPLOYEE SURVEY ANALYSIS USING PYTHON

by Philip Lillies, Internal Auditor (CIA), retired

Data analytics is becoming increasingly important in the business world. Indeed, data analytics has been especially profitable for early adopters like Amazon, Google, and Spotify, which have used it to predict the preferences of consumers. Data analytics has also been applied in the field of auditing to look for patterns that could indicate fraud or non-compliance with regulations, and provide general insight into an organization’s risks.

This article argues that auditors can take advantage of the rich data provided by employee surveys to extend data analytics to audits of organizational culture.

PROCESS MINING: A NEW ANALYTICAL TOOL FOR PERFORMANCE AUDITORS

by Ricardo Rocha, Auditor at the Court of Accounts, State of Bahia, Brazil

In recent years, many technological innovations have offered performance auditors new opportunities to expand the range of data analysis they can perform and increase the value and insight they can provide to their clients. Process mining is one of these innovations. By using this new analytical technique, performance auditors can gain a better understanding of where process weaknesses and inefficiencies exist, and formulate targeted recommendations that will help public sector organizations in redesigning and optimizing their business operations.

This article presents an overview of process mining and explains how this technology can be used in planning and conducting performance audits in the public sector.

ASKING THE RIGHT QUESTIONS: CONDUCTING SURVEYS IN PERFORMANCE AUDITS

by Maria Capozzi, Director, Office of the Auditor General of Manitoba

When properly conducted, opinion surveys can be a powerful element in a performance audit. Surveys can provide valuable insights and supplement audit findings. In this article, Maria Capozzi examines five key steps to consider when conducting surveys and highlights several factors that auditors should keep in mind when designing surveys and using their results.