Artificial Intelligence in Quality Control Maturity Model

Audit Quality Maturity Model (AQMM) is a tool for self-evaluation of audit firms & sole proprietors towards a technologically driven mechanism to increase operational efficiency. Since the business world is fast-changing, it is imperative for audit firms to adopt new technologies like Data Analytics and Robotic processes. The recent development in technology has significantly changed the way audit is done these days. The focus of the Audit Quality Maturity Matrix is to ensure continuous improvement of audit firms. Presently, the Audit Quality Maturity Model is recommendatory in nature.

The Audit Quality Maturity Model Version 1.0 focuses on the audit firms auditing the following:

• Listed entities
• Banks - other than co-operative banks
• Insurance companies

Audit firms doing branch audits are however not covered

Criteria on which the audit firms are evaluated are:

• Section 1: Practice Management - Operations
• Section 2: Human Resource Management
• Section 3: Practice Management - Strategic / Functional

In this article, we would discuss how Artificial Intelligence will help in achieving the objective prescribed in the Audit Quality Maturity Model.

1.1 Revenue from the Auditing and Assurance services

Revenue from Auditing and Assurance services forms an important consideration to decide the independence of the firm. Relying on a particular client hampers the independence of the audit firm. Artificial Intelligence can be used to monitor to maintain the percentage and provide alert to the client in case it reaches the threshold.

1.2 ​​​​​​​Evaluation of Independence for all engagements (partners, managers, staff, trainees, etc)

Artificial intelligence based on the parameters set can identify the threat to independence based on the data available of partners, managers, staff and trainees and alert the Quality Partner regarding the same. The database of the person engaged in the engagement would be analyzed and alert will be given if there are any violations with the set parameters.

1.3 ​​​​​​​​​​​​​​Adherence to Engagement withdrawal/rejection policy

Based on the policy set by the firm and the data available, artificial intelligence can help in analyzing the cases in which the engagement has to be withdrawn or rejected. It would compare the data available with the policy prescribed and would highlight the cases where the engagement has to be withdrawn or rejected.

1.4 ​​​​​​​​​​​​​​Capacity planning, budgeting & variance analysis for each engagement

Artificial Intelligence can be used for capacity planning based on previous experiences and budgeting can also be done accordingly. The previous data for the similar engagement based on the turnover, geographical area and scope of the work would be analyzed and the capacity planning and budgeting could be prepared for the current engagement. The tool can be deployed to track the efforts spent for each activity by the audit team members and monitor the planned hours and the actual hours spent.

1.5 ​​​​​​​​​​​​​​Tracking interaction with management

Artificial Intelligence tools can aid in tracking the various interactions with management (including mail communications) and the time spent with the management during the audit. Oral communications can be tracked effectively through the minutes of meetings.

​​​​​​​​​​​​​​1.6 Activity / Time sheet management

One of the most important considerations in the audit firm is to track the activities of the audit team and managing the timesheet. The timesheet management is important for the article assistance as they need to provide data to ICAI regarding the various activities done during the article period and the number of leaves taken. Artificial Intelligence along with capacity planning can be helpful along with tracking of the activities in the timesheet.

2.1 Effort Monitoring & Resource allocation

The system used for the activity management, capacity planning and budgeting can be used for allocation of assignments based on the skill sets, experience and to maintain the partner to manager, manager to articles and partner to client ratio.

2.2 Performance Management culture

Based on the parameters set for the appraisal, artificial intelligence through effort monitoring, resource allocation and timesheet management can be helpful in the performance management culture.