Experience during Green Hat IDI Innovation exchange series

IDI Green Hat series of workshops have been introduced to provide common platform for knowledge sharing among SAI experts. The first such workshop titled Green Hat: IDI Innovation Exchange Series – “SAI and Data Analytics” was held on 7-8 May 2019 in Malta. Overall, 55 Experts from SAIs of AFROSAI-E, OLACEFS, EUROSAI and ASOSAI participated in the workshop and shared their experience of introducing Data Analytics in respective SAIs. The participants demonstrated different practices and tools of Data Analytics used in compliance, financial audits and performance audits. Apart from presenting the experience of SAI India in Data Analytics and a case study, I contributed to the workshop by facilitating a session on “Use of data analytics tools and techniques”.

Presentation

During the presentation, I shared the following facts with the participants about Data Analytics in SAI India:

• SAI India adopted Guidelines on Data Analytics in September 2017 in order to provide institutional framework and consistency in approach and direction on use of data analytics for all field offices of SAI India.
• Centre for Data Management and Analytics was set up in June 2016 at SAI Headquarters.
• Data Analytics group were set up in all Field Offices.

I presented a Case Study on use of Data Analytics in the audit of “Revenue Generation activities in an Urban Development Authority”. The Data Analytics tools used (i.e. IDEA and Tableau) and audit approach was explained. The audit observations resulting from Data Analysis and subsequent substantive testing was discussed, which mainly included:

• Analysis of defaulters, their age analysis, inaction on the part of authority to recover dues;
• Analysis of un-allotted properties, their age analysis and revenue potential;
• Fraud Detection: Differences in receipts in the bank account of auditee and adjustment in allottee ledgers;
• Delay in issue of Demand notices;
• Analysis of un-auctioned resumed properties;
• Analysis of outstanding sewage and water bills;
• Heavy outstanding against leased property.

Lastly, I shared the challenges encountered in introducing Data Analytics, which mainly included Data Management and Capacity Building.

Facilitating session on “Use of data analytics tools and techniques”

I, along with Ms. Rebecaa from SAI Malta, facilitated the session on “Use of Data Analytics tools and techniques”. I made an interactive introductory presentation, wherein participants were asked to respond to some questions such as:

1. “Which Data Analytics (DA) tools are being used by participating SAIs?”
2. “What is the difference between IT Audit and DA? What has changed in last decade?”
3. “What are the challenges in introducing DA in their SAIs?”
4. “How do SAI select the most suitable tools?”

This was done to enhance the learning experience. After compiling participant’s responses, a conclusion was conveyed to the participants. The participants were apprised that DA is different from IT Audit as it is not only a domain of specialized IT auditors. The aim is to integrate DA throughout the audit process. Adoption of DA will lead to increased productivity, cost savings, quality audit output, independence, minimization of Audit Risk and timely and more reliable opinions.

The participants were told that the DA industry is booming with large number of tools. Not all tools are suitable for every organization and all types of DA work. Thus, SAIs needs to carefully pick the best of the lot to get the best results. The specific criteria, which needs to be considered for choosing the right tool, are:

• Size of SAI
• Price
• Platform (compatibility with existing hardware and software)
• Reporting ability
• Ease of Use
• Data Access and Management
• Control over the audit analytics process
• Collaboration, Efficiency and Sustainability

Noticeable contribution from other SAIs

• Participants from SAI Estonia explained two case studies. The SAI had evaluated the effectiveness of probation supervision system. Using Random Forest Analysis (Exploratory Data Analytics), SAI established that addiction status, employment and housing background does affect the effectiveness of probation. In the second case study, SAI Estonia has evaluated the performance of emergency health services, by surveying emergency department staff, as well as patients and arriving at counter intuitive conclusions.
• Participants from Croatia showed how their SAI is using a system to match information on registered donors of political parties, and suppliers in public procurement contracts.
• Integrity expert and audit manager of SAI Hungary explained the case of the data request system, which through a unique "one gate system" effectively diminishes integrity risks of the data collection procedure. Auditees can only provide data through a secure online platform, almost eliminating on site examination of audit documents. An integrity assessment dashboard was also demonstrated, which gives a detailed and informative feedback to public sector institutions to improve their overall integrity performance.
• Participants from SAI Finland shared experience of introducing DA in their SAI. Specifically, they shared the reasons for which SAI Finland ended up using DA; process involved in introducing DA; and lessons learnt during the entire process. The presentation also explained ways in which SAIs can engage and gain from experts/coders from outside SAIs.

Group Activities

Apart from presentations, various group activities were also planned to exchange ideas. The participants were divided into teams and were asked to brainstorm on various topics such as:

• Usability of Data Analytics in the planning, conducting, and reporting stages of an audit topic.
• How Data Analytics can help fight corruption?

After brainstorming, representatives from each group were asked to present their observations and opinions on the topic.  For instance, with regard to fighting corruption, it was realized after brainstorming that different SAIs possess different mandates to fight corruption. SAI Peru for example, has been given authority to call for information on individual Government officers from Government Authorities as well as commercial entities such as banks. They have been given punitive powers in case of non-supply of information in specified time.

Generally, the conclusion was that because of the hidden nature of transactions where corruption is involved, it is difficult to establish quid pro quo through audit alone. However, internal control systems and other preventive systems can be checked for their effectiveness in checking corruption.

Conclusion

Most SAIs realize the importance of Data Analytics in a governance paradigm, which is getting increasingly digital. They are planning to increase the use of Data Analytics in Audit assignments. Some of the common challenges are as below:

• There is a greater need of dialogue between the Data Analytics personnel and the field auditors in SAIs to improve synergies in their works and get higher levels of outcome. Making composite audit teams or allowing movement of human resource across verticals can resolve this problem to some extent.
• Finding an appropriate institutional set up remains challenging. For instance, some SAIs are planning to set up their own Data Lab, whereas others are planning to engage outside experts for the job. A right mix of both would be ideal. Capacity building of staff is the most critical factor.
• Finding the most suitable Data Analytics tool remains a challenge. The participants got an exposure to large number of tools and factors to be considered while choosing the tool.
• Data Quality and integrity remains a challenge.
• SAIs are at different level of maturity in using Data Analytics and there is a huge scope for learning from each other.

Apart from structured presentations and group activities, interaction with participants from various SAIs gave me an exposure to wide range of tools and techniques. Overall, it was a great learning experience.

 

 

Virender Kulharia

Deputy Director

National Academy of Audit and Accounts, Shimla