Future Auditing in Big Data Environments

ISACA Annual Conference 2019

Mombasa, Kenya.

Presentation By:

FCPA. Edward Ouko, CBS

Auditor-General of Kenya

Agenda

Introduction

How has the world defined Big Data

Big Data And Analytics Explained

Significance of Big Data to the Office

Some of the OAG’s Data Sources

Opportunities to the Office

OAG strategy for Big Data

OAG Use case for Big Data in Auditing

Skills OAG will Require for Big Data Audits

Challenges of Big Data in Audit

Conclusion

Introduction

The proliferation of data has transformed our lives, in the way we cannot imagine. The world is slowly becoming digital and most of our lives are run and determined

by what happens in this world.

big data continues to reshape

• how we do business,

• how we operate

How has the world defined Big Data

Big data is high-volume, high-velocity and high variety information assetsthat demand cost effective, innovative forms of information processing for enhanced insight and decision making

Big Data is a phrase used to mean a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques. In most enterprise scenarios the volume of data is too big or it moves too fast or it exceeds current processing capacity.

"Big data represents the information assets characterized by such a high volume, velocity and variety to require specific technology and analytical methods for its transformation into value”

Wikipedia,

BIG DATA AND ANALYTICS EXPLAINED

Significance of Big Data to the Office

Enable OAG auditors to better identify financial reporting, fraud and operational

business risks and tailor their

approach to deliver a more relevant audit.

Enable OAG analyze data and

get answers better than

slower and less efficient with

more traditional business

intelligence solutions.

analytics bring significant cost

advantages when it comes to

storing large amounts of data

using intelligent analytics to

deliver a higher quality of audit evidence and more relevant

business insights

the ability to analyze new

sources of data, businesses are able to analyze

information immediately

What other Auditors are saying…….

The auditor of the future will

use data analytics to check

data of much larger sets of

information from a wide

variety of agencies.

Ben Jiang, Director – Data analyticsVictorian Auditor-General’s Office

Big data not only encompasses the classic world of transactions, but also includes the new world of interactions and observations

Kumar Setty, CISAISACA JOURNAL VOLUME 3, 2013

The shift from traditional audits to future audits will not happen because auditors choose to do so. The main driver of big data application by auditors is client-side demands.

By Michael G. Alles, “Drivers of the Use and Facilitators and Obstacles of the Evolution of big data by the Audit Profession,” Accounting Horizons, June 2015

VMware –holistic view big data framework

Some of the OAG’s Data Sources

And many more

Opportunities to the Office

have access to all Government data, enabling it to combine, for example, HR data with operational data, or HR

data with financial data.

The ability to pull disparate data sources together, to perform simple

and complex analysis, join and append data sets, and draw on larger

enterprise and external data sets.

Examine all accounts receivables data rather than relying on sampling. The large volume of data also allows it to be stratified by difference variables (like transaction amounts, time and location) to find more meaningful

patterns or anomalies.

Higher quality audit evidence More relevant business insightsStronger ability to identify fraud and

operational business risks

Data Analytics - 100% Sample!

Under the future vision of auditing, organizations would

give auditors access not just to a sample of their transactions,

but to their entire general ledger and their databases.

“With Data Analytics tools, auditors will have the

capability to look at the underlying data, not just the

summary data,”

Opportunities in Public Sector

Effective and Efficient Audit of Revenue

Increased reliability of the audit result due ability to analyze all population of data!

OAG strategy for Big Data

Standards or Guidance on audit of Big Data.

Working Groups on Big Data were created in the last INCOSAI of 2016 with China National Audit Office (CNAO) as the Chair and Government Accountability Office (GAO) i.e SAI-USA as Vice Chair. The working group has planned to take up some research projects in their current three year plan.

OAG strategy for Big Data Cont.…….

Current Initiatives

• Capacity Building in the area of Data analytics (The office has trained All Auditors in the use of at least one analytical tool)

• We have invested heavily on ICT infrastructure

• Invested in a robust security infrastructure

• We are also creating awareness to staff.

OAG Use case of Big Data in OAG

OAG will use various channels to conduct Citizen Participatory Audits (CPA)

OAG Use case of Big Data in Auditing cont.…..Insights from Social Media

There is massive data and information across social media

platforms that can aid the auditor in doing smart audits.

By tracking and analyzing social media discussions by citizens of

all walks of life, the auditor is able to do focused audits

resonating with the ordinary citizens.

Under the Citizen Participatory Audit, social media will play a

key role through enhanced data analytics. Predictive analytics

will have the potential enabling prevention of corruption

OAG Use of Big Data in Auditing Cont..

Many conversations take place in the social media regarding governance at county and

national level.

This is a rich data source and can be combined with data from other sources to offer unique

insights.

These social media analytics and data discovery integrated will

allow discovery of co-relationships and tagging of data. This will work in conjunction with

structured data analysis.

Think creatively

44%

41%

Skills OAG will Require for Big Data Audits

Essential big data skill #1: Programming

• Programming skills in Python, R, Java, and C++ among others

• Good knowledge of databases through queries and statements.

Essential big data skill #2: Quantitative Skills

• Knowledge of calculus and linear and matrix algebra.

• a strong foundation in numerical analysis

Essential big data skill #3: Multiple Technologies

• Enterprise level, SPSS, Cognos, SAS, MATLAB coupled with knowledge of Python, Scala, Linux, Hadoop and HIVE.

Essential big data skill #4: Understanding of Business & Outcomes

• strong understanding of the Audit entity and domain they are Auditing

Essential big data skill #5: Interpretation of

Data

• Should be able to understand Audit data

Key to a successful big data Personnel

Resource Responsibility/Role

Sponsor Executive level Approval for funding

Data Owners Training

Data Officers Managing the day to day Activities

CISO Managing Security

Data Analysts Employment of Developers, DBAs, system administrators subject matter experts, etc.

Data Scientists Analytics specialists with a good understanding of the Audits

Big Data Architect For Designing the solutions for various teams

Key to a successful big data Technology

Resource

Hardware Capacity PlanningHigh availability Right sizing and ability to scale

Network Secure and Appropriate Network

Tools Appropriate tools and training

Challenges of Big Data in Audit

Increased Storage Requirements

• Increase of users (potentially an estimated 30 million Kenyans) and expanded data sources –structured and unstructured means significant increase in storage capacity.

Data Security

• The more data you store, the more complex it becomes to classify. This presents a challenge of securing such data.

Conclusion

Big Data is becoming an indispensable resource to modern organizations and has the potential to be a valuable resource to auditors.

But that presumption must not be taken as given without question, skepticism, and research.

OAG will continue to invest in data analytics and stretch its limits fully in tapping the potential of big data. This will contribute to the war against wastage in public sector.