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Using Data Analytics to Detect Irregularities and Earnings Manipulation

Expert Speaker Chee Hay Kheong Daniel

$599.20 (including GST)

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Overview

Earnings manipulation refers to what management do to financial reports or in the business to show profit that is desirable to them, rather than reflecting the actual performance. The usual accounting ratios can be useful when there are large scale manipulations of key figures such as revenue. Smaller scale manipulation of financial figures is more difficult to be picked up by ratio analysis. These may be easier to be detected using financial models to analyse accounting data.

Accounting Analytics explores how financial statement data and non-financial metrics can be linked to financial performance. In this highly practical workshop, we will use big data approaches to try to detect earnings manipulation. Specifically, we will be using prediction models to try to predict how the financial statements would look if there were no manipulation by management.

First, we will look at Discretionary Accruals Models, which attempt to model the non-cash portion of earnings or "accruals," where managers are making estimates to calculate revenues or expenses. Next, we will look at Discretionary Expenditure Models, which try to model the cash portion of earnings. Then we will take a look at Fraud Prediction Models, which try to directly predict the types of companies are likely to commit fraud. 

This programme is highly practical for Accountants, Auditors and anyone interested in the financial modelling of accounting data. By the end of this workshop, you will have an appreciation of the tool kit that will help you try to detect financial statements that may have been manipulated by management. 

Programme Outline

  • Earnings Manipulation techniques
    • What is earnings manipulation
    • Why management may want to manipulate earnings
    • Different ways to “manage” earnings
  • Discretionary Accruals : Model
    • Earnings are made up of cash portion and non-cash portion. Non-cash portion is affected by receivables and payables and other accruals, such as provision or depreciation. Manipulation of non-cash income or expense accruals can result in higher or lower reported profits.
    • This model uses regression analysis to determine the normal level of accrual, i.e. due to normal business activities and to detect abnormal level of non-cash earnings, if any.
  • Discretionary Expenditures: Model
    • This model uses regression analysis to determine the normal level of cash expenses and thus detect abnormal changes in cash expenses to “manage” earnings
  • Benford Law
    • This examines the frequency with which numbers (1 to 9) appear. Financial statements figures are found to appear in frequency that conforms to the Benford Law. If certain numbers appear more often or less frequently than dictated by Benford's Law, it's an indication that the financial statements were potentially manipulated
  • Beneish Model
    • This is a mathematical model that uses financial ratios and variables to identify whether a company has manipulated its earnings. The variables are constructed from the data in the company's financial statements and, once calculated, create an M-Score to describe the degree to which the earnings have been manipulated.


Participants are encouraged to bring along their laptops to try out some hands-on examples, guided by the Trainer. Your laptop should be equipped with Microsoft Excel with the Data Analysis function installed.
No prior knowledge in financial modelling is required, but some working knowledge of basic excel is preferred.

Participants without laptops will still be able to appreciate how accounting analytics can be used to detect fraud in financial statements.

Expert Speaker

Chee Hay Kheong Daniel

Daniel holds an Honours degree in Accountancy from the National University of Singapore and is a Certified Information Systems Auditor (CISA). He has more than 13 years of experience in the accounting profession, having worked for one of the Big 4 accounting firms both in Singapore and in the United Kingdom. He has also more than 5 years of senior management experience with MNCs, managing their operations in Singapore and Asia.

Daniel is a highly sought-after seminar trainer, and is currently an Adjunct Professor in the School of Business, Singapore University of Social Sciences. Prior to this, he was an Adjunct Associate Professor in the Department of Accounting of the NUS Business School. He served as a committee member of both the IT Committee and the Examination Committee of ISCA, and was a Committee member of the Disciplinary Sub-Committee of Accounting and Corporate Regulatory Authority (ACRA).

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