|$599.20 (including GST)|
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.
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.
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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