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This is a simple book that provides you with an easy-to-read overview of the basic terms, definitions and processes and procedures involved. Not only is this an easy ready, it is also a great reference book for your investigation library. The FBI Handbook is perfect for detectives and police officers.

The 12th edition of Criminalistics: An Introduction to Forensic Science is a textbook that provides an introduction to the theory, philosophy, technology and approach. It is written for readers without a scientific background. Much of the book is devoted to discussions on the most common items found at crime scenes.

ISBN 13: 9781439867822

The book has a rating of 4. Following is a brief overview of forensic accounting and a list of the best forensic accounting books to help you learn more. All of the larger accounting firms, as well as many medium-sized and boutique firms, have departments dedicated to this specialty. Within these groups, there may be further sub-specializations. Some accountants specialize in reviewing insurance claims and personal injury claims, investigating fraud, or performing royalty audits.

Private detectives who conduct financial investigations and asset searches may leverage skills and techniques from this specialty field.

Forensic accountant - Wikipedia

Obtaining the depth of knowledge and skills that are required to be successful generally requires a degree and experience in the field of accounting or some financially related field. This normally entails reviewing documented policies and procedures and may also include interviews with employees to help clarify any ambiguities in the documentation see Chapters 7 and 8 on witness interviews. Some considerations include:. It may also be important to review any training programmes that the subject of the investigation has received.

Doing so can establish more firmly that the subject had an understanding of the proper method of handling the transactions. Most accounting cycles, such as procurement, disbursement of funds and payroll include many steps. Some of these are evidenced manually, such as with written approvals by signature and supporting documents such as invoices and delivery confirmations. Other steps require analysis of electronic records. Examples of critical pieces of electronic evidence related to internal controls include:.


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Physical documents are often important pieces of evidence in an investigation. But electronic evidence associated with a transaction cycle tend to be equally or more important. Proper analysis of this evidence enables an investigator to draw conclusions and gain insight that would be impossible in an entirely paper-based system. For example, a paper copy of a vendor invoice can be analysed to establish whether a subject signed or initialled it, and perhaps whether any alterations were made to the document. Forensic analysis of data refers to analysis of electronically stored data. The most commonly analysed data are accounting and financial, but several non-financial categories of data are also very useful to investigators.

Each will be explored further in this section. Each of these will be explained further. But first, a few important points about data analytics are essential. Data analytics rarely prove that fraud or non-compliance occurred. Rather, data analysis identifies transactions or activities that have the characteristics of fraud or non-compliance, so that they can be examined further. These are often referred to as anomalies in the data. If an investigation ultimately leads to employee terminations or legal proceedings to recover losses, it is critical to have properly analysed the anomalies that data mining has identified.

Could the anomaly in the data, or an anomaly in a document, while often identified as a characteristic of fraud, also simply indicate a benign deviation? Failing to investigate and rule out non-fraudulent explanations for anomalies can have consequences that many investigators have learned about the hard way.

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Identifying and exploring all realistically possible non-fraudulent, non-corrupt explanations for an anomaly is also called reverse proof. Examining and eventually ruling out all of the valid possible non-fraudulent explanations for an anomaly in the data or documentation can prove that the only remaining reasonable explanation is fraud or corruption. Take a simple example to illustrate this important concept.

An employee is found to have submitted the same business expenditure twice for reimbursement paid for using a personal credit card. Further analysis shows that this is not an isolated incident. In fact, the rate at which the employee submitted duplicate expenditures has increased over time — a classic red flag commonly associated with perpetrators of fraud.

Is this a sufficient basis to support an allegation of misconduct? This would be premature.

Financial Investigation and Forensic Accounting

What if on further analysis, the investigator also finds that the employee has been asked to work an increasing number of hours every week and travel much more extensively over time. Investigating further, it is found that this employee is particularly disorganised and has never been asked to do this much business travel before. These additional facts make the distinction between an intentional act of fraud and an escalating series of honest mistakes a bit blurry.

Careful consideration of alternative theories for data and document anomalies is critical to protecting the organisation and the investigator from liability stemming from falsely accusing someone of wrongdoing. Depending on which application or phase of the investigative process is involved, the nature of forensic data analysis can vary. For example, as an initial detector of fraud or non-compliance through ongoing monitoring, forensic data analytics usually takes one of two broad, but opposite, approaches: identification of any activity that deviates from expectations, or identification of activity that possesses specific characteristics associated with fraudulent or corrupt behaviour or other non-compliant conduct.

The former approach is taken when acceptable behaviour is narrowly defined, such that the slightest deviation warrants investigation. The latter approach is the more common. It is driven by a risk assessment and is based on what this type of fraud or non-compliance would look like in the data. For example, a shell company scheme might evidence itself by an address in the vendor master file matching an address in the employee master file. Any instances of such a match would be investigated. For this reason, more sophisticated data analytics often rely on the consideration of multiple characteristics in assessing the risk of activity being fraudulent or corrupt.

Regardless of which of these two approaches is taken, data analytics performed at this stage represent the very first steps in the investigative process. One or more anomalous transactions or activities have been flagged for further evaluation. Following the reverse-proof concept described above is critical once anomalies indicative of possible wrongdoing are uncovered. As a method of corroborating an allegation that has been received, data analysis can be of great value see Chapters 18 and 19 for additional guidance on dealing with whistleblowers.

It is a significant advantage to the investigator because, more often than not, it can be performed on electronic data without alerting the subject of the allegation. In this application, the allegation is first assessed in terms of what impact the alleged fraudulent or corrupt act would have on financial or non-financial data.

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To illustrate, take the example of an allegation that workers in the shipping department of a warehouse are stealing inventory by short shipping orders to customers. There are numerous sources of data, both financial and non-financial, that could be analysed to assess the validity of this allegation:. This is a simple example, but one that illustrates that for every allegation, there likely exists data associated with either the perpetration or concealment of the fraud or non-compliance. And this data normally exhibits one or more anomalies in comparison with data from similar transactions that do not involve fraud or non-compliance.

The final application of forensic data analysis is during the investigation itself. Once an allegation has been substantiated, or an initial anomaly has been found to involve fraud or non-compliance, additional forensic data analysis may be performed to:. Determining who is involved has become increasingly important over the years. According to a recent report by the Association of Certified Fraud Examiners ACFE , nearly 45 per cent of all fraud and corruption schemes investigated involve multiple perpetrators. The 45 per cent is split nearly evenly between cases involving multiple internal perpetrators and those involving collusion between insiders and outsiders, such as vendors or customers.

Point 4, above, may also come as a surprise to some, but is important.

The ACFE report indicates that The allegation or investigation may have initially focused on only one specific method. Exploring what other activities the subject might have the capability of engaging in similar behaviour with is an important consideration in the investigation. Companies will wish to avoid a scenario in which only one type of fraudulent activity is discovered when the subject engaged in a second type of fraud at the same time.

For example, the investigation may reveal that a subject established a shell company designed to look like a legitimate vendor and has been transferring funds to the company, supported by fraudulent invoices for services that have not been rendered.


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  • On the surface, this appears to be a common asset misappropriation scheme. Further analysis, however, might reveal that the shell company is merely a conduit for paying bribes to foreign government officials, a potentially even more serious offence than an asset misappropriation. In the next sections, the distinction between financial and non-financial data will be explored, followed by a discussion of internal versus external data.

    How Forensic Investigation Works

    Accounting data can exist in several separate systems, such as:. CRA has the criminal trial testimony experience and forensic accounting and investigation knowledge necessary to help outside counsel identify the critical issues in white collar criminal defense matters. Whether it's the purchase or the sale of a business or a financing, problems and disputes concerning the accounting for these events requires specific experience.

    Our expert teams can be deployed across the globe, and they are experienced at keeping business disruption to a minimum.


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