Category: Management Notes

An F-test is any statistical test in which the test statistic has an F-distribution under the null hypothesis. It is most often used when comparing statistical models that have been fitted to a data set, in order to identify the model that best fits the population from which the data were sampled. Exact “F-tests” mainly arise when the models have been fitted to the data using least squares. The name was coined by George W. Snedecor, in honour of Sir Ronald A. Fisher. Fisher initially developed the statistic as the variance ratio in the 1920s.

Formula and calculation

Most F-tests arise by considering a decomposition of the variability in a collection of data in terms of sums of squares. The test statistic in an F-test is the ratio of two scaled sums of squares reflecting different sources of variability. These sums of squares are constructed so that the statistic tends to be greater when the null hypothesis is not true. In order for the statistic to follow the F-distribution under the null hypothesis, the sums of squares should be statistically independent, and each should follow a scaled χ²-distribution. The latter condition is guaranteed if the data values are independent and normally distributed with a common variance.

Common examples of the use of F-tests include the study of the following cases:

• The hypothesis that the means of a given set of normally distributed populations, all having the same standard deviation, are equal. This is perhaps the best-known F-test, and plays an important role in the analysis of variance (ANOVA).
• The hypothesis that a proposed regression model fits the data well. See Lack-of-fit sum of squares.
• The hypothesis that a data set in a regression analysis follows the simpler of two proposed linear models that are nested within each other.

Assumptions

Several assumptions are made for the test. Your population must be approximately normally distributed (i.e. fit the shape of a bell curve) in order to use the test. Plus, the samples must be independent events. In addition, you’ll want to bear in mind a few important points:

• The larger variance should always go in the numerator (the top number) to force the test into a right-tailed test. Right-tailed tests are easier to calculate.
• For two-tailed tests, divide alpha by 2 before finding the right critical value.
• If you are given standard deviations, they must be squared to get the variances.
• If your degrees of freedom aren’t listed in the F Table, use the larger critical value. This helps to avoid the possibility of Type I errors.

F Test to Compare Two Variances

A Statistical F Test uses an F Statistic to compare two variances, s1 and s2, by dividing them. The result is always a positive number (because variances are always positive). The equation for comparing two variances with the f-test is:

F = S^2 1 / s^2 2

If the variances are equal, the ratio of the variances will equal 1. For example, if you had two data sets with a sample 1 (variance of 10) and a sample 2 (variance of 10), the ratio would be 10/10 = 1.

A chi-squared test, also written as χ2 test, is a statistical hypothesis test that is valid to perform when the test statistic is chi-squared distributed under the null hypothesis, specifically Pearson’s chi-squared test and variants thereof. Pearson’s chi-squared test is used to determine whether there is a statistically significant difference between the expected frequencies and the observed frequencies in one or more categories of a contingency table.

In the standard applications of this test, the observations are classified into mutually exclusive classes. If the null hypothesis that there are no differences between the classes in the population is true, the test statistic computed from the observations follows a χ2 frequency distribution. The purpose of the test is to evaluate how likely the observed frequencies would be assuming the null hypothesis is true.

Test statistics that follow a χ2 distribution occur when the observations are independent and normally distributed, which are assumptions often justified under the central limit theorem. There are also χ2 tests for testing the null hypothesis of independence of a pair of random variables based on observations of the pairs.

Chi-squared tests often refers to tests for which the distribution of the test statistic approaches the χ2 distribution asymptotically, meaning that the sampling distribution (if the null hypothesis is true) of the test statistic approximates a chi-squared distribution more and more closely as sample sizes increase.

There are two types of chi-square tests. Both use the chi-square statistic and distribution for different purposes:

• A chi-square goodness of fit test determines if sample data matches a population. For more details on this type, see: Goodness of Fit Test.
• A chi-square test for independence compares two variables in a contingency table to see if they are related. In a more general sense, it tests to see whether distributions of categorical variables differ from each another.
• A very small chi square test statistic means that your observed data fits your expected data extremely well. In other words, there is a relationship.
• A very large chi square test statistic means that the data does not fit very well. In other words, there isn’t a relationship.

The formula for the chi-square statistic used in the chi square test is:

Fig:

The subscript “c” is the degrees of freedom. “O” is your observed value and E is your expected value. It’s very rare that you’ll want to actually use this formula to find a critical chi-square value by hand. The summation symbol means that you’ll have to perform a calculation for every single data item in your data set. As you can probably imagine, the calculations can get very, very, lengthy and tedious. Instead, you’ll probably want to use technology:

Essentially, a t-test allows us to compare the average values of the two data sets and determine if they came from the same population. In the above examples, if we were to take a sample of students from class A and another sample of students from class B, we would not expect them to have exactly the same mean and standard deviation. Similarly, samples taken from the placebo-fed control group and those taken from the drug prescribed group should have a slightly different mean and standard deviation.

A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. It is mostly used when the data sets, like the data set recorded as the outcome from flipping a coin 100 times, would follow a normal distribution and may have unknown variances. A t-test is used as a hypothesis testing tool, which allows testing of an assumption applicable to a population.

A t-test looks at the t-statistic, the t-distribution values, and the degrees of freedom to determine the statistical significance. To conduct a test with three or more means, one must use an analysis of variance.

Mathematically, the t-test takes a sample from each of the two sets and establishes the problem statement by assuming a null hypothesis that the two means are equal. Based on the applicable formulas, certain values are calculated and compared against the standard values, and the assumed null hypothesis is accepted or rejected accordingly.

If the null hypothesis qualifies to be rejected, it indicates that data readings are strong and are probably not due to chance. The t-test is just one of many tests used for this purpose. Statisticians must additionally use tests other than the t-test to examine more variables and tests with larger sample sizes. For a large sample size, statisticians use a z-test. Other testing options include the chi-square test and the f-test.

T-Test Assumptions

• The first assumption made regarding t-tests concerns the scale of measurement. The assumption for a t-test is that the scale of measurement applied to the data collected follows a continuous or ordinal scale, such as the scores for an IQ test.
• The second assumption made is that of a simple random sample, that the data is collected from a representative, randomly selected portion of the total population.
• The third assumption is the data, when plotted, results in a normal distribution, bell-shaped distribution curve.
• The final assumption is the homogeneity of variance. Homogeneous, or equal, variance exists when the standard deviations of samples are approximately equal.

Calculating T-Tests

Calculating a t-test requires three key data values. They include the difference between the mean values from each data set (called the mean difference), the standard deviation of each group, and the number of data values of each group.

The outcome of the t-test produces the t-value. This calculated t-value is then compared against a value obtained from a critical value table (called the T-Distribution Table). This comparison helps to determine the effect of chance alone on the difference, and whether the difference is outside that chance range. The t-test questions whether the difference between the groups represents a true difference in the study or if it is possibly a meaningless random difference.

T-Distribution Tables

The T-Distribution Table is available in one-tail and two-tails formats. The former is used for assessing cases which have a fixed value or range with a clear direction (positive or negative). For instance, what is the probability of output value remaining below -3, or getting more than seven when rolling a pair of dice? The latter is used for range bound analysis, such as asking if the coordinates fall between -2 and +2.

The t-test produces two values as its output: t-value and degrees of freedom. The t-value is a ratio of the difference between the mean of the two sample sets and the variation that exists within the sample sets. While the numerator value (the difference between the mean of the two sample sets) is straightforward to calculate, the denominator (the variation that exists within the sample sets) can become a bit complicated depending upon the type of data values involved. The denominator of the ratio is a measurement of the dispersion or variability. Higher values of the t-value, also called t-score, indicate that a large difference exists between the two sample sets. The smaller the t-value, the more similarity exists between the two sample sets.

• A large t-score indicates that the groups are different.
• A small t-score indicates that the groups are similar.

Degrees of freedom refers to the values in a study that has the freedom to vary and are essential for assessing the importance and the validity of the null hypothesis. Computation of these values usually depends upon the number of data records available in the sample set.

Correlated (or Paired) T-Test

The correlated t-test is performed when the samples typically consist of matched pairs of similar units, or when there are cases of repeated measures. For example, there may be instances of the same patients being tested repeatedly before and after receiving a particular treatment. In such cases, each patient is being used as a control sample against themselves.

This method also applies to cases where the samples are related in some manner or have matching characteristics, like a comparative analysis involving children, parents or siblings. Correlated or paired t-tests are of a dependent type, as these involve cases where the two sets of samples are related.

The formula for computing the t-value and degrees of freedom for a paired t-test is:

T = (Mean1-Mean2)

         s(diff)/√n

• mean1 and mean2=The average values of each of the sample sets
• s(diff)=The standard deviation of the differences of the paired data values
• n=The sample size (the number of paired differences)
• n−1=The degrees of freedom​

An ANOVA test is a way to find out if survey or experiment results are significant. In other words, they help you to figure out if you need to reject the null hypothesis or accept the alternate hypothesis.

Basically, you’re testing groups to see if there’s a difference between them. Examples of when you might want to test different groups:

• A group of psychiatric patients are trying three different therapies: counseling, medication and biofeedback. You want to see if one therapy is better than the others.
• A manufacturer has two different processes to make light bulbs. They want to know if one process is better than the other.
• Students from different colleges take the same exam. You want to see if one college outperforms the other.

Types of Tests

There are two main types: one-way and two-way. Two-way tests can be with or without replication.

• One-way ANOVA between groups: used when you want to test two groups to see if there’s a difference between them.
• Two way ANOVA without replication: used when you have one group and you’re double-testing that same group. For example, you’re testing one set of individuals before and after they take a medication to see if it works or not.
• Two way ANOVA with replication: Two groups, and the members of those groups are doing more than one thing. For example, two groups of patients from different hospitals trying two different therapies.

One Way ANOVA

A one way ANOVA is used to compare two means from two independent (unrelated) groups using the F-distribution. The null hypothesis for the test is that the two means are equal. Therefore, a significant result means that the two means are unequal.

Examples of when to use a one way ANOVA

Situation 1: You have a group of individuals randomly split into smaller groups and completing different tasks. For example, you might be studying the effects of tea on weight loss and form three groups: green tea, black tea, and no tea.

Situation 2: Similar to situation 1, but in this case the individuals are split into groups based on an attribute they possess. For example, you might be studying leg strength of people according to weight. You could split participants into weight categories (obese, overweight and normal) and measure their leg strength on a weight machine.

Limitations of the One Way ANOVA

A one way ANOVA will tell you that at least two groups were different from each other. But it won’t tell you which groups were different. If your test returns a significant f-statistic, you may need to run an ad hoc test (like the Least Significant Difference test) to tell you exactly which groups had a difference in means.

Two Way ANOVA

A Two Way ANOVA is an extension of the One Way ANOVA. With a One Way, you have one independent variable affecting a dependent variable. With a Two Way ANOVA, there are two independents. Use a two way ANOVA when you have one measurement variable (i.e. a quantitative variable) and two nominal variables. In other words, if your experiment has a quantitative outcome and you have two categorical explanatory variables, a two way ANOVA is appropriate.

For example, you might want to find out if there is an interaction between income and gender for anxiety level at job interviews. The anxiety level is the outcome, or the variable that can be measured. Gender and Income are the two categorical variables. These categorical variables are also the independent variables, which are called factors in a Two Way ANOVA.

MANOVA is just an ANOVA with several dependent variables. It’s similar to many other tests and experiments in that it’s purpose is to find out if the response variable (i.e. your dependent variable) is changed by manipulating the independent variable. The test helps to answer many research questions, including:

• Do changes to the independent variables have statistically significant effects on dependent variables?
• What are the interactions among dependent variables?
• What are the interactions among independent variables?

The Ministry of Corporate Affairs is an Indian government ministry. It is primarily concerned with administration of the Companies Act 2013, the Companies Act 1956, the Limited Liability Partnership Act, 2008, Insolvency and Bankruptcy Code, 2016 & other allied Acts and rules & regulations framed there-under mainly for regulating the functioning of the corporate sector in accordance with law. It is responsible mainly for regulation of Indian enterprises in Industrial and Services sector. Ministry is mostly served by the civil servants of the ICLS cadre. These officers are being selected through Civil Services Examination conducted by Union Public Service Commission. Brilliant talent pool of the country serves MCA in different capacities. The highest post of DGCoA is being fixed at Apex Scale for the ICLS. The current Minister of State for Corporate Affairs is Nirmala Sitaraman.

An expert panel set up by the ministry of corporate affairs (MCA) has proposed a new regime for businesses to report how sustainable and responsible they are in addition to being compliant with the law.

The panel led by Gyaneshwar Kumar Singh, a joint secretary in the ministry, has recommended two reporting formats a comprehensive reporting regime and a “lite version”. The reporting requirement is to be rolled out in a gradual manner. Eventually, these filings by companies could be used to develop a business responsibility and sustainability index for firms, the panel has recommended.

The idea is to put pressure on firms to pay attention to how they contribute to the society, going beyond meeting the objectives of shareholders and complying with laws. This would also give investors an opportunity to assess how ethical a company is while making investment decisions.

It also signals the thinking in the Union government that the corporate sector can contribute in meeting the sustainable development goals that the country is committed to meeting, such as poverty reduction, gender equality and adoption of clean energy.

“As a long-term measure, the committee envisions that the information captured through BRSR (Business Responsibility and Sustainability Report) filings be used to develop a business responsibility sustainability index for companies,” said the ministry.

The ministry will work closely with the Securities and Exchange Board of India (Sebi) in implementing the reporting regime, according to the government statement, which quoted the secretary in the ministry Rajesh Verma.

Indian companies aspiring to have a global foothold cannot ignore the emerging trend of corporate governance, which is being responsible businesses, the statement quoted Verma as saying.

Due to the trends of environmental, social and governance investing, the demand for non-financial reporting is growing and the proposed business responsibility framework will set the stage for sustainable investing, the statement said quoting Sebi executive director Amarjeet Singh.

The reporting regime will cover a set of guidelines on responsible business conduct brought out in 2019, which is an updated version of voluntary guidelines issued in 2009. Sebi has already mandated the top 1,000 listed entities by market capitalization to file business responsibility reports from an environmental, social and governance perspective. These enabled business to engage more meaningfully with stakeholders, going beyond regulatory and financial compliance, said the ministry.

The proposed reporting framework will cover both listed and unlisted enterprises.

When a former or the existing employee of the organization raise his voice against the unethical activities being carried out within the organization is called as whistle blowing and the person who raise his voice is called as a whistle blower.

The misconduct can be in the form of fraud, corruption, violation of company rules and policies, all done to impose a threat to public interest. The whistle blowing is done to safeguard the interest of the society and the general public for whom the organization is functioning.

The companies should motivate their employees to raise an alarm in case they find any violation of rules and procedures and do intimate about any possible harm to the interest of the organization and the society.

Types of Whistle Blowing

Internal Whistle Blowing:An employee informs about the misconduct to his officers or seniors holding positions in the same organization.

External Whistle Blowing: Here, the employee informs about the misconduct to any third person who is not a member of an organization, such as a lawyer or any other legal body.

Most often, the employees fear to raise a voice against the illegal activity being carried out in the organization because of following reasons:

• Threat to life
• Lost jobs and careers
• Lost friendships
• Resentment among workers
• Breach of trust and loyalty

Thus, in order to provide protection to the whistle blowers, the Whistle Blower Protection Bill is passed in 2011 by Lok Sabha.

Now, the question comes in the mind that which offenses are considered valid for whistle blowing and for which the protection is offered by the law. Following are the acts for which the voice can be raised and are law protected:

• Fraud
• Health and safety in danger
• Damage to the environment
• Violation of company laws
• Embezzlement of funds
• Breach of law and justice

Social Responsibility

CSR is corporate social responsibility and that is the responsibility of organizations to act in ways that protect ad improve the welfare of multiple stakeholders. A key word in this definition is “stakeholder” where that is any group within or outside the organization that is directly affected by the organization and has a stake in it’s performance. Stakeholders can be customers, organization members, owners, other organizations that work with them, competitors, community members, financial investors, any anyone else who would be effected by the organization’s actions. This means a lot considering how the difference between a company that considers all stakeholders and a company that considers only shareholders can heavily influence a company to be more or less socially responsible.

Developing an Effective Whistle Blower Policy:

All business entities often struggle with an appropriate level of segregation of duties making a whistle blower policy a good mitigating tool. The Whistle blower policies effective implementations not only reduce the fraudulent activities but also send a signal to both internal and external agencies that organisations exercises good corporate governance.

The Whistle Blower Policy may be drafted and implemented by management but it should be submitted to Audit Committee and Board of Directors. The foundation of Whistle Blower Policy is a clear and specific definition of Whistle Blowing. The key aspects are:

• Clear definition of individuals covered by the Policy
• Non retaliation provisions
• Confidentiality
• Process
• Communication

The Whistle Blower Policy should include the methods to encourage employees, vendors, customers and shareholders to report evidence of fraudulent activities. It should properly address the processes that the employees should follow in filing their claims. Specific Reporting Mechanisms within the process could include telephone, emails, hotlines, websites or suggestion boxes. The first steps of creating an environment where a whistleblower will report problems that exist is the crucial one, to be fully effective whistle blower policy must be consistently implemented, claims investigated and evaluated and proper enforcement taken when necessary. Clause 49 of the Listing Agreement keeps whistle blowing as non-mandatory item but it should be mandatory.

Economic Volatility, Global Competition, Growth risk appetite demands the governance professionals, the Company Secretaries to prioritise their role as whistle blowers.

Employees are usually the first to witness dangers and wrongdoings on Job. Although most employees remain silent, many chase to speak out and bear witness in corporate crimes that has not been addressed when flagged through normal company channels i.e Corporate Security, Audits, Inspections, Law enforcement combined.

Company Secretaries rank among the most productive, valued and committed members of their organisations. As they are the part of Top management and Board of Directors, they have a strong conscience; they are committed to formal goals of their organisation and have strong sense of professional responsibility.

Company Secretaries is also Corporate Governance Officer (CGO) and required to perform following roles:

• To ensure the effective running of the activities of the Board and its Committees.
• To ensure compliances of all listing rules, other Regulatory Codes and Acts.
• Keep under review all legal and regulatory developments affecting the company operations and make sure that directors and management are properly informed of the same.
• Manage relations with all stakeholders with regard to Corporate Governance, Corporate Social Responsibility, etc.
• Work with Board of Directors, Management to ensure that all regulatory reporting is correct and does not lead to errors resulting in offences under Various Acts.
• Act as the Conscience Keeper of the Company.
• Act as the Primary point of contact for Board of Directors and source of guidance in order to assist their decision making process.
• To assess, manage the compliances in the governance domain, governance processes, tracking of outcomes of governance processes and disseminate the information and documents for proper governance.

In ensuring implementation of proper corporate governance practices in the organisation, Company Secretary requires Governance Management and Reporting which includes:

• Development of Board framework and to determine the level of Independence
• Monitoring and reporting on the Independence of Audit Committee
• Development and Maintenance of a Board Charter to ensure that Board decisions can be measured against it.
• Acting as Board voice for providing shareholders feedback.
• Participating in Strategic Planning process, Risk Management process, Internal Control process, MIS, Corporate Communications, Succession Planning, Board performance evaluation process.

 In light of above, Company Secretary acts in the capacity that ensures high level corporate administration in accordance with best governance practices which results to well run, governed and sustainable business for the benefit of its stakeholders at large.

Company Secretary can be useful aid to implement whistle blowing as an internal regulator for ensuring good corporate governance in spirits. As he is a part of Board decisions process and recipient of all important information flowing in the organisation, he can easily smell the rat. He can suspect the improper activities/unethical practices adopted by organizations or some of its members.

India:

India had fairly weak whistleblower protection laws. The companies Act, 1956 though provided for provision through which mismanagement can be ventilate does not expressly provide for the protection of whistleblower as such. However, after coming into force of the Companies Act, 2014 there is a provision to protect the Whistle Blower. Every listed company or any company that is prescribed shall establish a Vigil mechanism specifically for the directors and employees to report genuine concerns. It also seeks to provide adequate protection to the employees from victimization as a result of disclosure made using the mechanism. It affords direct access to the chairperson of the Audit Committee in appropriate or exceptional cases. The establishment of a vigil mechanism has to be disclosed on the company’s website.

India lacks a specific whistleblowers protection law and does not cover all whistleblowers. The Indian Parliament has passed the Whistle Blowers Protection Act, 2011, however the Act has not come into force. The Act was approved by the Cabinet of India and passed by the Lok Sabha on 27 December 2011. The Bill was passed by Rajya Sabha on 21 February 2014 and received the President’s assent on 9 May 2014 yet the Act has not come into force till now. The Act provides for mechanism to scrutinize alleged fraud and abuse of power by public servants. It also seeks to protect one who would bring to light wrongdoing in government bodies, projects and offices. The wrongdoing might take the form of fraud, corruption or mismanagement. The Act will also have provision of penalty in case of false or frivolous complaints.

The Central Vigilance Commission, the sole authority in protecting future whistleblowers. The Act expanded the definition of whistleblower.[26]It classifies anyone making “public interest disclosure” a whistleblower. It is aftermath of murder of environmentalist activist Amit Jethava who was campaigning against illegal mining in the Gujarat’s Gir lion reserve to protect the lions.

The Central government came up with a legislative proposal to prevent such tragic killings. The Act empowers the Central Vigilance Commission to issue binding orders to protect whistleblowers from physical attack and/or victimization. CVC is authorized to issue interim orders to stop corrupt practice pointed out by the whistleblower. But these limited powers are likely to prove insufficient if CVC remains no more than an advisory body with regard to sensitive matters which may or may not be a corruption case that is to be registered against a public servant. It was an immense leap forward from where the legal framework stood. Only a public servant could be a whistleblower under the 2004 Cabinet resolution, but the expanded definition is the only real positive change in the official attitude towards whistle-blowing. The Act is to some extent on the lines of the Sabanes Oxley Act in United States which enacted as the repercussion of the Enron and WorldCom scandals, making it compulsory for audit committees of boards to establish procedures to receive anonymous complaints and reports from whistleblowers. Senior management is forbidden from discriminating against whistleblowers. Any retaliation against a whistleblower is a criminal offence, which can be punished with up to ten years in prison. But SEBI initially made  whistle blowing mandatory clause 49 of the listing agreement but later made it non- mandatory when SEBI accepted the argument made by the corporate sector that the regulation would lead to too many frivolous complaints.

Various companies are establishing Whistle Blower Policy in the company.  Maruti Suzuki India Ltd in its preface of their Whistle blowing policy mentions that Clause 49 of the Listing Agreement provides, a non-binding requirement, to establish a mechanism called “whistle blower policy” for all listed companies for the employees to report unethical behavior actual or suspected fraud or violation of the company’s code of conduct or ethics policy to the management of the company.

HCL adopted a whistle blower policy to afford appropriate avenues to the employees, contractors, clients, vendors, internal or external auditors, law enforcement / regulatory agencies or other third parties to bring to the consideration of the management any issue which is identified to be in infringement or in conflict with the essential business principles of the company. The employees are encouraged to raise any of their concerns by way of whistle blowing. All cases registered under the whistle blower policy of the company are reported directly to the CEO.

Corporate fraud consists of illegal or unethical and deceptive actions committed either by a company or an individual acting in their capacity as an employee of the company. Corporate fraud schemes are often extremely complicated and, therefore, difficult to identify. It often takes an office full of forensic accountants months to unravel a corporate fraud scheme in its entirety.

Corporate fraud consists of activities undertaken by an individual or company that are done in a dishonest or illegal manner, and are designed to give an advantage to the perpetrating individual or company. Corporate fraud schemes go beyond the scope of an employee’s stated position, and are marked by their complexity and economic impact on the business, other employees and outside parties.

Corporate fraud refers to illegal activities undertaken by an individual or company that are done in a dishonest or unethical manner. Often, this kind of business fraud is designed to give an advantage to the perpetrating individual or company. Corporate fraud schemes go beyond the scope of an employee’s stated position and are marked by their complexity and economic impact on the business, other employees, and outside parties.

Types of Fraud:

There are many types of corporate fraud, including the following common frauds:

1. Theft of cash, physical assets or confidential information
2. Misuse of accounts
3. Procurement fraud
4. Payroll fraud
5. Financial accounting mis-statements
6. Inappropriate journal vouchers
7. Suspense accounting fraud
8. Fraudulent expense claims
9. False employment credentials
10. Bribery and corruption.

Reasons:

1. The desire or perceived need to attract or retain investors

Corporate fraud commonly occurs for the same reason as any other fraud scheme – greed. However, amid the highly competitive global business environment of the modern world, it may also occur for other reasons. Many corporate fraud schemes consist of fraudulent accounting schemes used to make a company appear more profitable than it actually is. The impetus behind such schemes is the desire or perceived need to attract or retain investors.

2. Problems or defects with a company’s products

Another cause of corporate fraud may be problems or defects with a company’s products, which it tries to hide. Several recent corporate fraud cases have occurred with pharmaceutical companies that attempted to hide certain side effects or dangers associated with using certain medicines they manufactured and sold.

Government regulatory authorities, such as the Securities and Exchange Commission (SEC) in the United States, use laws and regulations to try to prevent, detect, and punish corporate fraud. However, fraud may go undetected for many years before it becomes apparent to authorities, especially if the guilty company is a private company that is not required to publicly disclose its financial records.

Prevention:

One of the best ways to develop policies and procedures that are effective in prevention corporate fraud is with the assistance of an experienced anti-fraud professional who has investigated hundreds of frauds to develop the most relevant and most effective anti-fraud controls including:

1. Establish clear and easy to understand standards from the top down. Have an employee manual that clearly outlines these standards and keeps the rules from becoming arbitrary.
2. Always check references and perform background checks that include employment, credit, licensing and criminal history for all new hires.
3. Secure physical assets, access to data, and money at all levels including monitoring and using pre-numbered checks, keep checks locked up, have a “voided check” procedure and never sign blank checks. Review all disbursements regularly.
4. Segregation of duties of employees. Divide activities so one employee doesn’t have too much control over an area or duty. Separate important accounting and account payable functions. Small-business owners and managers should review every payroll check personally. The person who has custody of the checks should never have check signing authority. The person opening the mail should not record the receivables and reconcile the accounts.
5. Proper authorization of transactions, ensuring that employees aren’t exceeding their authority.
6. Independent checks on performance, using audits, surprise check-ups, inventory counts, or other procedures to verify compliance with policies and procedures, as well as accuracy.
7. Instill an anonymous reporting mechanism, such as an employee fraud hotline.
8. Small-business owners should control who first receives the bank statements and other sensitive documents. Consider a separate post office box for the purpose of receiving bank statements, customer receipts or any other sensitive documents.
9. All account reconciliations and general ledger balances should have an independent review by a person outside the responsibility area such as an outside accountant. This allows for reviews, better ensuring nothing is amiss and providing a deterrent for fraudulent activities.
10. Conduct annual audits to motivate all bookkeeping- related staff to keep things honest because they can never be sure what questions an auditor is going to ask or what documents an auditor may request to review.
11. While no company, even with the strongest internal controls, is completely protected from fraud, strengthening internal control policies, processes and procedures will go a long way towards making your company a less attractive target to both internal and external criminals.

Corporate Scandals:

One of the most reputed company revealed in September that it had installed software on millions of cars in order to trick the Environmental Protection Agency’s emissions testers into thinking that the cars were more environmentally friendly than they were, investors understandably deserted the company.

Company lost roughly $20 billion in market capitalization, as investors worried about the cost of compensating customers for selling those cars that weren’t compliant with environmental regulations.

The company not only has to deal with compensating their customers, but it will also need to contend with potential fines from regulators as well as a reputational hit that could severely affect its market share.

Other Example of Corporate Scandal is one of the biggest Ponzi schemes in West Bengal that enjoyed political patronage and lured millions of investors to deposit money with the promise of abnormally high returns including fancy holidays etc. The chit fund eventually collapsed leading to defaults after a crackdown by SEBI and the Reserve Bank of India. The default, apart from leaving small depositors high and dry, also led to 10 media outlets owned by company being forced to wind up, leaving 1000 journalists jobless.

And an online business survey firm that collected thousands of cores of rupees from over 24 lakh investors, asking them to fill surveys and guaranteeing to quadruple their income in one year, company was accused of running a Ponzi scheme. A criminal case was registered against the company in 2011, some accounts frozen and its business shutdown.