FRAUD DETECTION

These days Business data is being managed and stored by IT systems in an organization. Therefore organizations rely more on IT systems to support business processes. Because of such IT systems the level of human interaction has been reduced to a greater extent which in turn becomes the main reason for fraud to take place in an organization. To detect and prevent such frauds again organizations go in for automated controls.

Fraud Detection

Fraud detection means the identification of actual or expected fraud to take place within an organization. An organization need to implement proper systems and processes to detect frauds at an early stage or even before it occurs. Fraud detection consists of the following techniques.

·     Proactive and Reactive

·     Manual and Automated

An organization should include these Fraud detection techniques in its anti-fraud strategy.

Why is fraud detection important ?

Fraud detection technique is important for an organization to find out new type of frauds and also so some traditional frauds. Even the most effective fraud detection technique can be circumvented by a skilled fraudster. So the organization should be very clever in developing such Fraud detection techniques.

The benefits of fraud detection includes the following;

·     Reduced exposure to fraudulent activities

·     Reduced costs associated with fraud

·     Find out the vulnerable employees at risk to fraud

·     Have organizational controls

·     Improves the results of the organization

·     Gains the trust and confidence of the shareholders of the organization

Analytics for Fraud Monitoring

Accessibility of business data from internal and external sources have become easier. This makes the organizations to use analytics in their fraud detection programs. Fraud Data analytics play a crucial role in the early detection and monitoring of fraud. These data analytic techniques will help the organization to detect the possible instances of fraud and implement an effective fraud monitoring program to protect the organization.

What is Fraud Analytics ?

Fraud analytics is the combination of analytic technology and Fraud analytics techniques with human interaction which will help to detect the possible improper transactions like fraud or bribery either before the transaction is done or after the transaction is done.

Why Fraud Analytics ?

Traditional Anomaly detection and various rules based methods are already in practice by many organizations to detect and prevent fraud. But they are not that powerful. They have their own limits. When analytics is added to such traditional methods, it enhances the fraud detection capabilities and gives a new dimension to the fraud detection techniques.

Another important reason for using data analytics to handle fraud is because these days internal control systems have control weaknesses. In order to avoid this the organizations should have a control over every transaction that takes place and test the transaction using fraud analytics.

And fraud analytics also helps to measure the performance which will help you to standardize and have a control for constant improvement.

Benefits of Fraud Analytics

·     Identify Hidden Patterns

Fraud analytics identify new patterns, trends and scenarios under which frauds take place. Whereas traditional approaches miss such things.

·     Data Integration

Fraud analytics plays an important role in integrating data. It combines data from various sources and public records that can be integrated into a model.

·     Enhance existing efforts

Fraud analytics does not replace the traditional rules based methods but it just adds up to your existing efforts to bring you more improved results.

·     Harnessing unstructured data

Fraud analytics helps in deriving the best value from unstructured data. Most of the structured data are stored in data warehouse of the organization. But unstructured data is the place where more fraudulent activities take place. This is where text analytics plays an important role in reviewing the unstructured data and preventing fraud from taking place.

·     Improve the performance

With the use of fraud analytics you can easily identify what is working for your organization and what is not working for your organization

Data Analytics Process

Steps to create your Fraud Program

·     Create a profile that includes all the areas where fraud is expected to occur and the possible types of fraud in those areas.

·     Measure the risk of fraud and the overall exposure to the organization. Prioritize the risks based on fraud.

·     Follow Ad-hoc testing method to find for indicators of fraud in particular areas of organization

·     Establish risk assessment and decide where to pay closer attention.

·     Monitor the activity and communicate it throughout the organization so that employees in the organization are aware about the happening in the organization.

·     If there is any fraud found out, inform the management immediately to solve out the issue and to find out why it happened.

·     Fix any broken controls.

·     Segregation of duties is very essential.

·     Expand the scope of the program and repeat the process.

Methods of Fraud Analytics

There are five important fraud detection methods.

·     Sampling

Sampling is mandatory for certain processes of fraud detection. Sampling will be more effective where there a lot of data population involved. But still it has its own disadvantage. Sampling may not be able to fully control the fraud detection as it takes only few population into consideration. Fraudulent transactions do not occur randomly therefore an organization need to test all the transactions to effectively detect fraud.

·     Ad-Hoc

Ad-Hoc is nothing but finding out fraud by means of a hypothesis. It allows you to explore. You can test the transactions and find out if there are any opportunities for fraud to take place. You can have a hypothesis to test and find out if there is any fraudulent activity occurring and then you can investigate on the same.

·     Repetitive or Continuous Analysis

Repetitive or Competitive Analysis means creating and setting up scripts to run against big volume of data to identify the frauds as they occur over a period of time.

Run the script every day to go through all the transactions and get periodic notification regarding the frauds. This method can help in improving the overall efficiency and consistency of your fraud detection processes.

·     Analytics Techniques

Analytic techniques helps you to find out frauds that are not normal

·     Calculate Statistical parameters to find out values that exceed averages of standard deviation.

·     Look at high and low values and find out the anomalies there. Such anomalies are often the indicators of fraud

·     Classify the data – Group your data and transactions based on specific factors like geographical area.

Benford’s Law

Benford’s law can often be used as an indicator of fraudulent data. Benford’s distribution is non-uniform with smaller digits more likely than the larger digits. Using Benford’s law you can test certain points and numbers and identify those which appear frequently than they are supposed to and therefore they are the suspect.

There are several other fraud detection data mining tools to detect fraud;

·     Data Matching – This method will find out if there is any data which exactly matches with another data.

·     Sounds like – This is another powerful method where it identifies variations of valid company employee names.

·     Duplicates – This is another method which is most commonly used by a lot of organizations to identify fraud as well as any error occurring within all the business transactions.

·     Gaps – In this method you can find out the missing sequential data. For example if you have purchase orders which is issued by the company in sequential order and if anything is missing you can easily find out. This is an easy method and it will work out great if used correctly.

Conclusion

Frauds will increase as the transaction volume of your business increases. Technology advancement is a plus as well as a minus to your business as it opens up new avenues for fraudsters. Analytics to detect Fraud can play a very important role in identifying fraud in the early stages and protecting your business from heavy loss. It does not require a lot of time and resources to get fraud analytics running for your business. Get started with a small fraud detection project and then start expanding. It can take as little as few weeks.