Fraud can take place in many forms, and it affects all kinds of industries but the degree of harm is different for different industries. The sectors which frequently deal with fraud detection use several techniques to deal with the fraud. The main thing that they must do is to know the reason behind the fraud. Data analytics is the best tool that can help you know the reason behind frequent frauds at your workplace.

The main advantage of using data analytics for fraud detection is that they can handle a huge amount of data at once. The data surely helps you know the area which suffers the fraud mostly and how to deal with it in the right manner. Data analytics also helps in tracking trends and possible problems substantially faster than people could do without the help of any technological tool. Some of the advantages of using data analytics for fraud detection include:

• Automates the repetitive tests which help save a lot of time
• Searches 100% of your transactions automatically for fraud indicators.
• Easily merge, normalize, and compare data from different systems.
• Identifies the fraud quickly before it becomes front-page news.
• Realign resources to focus detection efforts on suspicious transactions.
• Calculates the impact of fraud more accurately.
• Reduces the risk of sampling errors and improves internal controls

The volume of global data continues to grow exponentially and this data can be used to identify unusual patterns, red signals for danger which means some kind of unusual activity is happening which must be stopped immediately. This was not possible before data analytics was introduced to the world. With the help of data analytics fraud detection for the management and audit team has become an easy job. Given below are the steps that will help you use data analytics as part of your fraud detection program:

1. Identify fraud risk factors.
2. Identify areas more prone to fraud schemes.
3. Understand the data sources.
4. Mix, match, and analyze the data.
5. Share insights and schedule alerts.

Want to know How forensic investigation help business in different types of frauds, you can read here.

Most of the sectors of private as well as public enterprises suffer some of the other kinds of fraud, but data analytics helps in the detection of fraud and provides a mitigating solution for the fraud. Given below are key areas where we can use data analytics or tools for fraud detection:

• Fraud detection using data analytics in taxation: For many filling up tax returns is a stressful time. Some are scared about making mathematical errors while some are scared because of filing illegal returns. Both could lead them to get audited. It is very much evident that fraud refunds increase the burden on the government as well as honest taxpayers. To deal with this kind of fraud, data analytics has been used by the Internal Revenue Service (IRS) in the US. Data analytics uses predictive analytics to assess the reliability of tax returns for individuals.
• Fraud detection in the pharmaceutical industry with the help of data analytics: The medical sector is one of the most important sectors for all human beings. Fraud happens when a pharmaceutical company charges an inflated price for medicines. Most often these kinds of frauds extend to the government as well. This happens in cases when the patient is a Medicare participant. Data analytics helps by examining the approval timelines for similar generic drugs and contrasting them with a medication awaiting approval. It also helps in detecting the cases of pharmacy refill fraud by examining the data collected. 
• Helps cracking down on bank frauds: Financial institutions such as banks rely on data analytics to find out the fraud and deal with it. Data analytics records the communication that happens between the bank and the customer. This makes it easy to detect the fraud and curb it before it could take extensive and damage the name of the brand. Bank constantly uses data analytics to record all the conversations and happenings in the bank on a regular basis. Data analytics which is well-trained looks for issues 24/7, this makes them a perfect tool for finding out any illegal activity happening at all the time zones and gives a prompt response to the wrongdoing, thus reducing the fraud to some extent.
• Fraud detection in security- Data analytics have become the first technological tool for defense and security that combines text mining, machine learning, and ontology modeling to ease security threat prediction, detection, and prevention at an early stage. Large amounts of data are collected from various sources on potential terrorist behavior, involvement in extreme online conversations, unusual purchases, moving in conflicted regions, connecting with other extremist dispositions, etc. . Security and intelligence agencies are using real-time analytics to identify data patterns of the security breaches by linking these different and unusual behaviors.
• Helps manage fraudulent behavior in retail returns- There are several shoppers who have not kept any time limit on the return of defective products. Merchandise return can sum up to billions of dollars every year for retailers, and a decent amount of which is surely fraud. To deal with all these, several retailers such as Amazon, Best Buy, etc. have started using data analytics to uncover cases where a consumer might be doing a wrongful return and benefiting from an extremely liberal return policy. However, retailers must be careful while using such technological tools could frustrate customers who have shopped with a brand for decades.
• Detecting fraud in cybersecurity- Despite using several techniques and tools, fraudsters leave behind a trail of behavioral and transactional data which helps in detecting cyber fraud. However, it is difficult to manage such a huge amount of data with human resources thus we use data analytics to record the data and provide patterns and associations in data for use in building predictive models. These models collect data from data records, such as emails, social media interactions, call center notes, or agents’ reports. This helps in tracking the shifting patterns to detect new scams even as they emerge.
• Financial Fraud detection- Financial fraud has always existed since the time digitalization came up. Several techniques have been used by financial institutions and banks to prevent and combat fraudulent attacks but the extent and nature of financial fraud continue to change. Data analytics has brought with it fraud detection and prevention with the help of techniques such as behavioral analysis and real-time detection. Real-time Analytics allows financial institutions to gain a deeper understanding of suspicious activities, derive patterns, and locate unusual transactions that will surely help in preventing fraud before it happens.

The best way to deal with any kind of fraud is to identify suspicious activities before it is done. Data analytics which collects real-time data helps look for suspicious or unusual behavior. 

Data analytics is a source for collecting and saving a huge amount of data. This saved data helps in fraud detection in every field. NSKT Global being one of the top firms dealing in data analytics helps in detecting and managing the huge data collected by companies with the help of data analytics. We at NSKT Global assist in managing fraud detection using data analytics to all kinds of enterprises.

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