Why Your Business Is Susceptible To Fraudulent Attacks

At a time where cybercrime is at an all time high, you may have to reconsider what security measures your business have put in place to tackle this prevalence. It is estimated that the global cost of cybercrime may reach $10.25 trillion in the year 2025. This is supposed to be scary, but again, it looks like it is not causing enough ripples. A recent study showed that two-thirds of IT leaders preferred to to secure structured data as compared to unstructured data. What this translates to is, a shocking number of these IT leaders would leave voluminous amount of sensitive data, thus raising security concerns.

If you probably don't understand the gravity of this act, then, let's lay it bare. All data that contains a company's operational risks, mode of operations are usually classified as unstructured data. Leaving this data badly protected is an invitation to attacks or manipulation of data for selfish reasons.

Over 80% of businesses based in the United States have faced hacks and have had their data breached. Now, the United States of America is supposed to have advanced techniques to stop data assault, consider what the statistics would look like worldwide. It would be way worse. By no means will hackers and fraudulent acts reduce, in fact, if anything, the numbers are expected to increase at an exponential level. Why? The reason is simple, technology is becoming more accessible and there are a truckload of businesses springing up every now and then, hence, several avenues for cybercriminals and fraudsters to take advantage of.

One way to explain fraud in business is to use the analogy of a three-legged stool. The three legs of the stool represent the three elements that must be present for fraud to occur: opportunity, motive, and rationalization. These three elements are usually key to a successful fraud.

Opportunity refers to the ability to commit the fraud, such as having access to financial records, having data poorly guarded, greediness or being in a position of trust. Motive refers to the reason for committing the fraud, such as personal gain, vendetta or to cover up mistakes. Rationalization on the other hand, refers to the mindset or reasoning that allows the person or group of people to justify committing the fraud, such as believing that they are entitled to the money or that the company will never find out.

When all three legs of the stool are present, the risk of fraud increases. By understanding these elements and actively working to prevent them, businesses can reduce the risk of fraud and protect their financial interests.

In the digital age, fraud is no longer a crime confined to shadowy back alleys and underground networks. It has become a sophisticated, high-tech enterprise, with hackers and scammers using increasingly advanced techniques to steal sensitive information and defraud individuals and businesses. It is evident every year that fraud becomes more prevalent as organizations venture further into financial activities. It doesn't necessarily mean these organizations didn't implement measures. Is it possible that these measures were not sufficient or outdated at times? These types of questions must be addressed properly.

Factors That Encourage Fraudulent Attacks

Businesses are exposed to fraudulent attacks for a number of reasons. Some of these reasons are due to human errors or negligence. While sometimes, these attacks are not totally dependent on unprecedented errors, it could be as a result of the scantily layered security measures. There are some common factors that contribute to this vulnerability.

1. Complexity: The more complex a business is, the more opportunities there are for fraud to occur. For example, businesses with multiple locations, employees, vendors, and partners may have difficulty keeping track of all their transactions and ensuring that they are all legitimate.

2. Lack of controls: Businesses that do not have strong internal controls, such as segregation of duties and proper oversight, may be more vulnerable to fraud. This can be especially true in smaller businesses where there may be fewer resources dedicated to fraud prevention.

3. Weak financial reporting: Businesses that do not have robust financial reporting systems in place may be more susceptible to fraud because it can be easier for fraudsters to cover their tracks.

4. Insiders: Businesses are also vulnerable to fraud from insiders, such as employees or contractors, who have access to sensitive information and the ability to manipulate systems and processes.

5. Human error: Businesses are vulnerable to fraud due to human error, such as accidentally paying invoices to the wrong vendor or failing to properly verify the authenticity of a transaction.

6. Lack of segregation of duties: When one individual has complete control over a financial process, it can increase the risk of fraud. Segregation of duties means that different individuals are responsible for different aspects of a financial process, which can help prevent fraud.

Overall, businesses are vulnerable to fraud because of the many opportunities that exist for fraudsters to take advantage of. This is why it is important for businesses to have strong internal controls, financial reporting systems, and other safeguards in place to prevent and detect fraud.

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Measures To Prevent Fraud?

Preventing fraud in financial services requires a combination of technical measures, internal controls, and employee training. Here are some steps that financial institutions can take to prevent fraud:

1. Implement strong authentication measures: This can include using two-factor authentication, biometric authentication, or other methods to verify the identity of customers and employees.

2. Implement internal controls: This can include separating the duties of employees, conducting regular audits and reviews, and implementing policies and procedures to prevent and detect fraud.
3. Educate employees: Financial institutions should educate their employees on how to recognize and prevent fraud, as well as how to report suspicious activity.
4. Use fraud detection software: Many financial institutions use software that can detect unusual patterns of activity or transactions that may indicate fraud. 
5. Use data analytics: Financial institutions can use data analytics to identify trends and patterns that may indicate fraud. When there is enormous data available, the more the attackers can target. Data analytics can help to track anomalies internally and externally, giving you an overall picture of how to manage your data against breaches and attacks.
6. Collaborate with other financial institutions: Financial institutions can share information and collaborate with each other to detect and prevent fraud.
7. Monitor transactions: Financial institutions should regularly monitor customer transactions for any unusual activity or patterns that may indicate fraud.
8. Stay up to date on industry best practices: Financial institutions should stay informed about the latest fraud prevention techniques and technologies and implement them as appropriate.

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How Machine Learning Can Help To Prevent Fraud

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Machine learning is a method of training computers to learn and make decisions on their own, without explicit programming involved. It is based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention. With this, machine learning can be used to identify inconsistent patterns that reek of fraud and alert the administrator. 

Fraud is a costly and disruptive problem for businesses of all sizes. Traditional fraud detection methods, such as manual review and rule-based systems, can be time-consuming and may not always be effective at identifying complex or unusual fraud patterns. Fortunately, machine learning offers a powerful tool for detecting and preventing fraud.

Here are ways machine learning can help to detect fraud: 

• Anomaly detection: Machine learning algorithms can be trained to identify patterns of behaviour that are typical for a given user or system. When an anomalous event occurs, such as a sudden increase in spending or a login from an unusual location, the algorithm can flag it as potentially fraudulent.

• Risk scoring: Machine learning algorithms can be used to assign a risk score to a given transaction or event, based on factors such as the user's previous behavior, the amount of money involved, and the location of the transaction. Transactions with a high risk score can be flagged for manual review, while those with a low risk score can be automatically approved.

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• Fraud detection: Machine learning algorithms can be trained to recognize patterns of fraudulent activity, such as the use of stolen credit card numbers or the creation of fake accounts. The algorithm can alert security personnel or automatically block the transaction when such activity is detected.

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• Fraud prevention: In addition to detecting fraud, machine learning algorithms can be used to proactively prevent it from occurring. For example, an algorithm might be trained to identify the characteristics of a fraudulent transaction and block it before it can be completed. At Periculum, we can help organizations customize our machine learning models to help them monitor fraudulent activities. You can shoot a mail to our sales team at sales@periculum.io for a free demo on how your business can benefit from our machine learning models. 

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Overall, machine learning can be an effective tool for helping to prevent fraud by automating the detection and prevention of fraudulent activity.

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