How Can Machine Learning Help in Fraud Detection?
Machine Learning has always been proven to be useful for solving real-world problems. This is the reason why it is widely used in every field ranging from medicine, eCommerce, the banking sector, insurance companies, and many more. Unlike earlier when all the reviewing tasks were accomplished manually, now every sector has accepted the power of Machine Learning because of its advancement in statistical modeling.
With digitalization, fraud has been a major issue in every sector for years. Now, every sector has accepted online transactions through different payment options such as credit/debit cards, PhonePe, Gpay, Paytm, etc, resulting in increased fraudulent activities. Here comes the role of Machine Learning which is designed with fraud detection algorithms helping different sectors solve these real-world problems.
Common Types of Internet Frauds & Application of Machine Learning Fraud Detection:
Previously, industries used a manual rule-based approach for fraud detection in which the algorithms were written by fraud analysts based on strict rules. In case, there is a new fraud, then they are done manually. As a result, it is more likely to have false positives. But, nowadays Machine Learning in Artificial Intelligence resolves most of the issues that are quite impossible to deal with manually. The major types of Internet Fraud include:
- Email Phishing
- Payment Fraud
- ID Document Forgery
- Identity Theft
Email Phishing:This is a kind of fraud or cybercrime by which attackers send fake sites and messages to users via email. These messages and sites are more likely to look legit and authentic that anyone can misjudge them. As a result, they enter vulnerable data resulting in putting them at risk. Traditional phishing methods involve the use of filters that are primarily of two types, authentication protection, and Network Level Protection.
Now, Machine Learning algorithms have automated all these methods for classification and regression. It can easily differentiate between actual and spam email addresses helping to prevent these frauds. In addition, it helps experts read into the subject lines, the content of the emails, and the sender’s email details before segmenting them.
Payment Fraud:Nowadays, frauds related to payment systems are prevalent. It is because, fraudsters now find loops to steal cards, make counterfeit cards, steal Card IDs, etc. Thus, they can easily steal the confidential data of the users and use them to buy things and even apply for a loan. Simply put, they can do anything they imagine with payment fraud.
Machine Learning has a separate detection model that can easily identify the payment features and methods used in the past against the current techniques. This is the reason why this model is highly preferred for use in transactions where the physical card is not essential.
ID Document Forgery:Nowadays, ID Document forgery is also increasing. It enables fraudsters to buy ID proof of a person and use that to enter a system and make use of it. Today, this type of fraud is increasing the risk factors for many organizations by assessing their systems and faking ID Documents. After all, these cheaters are skillful in creating more legit IDs.
The Machine Learning algorithm is designed with a neutral network that can effectively differentiate a fake and original identity resulting in creating a full-proof system.
Identity Theft:Cybercriminals are now well-equipped to hack into the accounts of their victims and gain access to their credentials like names, bank account details, email addresses, passwords, etc. Thus, very naturally they cause harm to their victims mainly through the three types of identity theft namely real name theft, account takeover, and synthetic theft.
The Machine Learning model ensures that nobody can change the password or update the identity associated with an account. Once a hacker tries to hack into an account or change the details, you will be notified. It is because this model is designed with two-factor security and other effective measures. Needless to say, it is also backed by human-like intelligence ensuring better prevention of fraud.
Benefits of Using Machine Learning in Fraud Detection:
Now look at some factors for why organizations now prefer Machine Learning techniques for detecting frauds:
- Speed:Machine Learning is gaining popularity for its fast computation process. Simply put, it is capable enough to analyze, process data, and extract new patterns from it in minimal time. Unlike the traditional manual process which is more time-consuming, Machine Learning algorithms can detect fraud automatically without any error.
- Scalability:Machine Learning process can be fed more and more data as compared to the traditional Rule-based fraud detection model. It is more accurate in fraud prediction. This is the reason why a Rule-based system is not preferred by professionals in recent times. But, make sure you hire a dedicated team of Data Science professionals from a leading Digital Marketing Company like Gaurish Technologies, Gwalior. It is because only skilled and experienced professionals can perform the task most effectively.
- Efficiency:Machine Learning model is capable enough to perform the redundant task of data analysis and finding hidden patterns repetitively. In simple words, this model is proved to be better in providing results in comparison with manual efforts. Moreover, it can effectively avoid the occurrence of false positives due to their authentic way to detect these patterns. It enables professionals to focus on more advanced and complex patterns.
- Cost Effective:With the Machine Learning model, the expert team can handle a large amount of data while offering data in real-time for better decision-making capabilities. As a result, the team will be able to easily meet the requirements of the end users resulting in improving the overall outcomes.
So, when it comes to detecting the suspicious activity of any organization, Machine Learning techniques are proven to be more reliable than human review and transaction rules. Today, several leading organizations have realized the utility of this process in improving customer experience through technology.
Gaurish Technologies, Gwalior being one of the leading Digital Marketing companies in India always tries our best to help businesses improve their productivity by offering quality Machine Learning services enabling them in rapid decision-making, business process automation, and faster anomaly detection through myriad Machine Learning techniques.