Today, most companies are making a lot of losses from fraud caused by third parties who get access to their data illegally. Most of the types of fraud can be managed by the in-house It team or even prevented by the different practices the staff may engage in to pursue data security. The types of fraud that the company cannot easily manage require being handled correctly and through technology. One of the ways to manage and protect data from fraud in the Fintech industry is through artificial intelligence tools and machine learning models. Below are the common types of fraud that you should consider managing through machine learning.

Phishing

Phishing can be termed as a type of cybercrime handled through emails appearing real to the person the fraudster may claim to be. Most of these people may contact you through contact and text messages that may convince you to do it. This is why most Fintech companies are entrusting fintech consulting firms such as bay partners cane bay partners towards dealing with impersonation. Through phishing, the fraudster acts as a specific organization asking for personal details that may be a financial risk.

Spoofing

Spoofing tends to have a little bit of similarity with phishing. This can be regarded as a fraudster gaining access to your details. This is especially details regarding your financial and private data that a company may own and significantly relevant to its functioning. Spoofing can be a hazardous form of fraud since it may convince an individual’s customers to deposit funds in a different account. This may be of significant loss and may even lose trust in your customers.

Identity fraud

Identity fraud can be referred to as the use of another person’s information to commit a crime. Most fraudsters involved in identity fraud always try to get away with the authorities when the investigations into the crime are started. It is always relevant for an organization to be cautious of whom they share their details with and secure their mobile phones and computers.

Money laundering

This is regarded as converting money from illegal activities such as drug trafficking to other ways, such as through banking. Through machine learning, a Fintech company can identify this fast and help the government and other institutions identify these kinds of people.

Insurance claim fraud

Some people are signed up to an insurance company but seek funds illegally from an insurance company through illegal claims. They are bearing in mind that the insurance companies will have to handle the compensation through the help of a financial institution; such kind of fraud is easily detected through machine-learning kinds, of course, making it easy for the compensating institution to save money.

Account fraud

It is illegal to use financial statements to claim that a particular account with money credited in it belongs to you or even if you own a certain percentage of the money. This is mainly known to happen when the initial bank account owner passes away or is in a condition that they cannot handle their finances.

Transaction fraud

This mostly happens when a stolen credit card is made to transactions when not authorized by the owner. This is why most financial institutions require their customers to report once their credit cards are stolen immediately. This is to prevent a third party from accessing cards through the card; failure to do this in time may land you severe financial losses and lead to being declared poor credit score.

Machine learning can be the most applicable way for a Fintech institution to detect fraud. The machine learning model helps you identify this as well as come up with ways to manage it.