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In todays digital landscape, where it is so easy to do anything and everything online, the importance of fraud detection and security cannot be ignored. Whether its online money transactions,sharing of sensitive or personal information, it can all be done in a click. And just like that, it can also go away in a click.

As digital transformation in the form of AI takes over 2024, let us learn how it can help you effectively detect fraud and save you from major blunders.

Why Do You Need Fraud Detection and Security?

There is no doubt that the digital takeover has provided a plethora of opportunities for people and for businesses but it has also provided an easy space for fakes and fraudsters. And that is why you need to stay protected because prevention is better than cure.

Financial losses are a major problem given how easily transactional processes can be intervened by frauds. It can also lead to identity theft and cause major financial instability in the future.

If you have an online business, you need to be very cautious with your security system. Because, obviously, it can cause you enormous losses. But let’s say you recover from those losses, it will leave a mark on your business’s presence, and you will lose customer trust and loyalty. It will destroy the reputation of your business and people will feel less reliant on your products and services.

AI and Machine Learning Systems have all the acquired capabilities and processing powers to quickly analyse large amounts of data and identify patterns of fraudulent activities.

They are especially useful in industries with high transaction values such as finance and ecommerce. ML algorithms can quickly adapt changes in fraud patterns. They can also learn from data, a problem that rule-based detection systems struggle to deal with.

The Most Common Types of Fraud

AI has been designed in such a way that it can detect almost any type of fraudulent activity. Lets see what they are.

• Card Fraud – Credit card fraud is very common nowadays. Fraudsters use automated bots to attack payment gateways. It is also considered as identity theft, because, often, credit cards are used for multiple transactions without any authorization.
• UPI Fraud – Lets say that you use PhonePe a lot (which is very common in this generation). That would mean you get a lot of messages about your transactions. Which makes it really easy for a scammer to send such a transactional message and take hold of your bank account.
• Identity Theft – Imagine someone else takes over all your social media accounts, retrieves your personal information, licences, security numbers — that basically means your entire life. He or she can also commit crimes using your name and identity.
• Healthcare Fraud – This basically refers to billing anomalies that occur due to false information. For example, suppose the scammer takes a medical checkup or needs to get it done for someone close to him/her, but they do not have adequate money. Now suppose, you are getting a checkup at the same place, they can easily check the logs for your information and use your bill as theirs. In another scenario, providing false medical reports or using someone else medical reports as your own is also considered healthcare fraud.
• Insurance Fraud – This is such a common form of deception that we’re sure you also know. Agents use false IDs to make themselves believable as life insurance or health insurance providers and later deceive contacts. It is basically the online version of conmanship.
• E-commerce Fraud – It is another form of cybercrime where they can block transaction gateways in online shopping portals and retrieve personal information from a customer. So when you’re buying from unregistered websites, such a fraud can happen to you.
• Phishing – Another term we can use here is mail fraud. You know how you keep getting bombarded with emails from various different companies that offer you jobs or courses? Those are phishing emails that scammers send to retrieve illegitimate gains.

How Does AI and ML Play a Role in Fraud Detection and Security Systems?

There are actually countless ways that one can use AI and machine learning to detect fraud. Here are some of the best techniques that you can apply

• Natural Language Processing (NLP) – This tool is used to monitor emails and text messages to detect fraud. NLP techniques excel at analysing content and sentiment to understand whether a text is genuine or not. For example, gmail spam is an NLP technique where the tool detects which emails are spam or fake and sends them right to the spam or the bin folder.
• Deep Learning – With deep learning techniques, object detection and segmentation becomes very easy. Even with high volumes of data, this technology can detect the position of an object or target through images or videos. For example, in cases of identity theft, deep learning can help track large amounts of data related to transactions to find out where and when your information was released and locate where it has been used last.
• Machine Learning – ML can easily process and analyse complex data and discover abnormalities in patterns to detect fraud. For example, as mentioned above, you are running an ecommerce business where you come across multiple transactions as people purchase products. Here, out of 10, at least 2 of those transactions are likely to be fake. This is where ML comes in and detects it for you before the purchase is made.

Apart from that, you can also use certain AI tools for security systems They are

• Video Content Analytics (VCA) – Using VCA helps in monitoring and capturing video streams of a particular place. For example, CCTV cameras are a popular VCA tool that can be used for any social security system. You can install them in offices, your homes, retail stores and so on. You also must have noticed CCTV cameras on roads.
• Facial Recognition – This tool detects the facial structure of a person and can also perform sentiment analysis. When it comes to security, it basically entails recognizing the face of genuine and identified people and keeping strangers away. For example, face lock tools in phones use facial recognition AI in order to unlock your phone. So, if an unknown person tries to unlock your phone, they simply won't be able to do so as the tool does not recognise them.
• Biometric Recognition – The example mentioned for facial recognition works for biometric recognition as well. Most smartphones have the fingerprint feature. So, what this tool does is recognize your fingerprint and not allow an unknown fingerprint to enter your phone. Similarly, this technology can be applied in other ways as well, such as, to secure employee identity in offices, in locker systems, even in home safes, and so on.

Wrapping Up

Almost all industries are navigating through these challenges they face but the inclusion of AI in almost all aspects of the digital world has opened up many dark tunnels and provided light to them, the biggest ones being the detection of fraud and ensuring social security at every step of the way. Whether you have an ecommerce business or a retail store, you are sure to benefit from AI this year on, and experience the domination that it brings to the table.