How Does AI Detect Fraud?
What is fraud?
Fraud is a criminal offence where a perpetrator intentionally deceives a victim for an illegal gain or for depriving the victim of a legal right. According to the legal dictionary, fraud is “the intentional use of deceit, a trick or some dishonest means to deprive another of his/her/its money, property or a legal right.” Apart from monetary gain, there are other purposes of fraud such as obtaining a passport, travel document, or driver's license or qualifying for a mortgage.
In general, fraud involves the misrepresentation of facts, either by intentionally withholding relevant information or by providing false statements to another party for the specific purpose of gaining something. There are many types of fraud such as forgery, counterfeiting, tax fraud, credit card fraud, wire fraud, securities fraud, bankruptcy fraud, and internet fraud. These criminal activities are carried out by an individual, a group of individuals or a business entity. Fraudulent activities cost the global economy billions of dollars every year.
Financial fraud happens when a perpetrator deprives a victim of his/her money or harms the victim’s financial health through deceptive practices. There are different types of financial fraud:
- Identity theft: Here, the wrongdoer steals the victim’s personal financial information, such as credit/debit card number or bank account number, to make withdrawals from the victim’s account.
- Investment fraud: Here, the wrongdoer sells investment schemes or securities with false, misleading information such as false promises and insider trading tips. They may also hide certain facts about investment schemes to secure sales.
- Mortgage and Lending Fraud: It includes opening a mortgage or loan using others’ information or using false information. Separately, lenders may sell loan products with inaccurate information and deceptive practices.
- Mass Marketing Fraud: This type of fraud is done via mass mailings, telephone calls, or spam emails that are used to steal personal financial information or to raise contributions to fraudulent entities.
New avenues of fraud
The increasing use of the internet and other wireless communication methods have opened new avenues for fraudsters. In general, internet fraud or online fraud involves the use of the Internet and hiding of information or providing incorrect information for the purpose of tricking victims out of money, property, and inheritance. Some commonly found internet and wireless fraud types are:
- Wireless fraud/phone fraud: It is the use of telecommunications products or services for illegally acquiring money from, or failing to pay, a telecommunication company or its customers.
- Charity fraud: The scammer poses as a charitable organization (often via fake websites) soliciting donations to help the victims of a natural disaster, terrorist attacks, or epidemic.
- Internet ticket fraud: Here, a fraudster offers tickets (fake and never delivered) to sought-after events such as concerts, shows, and sports events.
- Online gift card fraud: Here, hackers steal gift card data, check the current balance through card providers’ online service, and then try to use those funds to purchase goods or to resell the cards/vouchers on a third party website. In cases where gift cards are resold, the fraudsters take the remaining balance in cash, which can also be used as a method of money laundering.
- Fraud using social media: Here, fraudsters make use of personally identifiable information of people (birthday, email, address, etc.) to steal users’ identities.
- Mobile payment fraud: Here, fraudsters create accounts within mobile payment technologies such as Google Wallet and Apple Pay using stolen credit card information.
What are the banking scams?
A banking scam or bank fraud is the use of illegal means to obtain money, assets or other property held by a financial institution or to obtain money from a depositor by posing as a financial institution. Often referred to as white-collar crime, bank fraud usually requires some sort of technical expertise to commit.
The banking fraud types include accounting fraud (where organisations use fraudulent bookkeeping to seek loans from a bank), demand draft fraud (where corrupt bank employees write fake demand drafts which are payable at a distant city), uninsured deposits and (uninsured or non-licensed bank soliciting deposits). Bill discounting fraud, card skimming, cheque kitting, document forgery, cheque forgery, bank inspector fraud, impersonation, payment card fraud, stolen cheques, identity theft and wire transfer fraud are other forms of bank fraud.
Methods of fraud detection
Many industries such as banking and insurance, which are more vulnerable to fraud, use various methods to prevent it. In general, fraud prevention is a set of procedures and activities to prevent money or property from being obtained through false representations. In order to do successful detection, financial institutions must have efficient systems that can screen financial transactions, locations, devices used, initiated sessions and authentication systems.
Traditionally, financial institutions use rules-based systems to detect fraud. These systems perform several fraud detection scenarios, manually written by analysts. Once a transaction complies with these rules or scenarios, they are approved. Often, these rules-based systems require adding/adjusting scenarios manually and they may not be able to detect implicit correlations, making them both inefficient and ineffective in modern times. They cannot process real-time data streams that are critical for the digital space.
The artificial intelligence (AI)-based approach to fraud detection in financial institutions has received a lot of interest in recent years. They are different and more efficient than the traditional rules-based approaches, which detect fraud by looking at on-surface and evident signals. AI-based fraud detection digs out subtle and hidden events in user behaviour that may not be evident, but still signal possible fraud. Technologies such as machine learning help create algorithms that can process large datasets with many variables and find hidden correlations between user behaviour and potential fraudulent actions. Machine learning systems can do faster data processing with less manual work.
Techniques used in AI fraud detection
As fraud is typically an act involving many repeated methods, statistical data analysis techniques and artificial intelligence (AI) techniques that can search for patterns and anomalies in data can be used as effective ways to detect fraud. The statistical data analysis techniques of fraud detection include the use of:
- Statistical parameters calculation
- Regression analysis
- Probability distributions and models.
- Data matching
Common AI techniques that are used to detect fraud are:
- Data mining: Data mining is used to classify, group and segment data to search through millions of transactions to find patterns and detect fraud.
- Neural networks: These are used to learn suspicious patterns, and further use those patterns to detect similar suspicious patterns ahead.
- Machine learning: Machine learning can automatically identify characteristics found in a confirmed fraudulent act so that similar instances can be detected in future.
- Pattern recognition: It helps detect classes, clusters and patterns of suspicious behaviour from a large volume of data.
Fraud and money laundering
Fraud often comes as a predicate offence for money laundering. The proceeds generated from fraud must be laundered to conceal their illegal origin and to incorporate them within the legitimate financial system. Money laundering detection in financial institutions often collides with fraud detection as well. Therefore, financial institutions are required to coordinate their anti-money laundering (AML) and anti-fraud operations to prevent criminal activities and avoid reputational damage.
There are AML software that can effectively detect fraud. The Tookitaki Anti-Money Laundering Suite, an end-to-end, AI-powered AML/CFT solution, is helping financial institutions help detect fraud among many other predicate offences.
To know more about our AMLS solution and book a demo, please contact us.