Robbing a bank with a gun is obsolete. Today fraudsters commit robbery without even leaving the house.
Implementing a system for financial fraud prevention is crucial to reducing banking losses. PwC’s 2018 Global Economic Crime and Fraud Survey observed that 49 percent of the 7,200 companies they surveyed had experienced fraud of some kind.
The reported rate of economic crime has increased across all territories
Fraud has become common in many industries. Juniper Research has found three hot industries where fraud takes place most:
The reported rate of economic crime is on the rise
In this article, we will explain how the implementation of AI can help in financial fraud prevention and what benefits it can provide.
Fraudsters are experts at hijacking online sessions. They can steal your credentials and use malware and false positive or negative alerts to get data. Every day financial institutions search for the best alternatives to fight cybercrime.
Organizations continue to increase spending on combatting fraud
Credit card fraud is one of the most prevalent types of cybercrime. Fraudsters can use phone calls, emails, Wi-Fi hotspots, and even skimmers to obtain your personal data.
Scammers don’t need to hold your card in their hands. They steal the cardholder information online and use it illegally.
This happens as a result of “phishing”. During online communication, fraudsters ask you to provide personal data pretending that they are a trustworthy entity.
Scammers find another way around if a particular type of cybercrime has been prevented. The implementation of bots is the most usual type of mobile fraud attack.
In 2016, fraudsters created a bot on Facebook, which hacked 10,000 accounts by offering users a browser extension to install. It helped them to obtain users’ personal data on websites, including financial sites.
Fraudsters can create fake accounts, get access to accounts linked to a mobile phone and then steal credentials.
These attacks become more hackish. You cannot even assume that missed calls, recorded messages, text messages, ringtones, or phone insurance claims were legitimate or scams.
For example, they steal your data when you are offered to add a ringtone. You enter a unique code and it opens many ways for hackers to complete fraud.
Or fraudsters can present a claim that a phone was damaged, stolen or lost and try to recover money from an insurance provider
The fraud triangle: what makes an employee commit fraud?
This type of fraud is committed by an employee against the organization.
The employee misuses or misappropriates an employer’s resources or assets for personal use.
NetGuardians has stated that 70% of banking fraud is internal and most remains undetected.
Why does it happen?
Because an employee is a trusted person who has little supervision and will be suspected only at the very end.
The United Nations Office on Drugs and Crime announced that between $800 billion and $2 trillion goes through the money laundering cycle every year.
Money laundering means that fraudsters acquire the cash received via fraud.
How does it happen?
Fraudsters create an illusion that money from source A comes to source B. But the origin of money is misrepresented, as it has been obtained through illegal operations that look like legal ones.
Banking systems must be on the right side of the law and avoid being penalized.
That is why financial institutions regularly review sanction lists in multiple languages to verify that fund investors aren’t involved in any kind of financial crime or terrorism.
Scammers can commit identity fraud when a person uses Internet banking or makes payments via the Internet.
When they obtain another person’s personal information, it can be used fraudulently to steal money.
Fraudsters commit social fraud when they try to deceive or manipulate their victims into giving out confidential information.
You need to detect fake accounts and get rid of inappropriate content.
The financial services and technology industries are finding the most value in AI and advanced analytics
Since the computing capacity of cloud technologies has increased, sophisticated algorithms have become available for banks.
AI allows using more advanced algorithms that can differentiate acceptable and potentially fraudulent information.
Positive transactions can be placed in the express lane, reducing the risk of credit card fraud.
Many financial institutions have launched AI biometric technologies. They are split into two groups: physical and behavioral.
For example, ID Finance has implemented AI biometric technology successfully. They use behavioral data to estimate fraudulent cases, calculating how a person touches the screen, swipes, and types.
Physical biometric solutions investigate different human body parts: face, eye iris, DNA, veins, fingerprints. Then this information is transformed into a code recognized by the AI system.
Behavioral biometric solutions use other unique characteristics: typing rhythm, device interaction method, gait, voice, etc. A database stores this information and then applies it during the authentication or verification process.
In mobile banking, clients usually need only to log in with their username and password. To create additional difficulties for scammers, think about a second level of identity authentication.
The issue is that clients will need an authentication code, which will be sent to their smartphone in a form of a text message.
Let’s imagine this situation: fraudsters were waiting and then got the opportunity to steal your username and password. They think the main difficulty has been overcome.
But here is the trick.
With a second level of identity authentication in a banking management system, fraudsters will never be able to access data, as they must hold a person’s phone at the very moment of fraud.
A bank uses data analytics to measure geographical locations of payments and the time spent for them. This is called geotiming.
Example: Two in-person card payments appear in different locations without enough time elapsed for the customer to travel between them. This activity will be marked as fraudulent within seconds.
The method for preventing internal fraud is similar but focused on staff work-related activities.
The system collects data when a bank employee processes transactions, engages in phone conversations or website visits, etc.
Then it shapes a model of behavior for a particular role to detect internal fraud within minutes or hours.
Anti-money laundering systems can be built on blockchain technology.
Blockchain uses an open-source ledger to store and keep track of transactions. Parties can transact with each other in the blockchain network.
The information will be available to each node and suspicious activity will be detected for all participants.
How does it work?Each participant in a transaction has a cryptographic key and the parties in the network must approve this transaction.
After it becomes approved and completed, the encrypted block appears. This block joins the public ledger. But the transaction details stay private because of this cryptographic key.
If there is an alert of potential fraud, the transaction can be prevented automatically.
A blockchain-based AML platform allows you to audit data securely, monitor complex transactions, make records of suspicious ones, and provide the highest efficiency with minimal friction.
It is up to your business to choose which powerful tool to use for financial fraud prevention.
The biggest obstacle is a dilemma: you want to ease all transaction processes to provide a better user experience with your financial services. But it is hard to perform, as all advanced algorithms, technologies and two-step authentication processes take time and make the transactional procedure extensive.
By implementing AI biometric technologies, big data, blockchain technologies and a second level of identity authentications, you will reduce the risk of financial fraud significantly, prevent suspicious transactions, and apply possessed knowledge for further model refinement.