How AI Detects Online Fraud: Methods & Effectiveness
Virtually every industry in the business environment is investing in or at least considering making investments in artificial intelligence (AI), including machine learning (ML), one of the most well-known subsets of AI. Advanced AI and ML solutions have and will continue to transform sectors like manufacturing, consumer electronics, marketing, and health care, among others.
As the world becomes increasingly digital, AI and ML solutions can provide much-needed assistance to various types of companies, government agencies, and individuals. Consider how cases of identity theft and other forms of online fraud are rising, leaving businesses struggling to face the negative consequences.
Online fraud is not new. However, AI plays a major role in helping organizations detect and respond to fraud. Below, learn more about how AI is beneficial in online fraud detection, some of the methods companies employ for AI-based fraud detection, and how effective these methods can be to stop cases of fraud in their tracks.
A Brief Overview of Online Fraud
Fraud detection serves an essential function in the modern business world. From e-commerce brands to financial institutions and everything in between, various types of online fraud, also called internet fraud, can impact a wide range of public and private organizations.
North Carolina’s Office of Information Technology defines online fraud as any scheme that uses the internet to publish fraudulent solicitations, transmit money earned through fraudulent activities, or conduct fraudulent transactions. Some popular types of internet fraud include, but are not limited to:
- Advance fee (Nigerian letter scams)
- Counterfeit checks
- Credit or debit card fraud
- Pyramid schemes
- Business or employment scams
- Investment schemes
- Nondelivery of goods or services
Identity theft and phishing attacks are also common examples of internet fraud. Both of these crimes are threats to anyone using the internet, especially users who store sensitive data, like Social Security numbers (SSNs) or credit card numbers.
Benefits of AI-Based Fraud Detection
AI-based fraud detection solutions are indispensable for the modern organization. These systems leverage the power of AI to learn about fraud, detect cases of fraud, and keep a business operating smoothly. Below are the main benefits offered by AI-based fraud detection solutions:
- A fast and efficient form of fraud detection that works 24/7
- Reduced human labor and error
- Better predictions based on the ability to examine large data sets
- Identification of unique, sophisticated fraud traits humans may not identify
- Has a successful track record, particularly in banking and insurance fraud detection
These benefits make AI-based fraud detection systems worthwhile investments for most companies. However, it’s commonly understood that AI and ML tools work best alongside skilled human employees.
While AI and ML models typically require less human oversight compared to traditional business technologies, businesses should still consider retaining employees to support fraud detection initiatives.
3 Methods: Leveraging AI for Fraud Detection
Below are three methods of using AI to detect cases of online fraud some businesses employ to improve their fraud detection strategies.
1. Financial Institutions, Insurance, and Compliance
Fintech companies, banks, and insurance providers work with highly sensitive customer data and must meet various compliance requirements to operate successfully. Therefore, the role of establishing good fraud detection practices is even more important in these industries.
For example, Bank of America uses AI for various purposes, including fraud detection. The organization uses AI to comb through data regarding past fraudulent transactions. The AI develops an understanding of what makes a transaction suspicious and is trained to flag any potential fraud in the future.
2. E-Commerce and Transaction Fraud
E-commerce businesses must complete thousands of transactions per day, which can be challenging for even the most seasoned fraud managers.
With an AI-based fraud detection system, managers can input historical data to understand why past cases of fraudulent transactions were not flagged. From there, companies can gain valuable insights into their current fraud detection strategies and make adjustments to detect fraud more effectively.
3. Online Gaming and Suspicious Account Behavior
Online gaming companies, like casino apps and betting platforms, are becoming more popular among consumers. However, they also increase the risk of fraud. Experian suggests that as more people spent time at home during the pandemic, cases of online gambling fraud increased.
As a result, online gaming companies and other entities in the gaming industries are leveraging AI fraud detection to flag suspicious accounts. Some solutions require users to go through an identity verification process, helping to reduce the chances of fraud. Additionally, these companies can meet compliance requirements by checking users’ ages to ensure they’re gambling legally.
Are AI-Powered Fraud Detection Methods Effective?
Ultimately, companies must have sound fraud detection protocols in place when conducting investigations, whether internally or externally. The three methods described above suggest that AI-powered fraud detection systems are effective. However, companies must understand that there is no one perfect technology or software solution that will catch every instance of fraud.
Unfortunately, cases of fraud are common and no business is entirely immune from facing some form of fraud. Organizations across the globe lose trillions of dollars annually due to fraud, and consumers lost around $5.8 billion due to fraud in 2021, 70% more than the previous year. That figure could be even higher if unreported cases were counted.
The Future of AI for Fraud Detection
Fraud is a serious problem many industries are grappling with, especially during the global pandemic. However, using the latest advanced technology like AI and ML for fraud detection purposes can prove effective for organizations.
The upfront costs for these solutions might be high, but businesses that are serious about defending their customers and assets should consider making these worthwhile investments.