Virtually every industry in the business environment is investing or at least considering investing in artificial intelligence (AI), including machine learning (ML), one of the best-known subsets of AI. AI. Advanced AI and ML solutions have and will continue to transform industries such as manufacturing, consumer electronics, marketing, and healthcare, among others.
As the world becomes increasingly digital, AI and ML solutions can provide much-needed assistance to various types of businesses, government agencies, and individuals. Consider how cases of identity theft and other forms of online fraud are increasing, leaving businesses struggling to deal with the negative consequences.
Online fraud is not new. However, AI plays a major role in helping organizations detect and respond to fraud. Below, find out how AI is beneficial in detecting online fraud, some of the methods companies are using for AI-based fraud detection, and how effective these methods are in stopping fraud cases in their momentum.
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 known as internet fraud, can impact a wide range of public and private organizations.
The North Carolina Office of Information Technology defines online fraud as any system using the Internet to post fraudulent solicitations, transmit money earned through fraudulent activities, or engage in 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
- Non-delivery of goods or services
Identity theft and phishing attacks are also common examples of Internet fraud. Both these crimes are threats to anyone using the Internet, especially users who store sensitive data, such as social security numbers (SSN) 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 instances of fraud, and keep a business running smoothly. Below are the main advantages offered by AI-based fraud detection solutions:
- A fast and effective form of fraud detection that works 24/7
- Reduced human labor and errors
- Better predictions based on the ability to look at large datasets
- Identification of unique and sophisticated fraud traits that humans cannot identify
- Has a successful track record, particularly in the detection of banking and insurance fraud
These advantages make AI-based fraud detection systems attractive investments for most businesses. However, it is commonly accepted that AI and ML tools work better alongside skilled human employees.
Although AI and ML models generally require less human oversight compared to traditional business technologies, companies should still consider retaining employees to support fraud detection initiatives.
3 Ways: Leveraging AI for Fraud Detection
Below are three methods of using AI to detect cases of online fraud that some companies are using to improve their fraud detection strategies.
1. Financial institutions, insurance and compliance
Fintech companies, banks and insurers 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 a variety of purposes, including fraud detection. The organization uses AI to navigate 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 transactional fraud
E-commerce businesses have to perform thousands of transactions per day, which can be difficult for even the most experienced fraud handlers.
Using an AI-based fraud detection system, managers can capture historical data to understand why past instances of fraudulent transactions have gone unreported. From there, businesses can gain valuable insight into their current fraud detection strategies and make adjustments to detect fraud more effectively.
3. Online games and suspicious account behavior
Online gaming companies, such as casino apps and betting platforms, are becoming increasingly popular with 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 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 risk of fraud. Additionally, these companies can meet compliance requirements by verifying the age of users to ensure they are gambling legally.
Are AI-based fraud detection methods effective?
Ultimately, companies must have strong fraud detection protocols in place when conducting investigations, whether internal or external. The three methods described above suggest that AI-powered fraud detection systems are effective. However, businesses need to understand that there is no perfect technology or software solution that will catch every instance of fraud.
Unfortunately, instances of fraud are common and no business is entirely immune to some form of fraud. Organizations around the world lose billions of dollars a year due to fraud, and consumers have lost approximately $5.8 billion due to fraud in 2021, 70% more than the previous year. This figure could be even higher if unreported cases were counted.
The Future of AI for Fraud Detection
Fraud is a serious problem facing many industries, especially during the global pandemic. However, using the latest advanced technologies such as AI and ML for fraud detection purposes can prove effective for organizations.
Upfront costs for these solutions can be high, but companies that are serious about defending their customers and their assets should consider making these cost-effective investments.