Artificial Intelligence is Becoming a Powerful Weapon in the Fight Against Fraud

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We’re now in the digital frontier. In today’s digital world, more people are shopping and banking online than ever before. For example, statistics show that by the year 2021, there will be an estimated 2.14 billion digital buyers worldwide, an online phenomenon driven by rapid technological advancements and economic globalization. As exciting as this significant increase in digital buyers may be for businesses hoping to reach these buyers, this growth in digital buyers has also caught the attention of cybercriminals worldwide. In 2018 alone, digital crimes accounted for an estimated $4.2 trillion in fraud losses, with $31 billion coming directly from the banking industry.

Consequently, fraud is becoming a bigger worry for businesses across many sectors. Luckily, advancements in artificial intelligence (AI) can assist in combating this growing risk. AI technology uses the power of computing to efficiently analyze significant amounts of data, establishing patterns that can trigger alerts in real-time all while avoiding human errors and biases. Machine learning—a branch of AI—is an essential strategy for both today and tomorrow's fraud-related business challenges.The ability to process data and make decisions without supervision can help meet the immense demand driven by millions of online transactions occurring every day. Let’s now take a closer look at how AI is helping three industries fight back against fraud while improving the digital customer experience.

Artificial Intelligence for Fraud Detection in Banking

The banking industry today is more competitive than ever, where offering access and convenience to customers has resulted in the creation of new digital channels for managing personal assets. From online banking to mobile apps, digital channels are offering customers a better overall experience but unfortunately, this comes with a significant increase in digital fraud risk. A new wave of digital fraud poses a multi-billion dollar challenge for the global banking industry. To address this challenge, banks and financial institutions are beginning to employ modern data science technologies to fight back against digital fraud. AI helps banks protect customer loyalty, discover adverse patterns in large data sets and decrease fraud losses for the organization.

One of the best ways the banking industry is using AI to battle fraud is having the capability to monitor a vast amount of transactions to flag suspicious behaviors occurring in real-time across any banking channel. Currently, most banks have individual fraud detection systems for each banking channel creating silos which block cross-channel fraud communication. AI allows banks to centralize their fraud detection platforms to obtain an enterprise view of suspicious behaviors occurring across any channel at any time. This helps cut down on cybercriminals’ attempts to hide fraudulent activity in one account while attacking another as a cat-and-mouse game to throw off fraud prevention teams. AI is helping banks discover these adverse patterns in real-time allowing for quick decisions and the ability to attack fraud at the source before it has a chance to spread to other accounts.

Artificial Intelligence for Fraud Detection in E-commerce

AI is nothing new to the online retail industry which uses this technology for the purpose of drawing in consumers to buy products and services. In retail, AI has historically been used more for customer experience and supply chain tactics. To show the value-add AI has for online retail, a 2018 survey found artificial intelligence could save retailers $340 billion by 2022. This is largely due to it helping create more efficient supply chain systems and customer interfaces which increase consumer access to information about products and services. With AI being a core competency for any business engaging in online retail, this same value-add process optimization can be channeled towards decreasing digital fraud risk, leading to lower losses.

One of the biggest fraud challenges for the e-commerce industry is false positives. False positives are when a legitimate transaction is flagged as suspicious which adversely impacts the customer experience and leaves consumer money on the table. One report estimated $118 billion is lost every year due to false positives occurring during online purchases. AI is meeting the challenge to decrease the number of false positives eroding consumer loyalty and company revenues by implementing new technologies to meet the rising fraud threat. Machine learning conducts deep analysis into this data to better predict transactions which truly exists outside of normal spending habits. The result is fewer false positives, a win for both consumer and online retailers. Moving forward it will be interesting to see how a reduction in false positives helps lower fraud expenses for online retailers and their banks.

Artificial Intelligence for Fraud Detection in Gaming

Gaming has come a long way since the days when Atari introduced the world to the start of the multi-billion dollar industry that would soon follow. Gaming, like most other technologies, has advanced significantly over the years, with online gaming becoming a major industry of its own. An industry bringing in around $33.6 billion this year from PC online games alone, not counting online gaming purchases on other gaming consoles like Xbox, PlayStation, and mobile devices. With 2.2 billion active gamers worldwide and 47% engaging in online purchases, this leaves over a billion individuals exposed to online fraud. The top ways cybercriminals exploit online gaming platforms is through account takeovers, synthetic IDs, bots, and spoof sites. These methods aim to exploit this lucrative market which is not heavily regulated and currently has a lack of cybersecurity standards in place for protecting customer data.

In the gaming industry, artificial intelligence is being used to protect profits not just to help create them. AI is being unleashed to tackle issues with in-game purchases which must occur instantaneously to not interrupt the gamer's experience. Data science methodologies like machine learning can process massive amounts of user data to help ward off transactions that are outside the norms of the user's normal patterns of activity. This technology helps capture suspicious activity in real-time while also not disrupting the gaming experience for users. Combining transaction and gaming data takes significant brain power to analyze which AI can handle, making it the perfect weapon for online gaming platforms to ward off cybercriminals looking to exploit their booming market.

In Conclusion

No matter the industry, any company engaging in online data transfers is exposed to adverse fraudulent activity. These days, it is not a matter of if, but when a company will be targeted by cybercriminals to carry out an illicit online activity which hurts both the consumer and merchant. With great advancements in artificial intelligence technologies, businesses across all industries from e-commerce to online gaming are fighting back to keep their customers and revenues safe from external threats.

AI methodologies like machine learning have the deep-thinking capabilities to process massive amounts of data in real-time which gives any business a fighting chance to stop fraud in its tracks and keep transactions safe.