Stopping Fraudsters From Taking The Travel Industry For An $11B Ride

Fraud attacks’ frequency and complexity will likely continue to rise despite merchants’ best efforts to prevent them.

Bad actors are tapping into personally identifiable information (PII) gathered from previous hacks to orchestrate their increasingly sophisticated efforts, including data purchased from the dark web to hide their tracks or pieces cobbled together from several victims to create difficult-to-detect synthetic identities.

Advances in cybercrime mean merchants often have issues combatting the attacks executed against them, especially if they are relying on legacy systems to do so. Many are turning to artificial intelligence (AI), machine learning (ML) and other advanced learning solutions to prevent and detect breaches before they can cause large-scale problems, but bad actors are using the same set of tools to sidestep authentication processes or impersonate legitimate customers. Manual processes will thus no longer make the preventive system cut.

In the March Merchant Fraud Decisioning Playbook, PYMNTS examines how AI and ML are enabling merchants to gather information from various data sources, transforming those details into actionable insights and bypassing the manual reviews that can leave them unable to keep up with fraudsters’ ever-evolving efforts.

The Latest Fraud Decisioning Developments

Fraudsters appear to be finding success in new versions of the age-old heists. Phishing attempts surged 640 percent last year alone, with hackers placing malicious URLs on domains such as Apple, Dropbox, Facebook, Google, Microsoft and PayPal, according to a recent report. Users who clicked the links would see their computers infected with viruses. Malware targeting computers running the Windows 7 operating system were especially hard-hit, rising 125 percent, according to the report.

Solution providers around the world are preparing to counter such attacks. Madrid, Spain-based security firm buguroo is combatting account opening fraud with its bugFraud solution, which uses deep learning to detect fraud by measuring how application processes compare to legitimate transactions. The United Kingdom’s RELX, an information and analytics firm, has meanwhile purchased fraud prevention firm Emailage to boost its own anti-fraud efforts.

A surprising tactic is emerging to thwart such preventative efforts, however. Fraudsters are now using low-cost, sweatshop-style workforces from countries such as the Philippines, Russia and the Ukraine to create larger numbers of crimes. The perpetrators caused a 90 percent increase in fraud attacks between October and December 2019, and appear largely focused on new account registrations and logins across eCommerce, gaming and social media platforms.

For more on these stories and other recent fraud decisioning headlines, read the Playbook’s News & Trends section.

How Emerging Travel Group Is Using AI To Weather Fraud-Related Turbulence

Fraud is expected to cost the travel industry more than $25 billion this year, meaning online travel aggregators will need to up their security efforts — or risk losing their customers to platforms that will. Balancing seamless-but-fraud-free user experiences requires careful effort, however. Lax security steps that are frictionless for consumers may let bad actors in, for example, but those that require too much work from customers can result in lost sales. In this month’s Feature Story, Felix Shpilman, CEO of global online hotel accommodations and travel services provider Emerging Travel Group, discusses how the company has fought chargebacks and other scams with AI- and ML-powered solutions while offering consumers more seamless and satisfying experiences.

Deep Dive: Betting On Positive Friction To Thwart Fraud

Emerging fraud techniques and evolving cybercriminal skillsets have merchants digging deep into their prevention toolboxes for the right anti-fraud approaches. Many online firms are embracing the concept of well-placed frictions in authentication processes to foil such attempts, adding just enough verification to keep bad actors from success without alienating legitimate users in the process. This month’s Deep Dive explores how ML tools can work with techniques like device fingerprinting to facilitate strategic “positive frictions” that protect companies’ finances, data and operations without hampering customers’ experiences.

About The Playbook

The monthly Merchant Fraud Decisioning Playbook, a PYMNTS and Simility collaboration, highlights how eCommerce merchants, financial institutions and other businesses are embracing fraud decisioning solutions to reduce chargebacks and account takeovers, thereby enabling secure and seamless experiences for legitimate users.