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Online Fraud Prevention for a Better Internet

By Jason Tan  / 

14 Oct 2019

The global community is getting more and more interconnected. The internet enables people and businesses to expand their reach and connect with others around the world in amazing and unprecedented ways. We truly are in the middle of a digital transformation, and it’s just getting started. More than half the world’s population is online, with many accessing the internet solely through mobile devices, allowing them to stay connected wherever they go. From a business and financial standpoint, eCommerce only represented about 14% of all retail sales in 2018, a statistic that will significantly increase in the future.

But as internet usage grows, so do the dangers of internet fraud. Annual online fraud losses are projected to top $48B by 2023. Without some degree of stewardship, the internet would turn into a digital war zone, with armies of fraudsters running rampant, taking whatever they want – money, personal data, account credentials, identity and credit information. The internet should be an egalitarian and open platform for everyone. To allow it to be corrupted by mistrust and fear is something that cannot happen. 

Making the Internet a Safer Place

We believe in order to preserve trust in the internet, stewardship in the form of online fraud prevention solutions like Sift is required. Our common goal is to make the internet a safer place so businesses and their users can trust that their interactions are protected. If that trust is broken, we all suffer – businesses and users alike.

But building an effective fraud prevention solution is difficult, especially when the goal is to deliver great customer experiences. Many businesses attempt to find and create a solution themselves but go with obsolete methods. They implement rules that test every user – from trusted to unknown – in the same way, hoping to weed out fraudsters, much like how every passenger needs to go through airport security. While effective, a solution based on rules or CAPTCHAs alone, where even low-risk users are treated as potential criminals, also results in false positives, bad experiences, and lower conversions. 

It is possible to build a solution that stops fraud and delivers great user experiences, but it requires machine learning to proactively analyze an immense amount of data that is generated as users interact with a site. With a machine learning-first fraud prevention solution, a business can utilize that data, automate processes, tailor experiences based on risk level, and stay ahead of constantly changing online fraud schemes.

Unfortunately, most companies don’t have the resources to create a machine learning-first solution themselves. They don’t have the expertise, time, or access to the amount of data needed to build accurate models. They are stuck doing it the old way. Large tech companies can find and hire engineers to build large-scale, real-time ML solutions but why should they be the only ones to have access to that technology? That’s why at Sift we want to democratize online fraud prevention, restore trust to the internet, and provide all companies the power of machine learning to protect and grow their business while delivering delightful experiences to their trusted users.

Our Take on Online Fraud Prevention

Sift enables our customers with the technology, community, training, and partnership needed to effectively prevent online fraud and provide great user experiences. Sift creates custom machine learning models tailored to each unique business that we work with, fine-tuned to spot attacks other solutions miss. We also analyze more than 35 billion events per month from the global network of our customers’ sites, which improves our models and enables us to provide the most accurate internet fraud prevention solution in the industry. The more businesses that adopt Sift, the more the entire internet community benefits. And we partner with our customers at every step of their journey to serve their unique needs and forge trusted long-term relationships.

The accuracy of machine learning models depends on data. The more data points we collect with predictive value, the more effective we are at contributing to a better internet, ultimately serving the greater good of online businesses and users. We only use data for the purposes of detecting and preventing fraud and abuse on the internet, allowing businesses to make better data-driven decisions, and stop attacks before they happen. And we never sell data to anyone.

In fact, our services are designed from the ground up to prevent the type of privacy, security, and online integrity issues that led to regulations like the California Consumer Privacy Act (CCPA) – the misuse of personal data. Furthermore, the General Data Protection Regulation (GDPR) in the European Union specifically calls out fraud prevention as a legitimate interest to businesses, meaning the processing of data for the purposes of fraud prevention is beneficial for the greater good.

Services like Sift are essential to preserving a safe and frictionless internet. Without solutions that proactively combat cyber fraud, many businesses cannot survive, and every user would be treated with the same level of scrutiny as fraudsters – guilty until proven innocent. Our ultimate goal remains the same: we want to make the internet a safer place while proactively preventing fraud, streamlining operations, and driving revenue growth for our customers. If you’d like to learn more about how we operate, check out the following posts:

  • Sift Data Privacy Policy
  • Commitment to Data Privacy
  • Sift Scores – Growing & Protecting Businesses

Related

fraud preventionmachine learningSift

Jason Tan

Jason Tan is the Founder and Executive Chairman of Sift. Fueled by a passion for building great products and amazing teams, he's also held leadership and engineering roles at BuzzLabs, Optify, and Zillow.

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