arrow left facebook twitter linkedin medium menu play circle

Best Practices for Fraud Managers: Selecting a Fraud Prevention Solution – Part III

By Julian Wong September 19, 2018

Photo of Julian Wong

about Julian Wong
Julian is the VP of Customer Success at DataVisor. A proven leader in the realm of trust and safety, Julian developed scalable systems and teams for mitigating fraud and abuse at Indiegogo, Etsy and Upwork. Julian also led Google’s engineering team responsible for building algorithms to prevent fraud on its ad platform.

This blog post is the third and final part of a three-part series highlighting some of the key things to look for when it comes to choosing a third-party fraud prevention solution. Please be sure to check out part one and part two.

The first two posts of this series highlight some key things to look for when it comes to selecting a third-party fraud prevention solution. Among those things are multiple layers of protection, dashboards with engaging visualizations, and the ability to access real-time data. This final post in the series highlights a few more things fraud operations managers should look for in a third-party fraud prevention solution.

Adaptability and Scalability

Some organizations are using rules-based systems to detect and prevent fraud. These systems require humans to create and maintain rules regularly. Some companies are using systems that require humans to create labeled training data to tune models. There are benefits to using these types of fraud prevention systems, but there are also limitations which we discuss in this white paper.

Many fraudsters today use a variety of advanced tools to commit fraud at tremendous speeds and scale- tools such as bots, content scraping apps, and mass registration software. Systems that rely heavily on human intervention are unable to detect new fraud attacks quickly enough or at scale. Organizations must choose a fraud prevention solution that can adapt and scale just as fast as fraudsters.

Organizations should look for a solution that combines the power of machine learning and the domain expertise of business rules. Machine learning allows a fraud prevention solution to analyze data at a speed, scale, and accuracy far beyond the capabilities of humans. Machine learning also allows many processes to be automated. For example, our Automated Rules Engine is powered by machine learning allowing new rules to be automatically created when our UML Engine discovers suspicious attributes. Automating the rules creation process allows our fraud prevention solution to detect attacks proactively and adapt to new types of attacks quickly.

Scalability is another thing to expect from a fraud prevention solution. The solution should allow companies to load all their data at once. It should be able to not only connect to real-time data but also ingest and analyze vast volumes of data from many disparate sources. In order to do these things, the solution must be built on a highly scalable infrastructure.

Easy Integration and Flexible Deployment

Once the team has reviewed the features of each solution and narrowed down the choices, there are still two more crucial things to consider: integration and deployment. A solution should not be too difficult and time-consuming to integrate. The vendor should provide an easy to use API or SDK so that the solution can be integrated with systems quickly. Ideally, the solution will also include built-in integrations for specific fraud use cases. For example, DataVisor features built-in integrations for Adjust, AppsFlyer, and Tune which can be used to detect app install fraud. Pre-built integrations allow for instant data connections and make it easier for companies to send, receive, and manage data.

Flexible deployment options are also important. You should be able to deploy the fraud prevention solution where needed which could be on the cloud, on-premises, or on both. DataVisor supports many public clouds including AliCloud, AWS, Azure, and Google. DataVisor supports private cloud and on-premises deployments. And we offer batched and real-time data connection choices to meet your specific fraud detection needs.

There is Much to Consider

When it comes to choosing a third-party fraud prevention solution, there is much to consider. The best way to find out if a fraud prevention solution is right for you is to try it out. A reputable vendor will offer a trial.

Popular Posts

Intelligent solutions. Informed decisions. Unrivaled results.

DataVisor Digital Fraud Trends Report: Q1 2020

Learn More

Download the new “State of Sophistication in Fraud” report from DataVisor to ensure your business is equipped to…

Download the new “State of Sophistication in Fraud” report from DataVisor to ensure your business is equipped to prevent high sophistication threat attacks.

A Guide to Centralizing Data Intelligence

Learn More

Discover AI-powered fraud strategies for preventing financial and reputational damage in this powerful e-book.

Online marketplaces withstand a complicated array of fraud attacks—spam, scam, and all points in between. Only the most comprehensive, proactive AI-powered solutions can fully protect against reputational and financial damage. This e-book details the entire lifecycle of a fraud attack, and lays out…

A Practical Guide to Eliminating False Positives in Fraud Management

Learn More

This e-book explores the next generation of fraud prevention technology, which applies unsupervised machine learning to reduce false positives and risk.

This e-book explores the next generation of fraud prevention technology, which applies unsupervised machine learning to reduce false positives and risk.

Protect your business, your customers, and your data.

Request Demo