August 3, 2022

Let’s Get Real: There is No Silver Bullet for Cyberfraud

Data quality is and will always be at the top of researchers’ minds in the insights industry. How in today’s ever-evolving climate can you trust that your data is reliable?…

Let’s Get Real: There is No Silver Bullet for Cyberfraud
Lisa Wilding-Brown

by Lisa Wilding-Brown

Chief Executive Officer at InnovateMR

Data quality is and will always be at the top of researchers’ minds in the insights industry. How in today’s ever-evolving climate can you trust that your data is reliable? Even though this issue has grown and changed over time, it remains fundamentally the same: there will always be fraudsters looking to cash out on survey incentives.

There isn’t a silver bullet for cyberfraud, and there is no way for any one company to completely solve this issue. I’ve spent the lion’s share of my career studying fraudsters, understanding their motives and tactics, and building solutions to be more proactive in catching these nefarious users. I’m deeply passionate about this topic, and I strongly believe it is time for our industry to have a major wake up call.

In my testing over the years, I’ve seen sample providers large and small deal with this problem. It isn’t a matter of if, but when you will encounter an issue with sample quality. According to Accenture, 68% of businesses today feel that their cyber security is at risk on multiple fronts, and this is expected to rise in future years as fraudsters become increasingly sophisticated. Cybersecurity Ventures, a leading security publisher recently featured in Forbes, predicts that cyberfraud will cost $10.5 trillion globally by the end of 2025. It’s a very real and material problem, not only for our industry, but many others as well.

There are many resources available to fraudsters that explain how to start to process. There are videos on how to start a device farm and where to buy inexpensive phones. YouTubers have a ready-made bot that you can freely use and even upgrade to a more powerful version. There are tutorials outlining the blueprint of success for a survey screener; they know what the insights space routinely looks for. Another helps viewers leverage residential proxies which serve to hide their true location.

Getting started in the fraud industry is incredibly easy. You can rent a virtual datacenter for $120 which will help you transform a single computer into 1,000 virtual computers with unique device features. You can rent a residential proxy service for $60 to spoof your geo-location and IP address. You can leverage the AWS QA virtual device. With nominal upfront costs of $200 or so, the return on investment is incredible. On the consumer side, a casual fraudster can make $120,000 annually with ease. For B2B research, which is a common target due the high incentive payout, a fraudster can cash in further at $180,000 annually.

Tackling these issues can be intimidating, but it’s important that we as researchers take our power back and get ahead of these fraud innovations. There are both tactical and strategic things you can do to better position yourself and produce higher quality results.

  1. Assumptions are dangerous. It is critical to scrutinize your data closely and work with partners who are transparent and open about the challenges facing our industry.
  2. Fraudsters study our ecosystem closely, and they prey on predictability. Changing our tactics is key to keeping the fraudsters on their toes.
  3. No one is impervious to fraud, but there are some who are more proactive than others. It is important to ask the tough questions and work with partners who will give you a transparent view when things go off track.
  4. Recognize and accept that quality really exists at the participant level. There are good and bad users in every source online.

There is no such thing as perfect and there is certainly no silver bullet, but we can do so much better!

analysis automationautomation trendsbusiness innovation 2022grit reportInnovateMRresearch automationResTech

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The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.

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