IT Central Station is now PeerSpot: Here's why

Amazon Fraud Detector OverviewUNIXBusinessApplication

Amazon Fraud Detector is #11 ranked solution in Fraud Detection and Prevention software. PeerSpot users give Amazon Fraud Detector an average rating of 8 out of 10. Amazon Fraud Detector is most commonly compared to Riskified: Amazon Fraud Detector vs Riskified. Amazon Fraud Detector is popular among the large enterprise segment, accounting for 61% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 36% of all views.
Buyer's Guide

Download the Fraud Detection and Prevention Buyer's Guide including reviews and more. Updated: June 2022

What is Amazon Fraud Detector?

Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities such as online payment fraud and the creation of fake accounts. Globally each year, tens of billions of dollars are lost to online fraud.

Amazon Fraud Detector was previously known as AWS Cloud9 IDE, Cloud9 IDE.

Amazon Fraud Detector Customers
Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Amazon Fraud Detector Video

Amazon Fraud Detector Reviews

Filter by:
Filter Reviews
Filter Unavailable
Company Size
Filter Unavailable
Job Level
Filter Unavailable
Filter Unavailable
Filter Unavailable
Order by:
  • Date
  • Highest Rating
  • Lowest Rating
  • Review Length
Showingreviews based on the current filters. Reset all filters
Graduate Analytics Consultant at a tech services company with 51-200 employees
Real User
Top 20
Quickly and reliably identifies potentially fraudulent activity
Pros and Cons
    • "There was also a problem with latency. In fraud detection, everything needs to be happening in real-time, but some of the algorithms ran for three to four minutes, which is not a viable option."

    What is our primary use case?

    We used it for an Academy project and we also used it for a credit card transaction fraud detection project. The purpose of the project was to denote anomalies or customer records that were different from usual. The reason that we used this solution was that it was the only end-to-end framework available on the market at that time. If I were to build my own solution on AWS, I would have had to bring in all the components, but AWS Fraud Detector has the capability to blend in not just the data streaming part, but also the multi-building part, ultimately chiming in with Amazon QuickSight for the visualization and Amazon SNS for notification.

    How has it helped my organization?

    In machine learning, we may measure a metric, something called recall — the other metric is false-positive. A recall refers to the total amount of fraud — how much were we able to recall (capture). Overall, we got some really good results. We got roughly a 77% recall, which meant 77% of the total fraud was actually picked up by Amazon Fraud Detector. We could pick a lot of fraud at the same time, but you're false positive, so the number of customers who may not be fraudulent, who get tagged as fraudulent also increased. We were able to reduce the false positives to roughly 20%, which is an extremely small number compared to other solutions or other models in place.

    What is most valuable?

    In terms of infrastructure — seamless integration was the most valuable feature. Everything was really plug-and-play style. I could see what I had to do, and I could customize it according to my needs. The second valuable feature involved the machine learning part of things where I could experiment with different algorithms in Amazon — Amazon SageMaker and experiment with different algorithms. 

    What needs improvement?

    The problem I was facing, from a machine learning perspective, it only had a supervised learning capability. You would have to provide your data live, but in fraud, the pattern of the fraudsters keeps changing and it's impossible to provide data labels. That's where the user unsupervised learning comes in handy — you don't have to tell them, "okay, this is fraud and this is not fraud."  If unsupervised learning was also incorporated with Amazon SageMaker, that would be really cool. I am talking about anomaly detection algorithms, like isolation, forest, or anything on the neural network side for anomaly detection, including autoencoders. These are some things which companies would really like to use. There was also a problem with latency. In fraud detection, everything needs to be happening in real-time, but some of the algorithms ran for three to four minutes, which is not a viable option.
    Buyer's Guide
    Fraud Detection and Prevention
    June 2022
    Find out what your peers are saying about Amazon, Broadcom, Riskified and others in Fraud Detection and Prevention. Updated: June 2022.
    607,127 professionals have used our research since 2012.

    For how long have I used the solution?

    I used this solution for six months.

    What do I think about the stability of the solution?

    It is stable. I didn't face any of the issues with respect to crashing or it being nonresponsive, or the server being down. 

    What do I think about the scalability of the solution?

    I would say it is quite scalable. The services are built on top of each other, so you could seamlessly bring in any of the services and get them into play — it is highly scalable.

    How are customer service and support?

    The technical support was pretty responsive. Some of the things required access to Amazon, instances like a higher compute capacity and all that, but they went on doors and they were responsible in real-time. For some of the things which required greater access, they took not more than one day.

    How was the initial setup?

    The whole process was straightforward, actually. Amazon has really good documentation. I have to give credit to them on that. It was plug-and-play, and we knew we had access to all the codes and the repositories on GitHub — it was seamless.  The entire setup just took a couple of days.

    What other advice do I have?

    Make your integrations right and test them properly because it is still a new product. Things could break depending on their use case. If you are able to ensure that everything is one hundred percent connected and know that nothing is going to break — that would be good. On a scale from one to ten, I would give Amazon Fraud Detector a rating of eight.
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    Buyer's Guide
    Download our free Fraud Detection and Prevention Report and find out what your peers are saying about Amazon, Broadcom, Riskified, and more!
    Updated: June 2022
    Buyer's Guide
    Download our free Fraud Detection and Prevention Report and find out what your peers are saying about Amazon, Broadcom, Riskified, and more!