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Amazon Fraud Detector vs Broadcom Payment Security comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Amazon Fraud Detector
Ranking in Fraud Detection and Prevention
24th
Average Rating
8.0
Reviews Sentiment
7.8
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Broadcom Payment Security
Ranking in Fraud Detection and Prevention
20th
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
16
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Fraud Detection and Prevention category, the mindshare of Amazon Fraud Detector is 1.6%, up from 1.0% compared to the previous year. The mindshare of Broadcom Payment Security is 1.7%, up from 0.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Fraud Detection and Prevention Mindshare Distribution
ProductMindshare (%)
Broadcom Payment Security1.7%
Amazon Fraud Detector1.6%
Other96.7%
Fraud Detection and Prevention
 

Featured Reviews

reviewer1461372 - PeerSpot reviewer
Graduate Analytics Consultant at a tech services company with 51-200 employees
Quickly and reliably identifies potentially fraudulent activity
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.
JP
Consultant Fraud Risk Management at a financial services firm with 501-1,000 employees
We are using the product for 3D Secure authentication and fraud prevention
For CA Risk Analytics, we would like to have some statistics available, to do some counting on the number of transactions for example. Also, to have the ability not only for 3D Secure, but accross all online channels. Online banking and App. Because then you would have three online channels. You would have the same device data, so you can combine it. So then you would have an online banking platform, an app, and 3D Secure all from one supplier. This supplier would support all of our authentication methods across those three channels. That's our ultimate goal to have one supplier to support all three online channels.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"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."
"Helped reduce 3-D Secure losses to one of the lowest in the industry while having minimal customer impact."
"They are excellent."
"I think for us, the value that we get out of CA is their effective scheme diagnostics."
"We see a high value in that, with all the fraud rules that we built, we have a very good false positive ratio because of the big data that CA has."
"This is a good product, which is easy to deploy and has lot of user friendly features."
"For a bank, we've seen transactions move to e-commerce. We needed a solution that would protect the bank and protect the bank's cardholders, and that's what this solution gives us."
"I think stability-wise, we've not really had any issues in terms of stability."
"In terms of the fraud that we see on the card site, card not present fraud, the person gives contribution to what the total fraud has increased substantially."
 

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."
"The deployment process needs to be updated to ensure the base code does not involve details of other clients."
"We are still unable to implement OTP through email using this solution."
"I think improvements for us, it's making it simple enough that anybody can understand how it works."
"I had wish it would be this one, this authentication for fingerprint and face would be promising."
"Unifying operational changes around highlighting. If you highlight one item, it will highlight the one card that's affected across the board."
"In the first two years, there were several issues with stability."
"This is the one area where there's room for improvement. I think that is the one area where improvements can be made in terms of speed of response, in terms of quality of response, and in terms of more so a proactive problem monitoring."
"Sometimes, there is a bit of language issue of understanding problems."
 

Pricing and Cost Advice

Information not available
"Utilize the transaction pricing model versus the active cards because the ability to monitor active cards hasn’t been good."
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Top Industries

By visitors reading reviews
No data available
Construction Company
18%
Outsourcing Company
13%
Financial Services Firm
12%
Comms Service Provider
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise3
Large Enterprise12
 

Also Known As

AWS Cloud9 IDE, Cloud9 IDE
CA Risk Analytics, CA Transaction Manager, CA Payment Security Suite
 

Overview

 

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Eurocard
Find out what your peers are saying about NICE, ThreatMetrix, BioCatch and others in Fraud Detection and Prevention. Updated: July 2026.
908,800 professionals have used our research since 2012.