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Amazon Fraud Detector vs IBM Safer Payments comparison

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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
22nd
Average Rating
8.0
Reviews Sentiment
7.8
Number of Reviews
1
Ranking in other categories
No ranking in other categories
IBM Safer Payments
Ranking in Fraud Detection and Prevention
5th
Average Rating
8.0
Reviews Sentiment
7.1
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2026, in the Fraud Detection and Prevention category, the mindshare of Amazon Fraud Detector is 1.8%, up from 1.4% compared to the previous year. The mindshare of IBM Safer Payments is 2.1%, down from 3.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Fraud Detection and Prevention Mindshare Distribution
ProductMindshare (%)
IBM Safer Payments2.1%
Amazon Fraud Detector1.8%
Other96.1%
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.
TA
Business Technology Services at Habib Bank Ltd.
Real-time fraud prevention empowers effective decision-making
The features of IBM Safer Payments that I found most valuable are the "what if" scenarios. I find "what if" scenarios very valuable for my use cases because it's easier to simulate the rules that one would want to set up and see what the outcome would be beforehand; it doesn't take too much rework or effort. I have used the transaction scoring feature of IBM Safer Payments. IBM Safer Payments adaptive machine learning models are still under review for improving the accuracy of fraud detection over time; it's not yet been fully realized because the more data you have, the better it is. Currently, the data is being populated, and it's too early to make definitive conclusions. The ability to process large volumes of transactions in real-time for my organization is very important; that will become even more important once we are doing real-time monitoring and scoring. I have benefited from the comprehensive reporting and visualization tools offered by IBM Safer Payments; they are lovely. These tools have assisted in optimizing my fraud prevention strategies because we are still building on a few things, but once you have a 360 view of the customer's transactional history, it's easier to build in rules for flagging anything that comes out of the ordinary, whether it's in terms of the number of transactions, the volume of the transactions, the location of the transactions, or all of them together. It brings in a lot of visibility into the transactional history and patterns for each customer.

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."
"It's a very fast solution. It can make decisions in 10, 20 or 30 milliseconds. Another feature is that it's a white-box solution. Our clients can see the system's operation, including the rules influencing each decision. Additionally, it's an omnichannel solution capable of utilizing information from various digital channels such as card processing, mobile banking, web banking, APMs, and others."
"This feature has influenced my decision-making processes because IBM is a big player in this market, and we were looking for someone who could handle the number of transactions that we have, support us, and also had a local presence in the market."
 

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 tool should enhance its reporting interface by adding more graphical elements like charts, diagrams, etc. Customers now want more vibrant visuals—bright charts with larger tables, perhaps incorporating animations and 3D elements. Sometimes, it's challenging to explain to customers why the current solution, while good, lacks these kinds of visuals."
"My experience with the initial setup of IBM Safer Payments was complex. It was complex because without pre-built-in templates, you need to build integration with different systems."
 

Pricing and Cost Advice

Information not available
"I rate the solution's pricing a seven out of ten."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
40%
Manufacturing Company
9%
Computer Software Company
7%
Comms Service Provider
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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What needs improvement with IBM Safer Payments?
I haven't looked at IBM Safer Payments in that detail, so I wouldn't be able to answer what areas need to be improved or enhanced. I would suggest improving the integration because given that IBM S...
What is your primary use case for IBM Safer Payments?
My usual use cases for IBM Safer Payments involved real-time fraud monitoring of near real-time, not real-time, near real-time fraud monitoring on debit and credit cards, as well as mobile and inte...
What advice do you have for others considering IBM Safer Payments?
This feature has influenced my decision-making processes because IBM is a big player in this market, and we were looking for someone who could handle the number of transactions that we have, suppor...
 

Also Known As

AWS Cloud9 IDE, Cloud9 IDE
No data available
 

Overview

 

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Borgun
Find out what your peers are saying about ThreatMetrix, BioCatch, NICE and others in Fraud Detection and Prevention. Updated: October 2026.
920,769 professionals have used our research since 2012.