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ACI Fraud Management vs Amazon Fraud Detector 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

ACI Fraud Management
Ranking in Fraud Detection and Prevention
24th
Average Rating
0.0
Reviews Sentiment
7.5
Number of Reviews
1
Ranking in other categories
Anti-Money Laundering (AML) (11th)
Amazon Fraud Detector
Ranking in Fraud Detection and Prevention
23rd
Average Rating
8.0
Reviews Sentiment
7.8
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2026, in the Fraud Detection and Prevention category, the mindshare of ACI Fraud Management is 1.4%, up from 1.4% compared to the previous year. The mindshare of Amazon Fraud Detector is 1.6%, up from 0.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Fraud Detection and Prevention Mindshare Distribution
ProductMindshare (%)
Amazon Fraud Detector1.6%
ACI Fraud Management1.4%
Other97.0%
Fraud Detection and Prevention
 

Featured Reviews

Austin Aghedo - PeerSpot reviewer
Develop engineer at Interswitch
Automatically detect payment fraud with diverse rules and machine learning capabilities
There is room for improvement in the acceleration of its artificial intelligence capabilities. Artificial intelligence could enhance fraud detection without the need to manually set rules. Greater focus should be on machine learning and artificial intelligence capabilities, allowing the system to learn through existing rules and train itself to develop self-detection capabilities. Currently, the machine learning feature requires extensive usage before activation, which hinders its effectiveness.
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.

Quotes from Members

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

Pros

"The primary value of ACI Fraud Management lies in its capability for detection and prevention of card fraud around payments."
"The primary value of ACI Fraud Management lies in its capability for detection and prevention of card fraud around payments, with diverse rules that automatically decline suspicious transactions and real-time detection that adds another layer of security while its API integration capabilities facilitate use across multiple channels, including mobile transactions, enhancing its versatility."
"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."
 

Cons

"There is room for improvement in the acceleration of its artificial intelligence capabilities."
"There is room for improvement in the acceleration of its artificial intelligence capabilities."
"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."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
28%
Comms Service Provider
13%
Computer Software Company
9%
Construction Company
8%
No data available
 

Company Size

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

Questions from the Community

What needs improvement with ACI Fraud Management?
There is room for improvement in the acceleration of its artificial intelligence capabilities. Artificial intelligence could enhance fraud detection without the need to manually set rules. Greater ...
What is your primary use case for ACI Fraud Management?
Our primary use case for ACI Fraud Management is the detection and prevention of payment fraud. We work with a company that is a partner with ACI, and we use this solution integrated with a switchi...
What advice do you have for others considering ACI Fraud Management?
I advise those interested in ACI Fraud Management to try it out, especially for its seamless integration with current payment technology. It is suitable for medium and large enterprises, while smal...
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Also Known As

No data available
AWS Cloud9 IDE, Cloud9 IDE
 

Overview

 

Sample Customers

Information Not Available
Expedia, Intuit, Royal Dutch Shell, Brooks Brothers
Find out what your peers are saying about ThreatMetrix, NICE, BioCatch and others in Fraud Detection and Prevention. Updated: March 2026.
885,667 professionals have used our research since 2012.