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Darwin vs FICO Decision Management comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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

Darwin
Ranking in Data Science Platforms
25th
Average Rating
8.0
Reviews Sentiment
6.7
Number of Reviews
8
Ranking in other categories
No ranking in other categories
FICO Decision Management
Ranking in Data Science Platforms
27th
Average Rating
9.0
Reviews Sentiment
6.7
Number of Reviews
4
Ranking in other categories
Decision Management Tools (2nd)
 

Mindshare comparison

As of March 2026, in the Data Science Platforms category, the mindshare of Darwin is 1.5%, up from 0.3% compared to the previous year. The mindshare of FICO Decision Management is 1.4%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms Mindshare Distribution
ProductMindshare (%)
Darwin1.5%
FICO Decision Management1.4%
Other97.1%
Data Science Platforms
 

Featured Reviews

AC
Founder at Helio Summit
Empowers SMEs to build solutions and interface them with the existing business systems, products and workflows.
There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do. Because it's so much better than traditional methods, we don't get a ton of complaints of, "Oh, we wish we could do that." Most people are happy to see that they can build models that quickly, and that it can be done by the people who actually understand the problem, i.e. SMEs, rather than having to rely on data scientists. There's a small learning curve, but it's shorter for an SME in a given industry to learn Darwin than it takes for data scientists to learn industry-specific problems. The industry I work in deals with tons and tons of data and a lot of it lends itself to Darwin-created solutions. Initially, there were some limitations around the size of the datasets, the number of rows and number of columns. That was probably the biggest challenge. But we've seen the Darwin product, over time, slowly remove those limitations. We're happy with the progress they've made.
it_user147981 - PeerSpot reviewer
Project Manager at a financial services firm with 501-1,000 employees
I would recommend buying this product for loan origination purposes
FICO OM is very flexible in terms of development, with rapid application development options Streamlined loan origination processes. Credit products. Two years. No. No. Below average. Straightforward. Flexible. Yes, we did. I would recommend buying this product for loan origination…

Quotes from Members

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

Pros

"We have managed to reduce the percentage of high-risk clients from 8.9 percent to 5 percent, which is very significant in the overall quality of our clients and very good news for everyone, especially our investors."
"Darwin is the perfect tool to solve this issue; what the machine-learning industry needs at this point to expand exponentially in the oil and gas market."
"The solution helps with the automatic assessment of the quality of datasets, such as missing data points or incorrect data types."
"Darwin is really useful for people who don't necessarily do a lot of data science."
"Even people who are not fully technical can use it with a little guidance or something."
"In terms of streamlining a lot of the low-level data science work, it does a few things there."
"Our main goal is to transform data into knowledge and Darwin is definitely helping us to do that faster."
"The thing that I find most valuable is the ability to clean the data."
"FICO OM is very flexible in terms of development, with rapid application development options."
 

Cons

"Something they are working on, which is great, is to have an API that can access data directly from the source. Currently, we have to create a specific dataset for each model."
"An area where Darwin might be a little weak is its automatic assessment of the quality of datasets. The first results it produces in this area are good, but in our experience, we have found that extra analysis is needed to produce an extra-clean set of data."
"In the beginning, when we started to see how Darwin works, we thought that maybe, from raw, dirty data, we could generate a model really fast, but that's not true."
"Darwin is stable, but it just doesn't provide the functionality that an analyst would need."
"If you give a lot of data to Darwin, sometimes it can hang."
"There's always room for improvement in the UI and continuing to evolve it to do everything that the rest of AI can do."
"The license cost is not cheap, especially not for markets like Mexico."
"Our main data repository is on AWS. The trouble we are having is that we have to download the data from our repository to bring it into Darwin."
"Customer service is below average."
 

Pricing and Cost Advice

"In just six months, we calculated six million pesos that we have prevented in revenue from going away with another customer because of this solution. Thanks to Darwin, we didn't lose those six million pesos."
"I believe our cost is $1,000 per month."
"The license cost is not cheap, especially not for markets like Mexico. But sometimes, you do have to make these leap of faith for some tools to see if they can get you the disruption that you are aiming for. The investment has paid off for us very well."
"As far as I understand, my company is not paying anything to use the product."
Information not available
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
32%
Real Estate/Law Firm
7%
Manufacturing Company
7%
Outsourcing Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Large Enterprise2
No data available
 

Overview

 

Sample Customers

Hunt Oil, Hitachi High-Tech Solutions
Aiful, Raiffeisen Bank International AG
Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms. Updated: March 2026.
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