Software Alternatives & Reviews

ComplyCube VS Scikit-learn

Compare ComplyCube VS Scikit-learn and see what are their differences

ComplyCube logo ComplyCube

Verify your customers in under 15 seconds anywhere in the world with a cutting-edge SaaS & API platform for Identity Verification and AML/KYC compliance.
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Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • ComplyCube Landing page
    Landing page //
    2022-06-06

ComplyCube offers one of the most advanced and complete platforms in the identity verification and KYC space, helping small, large, and prominent organizations effortlessly meet their AML obligations worldwide.

ComplyCube's mission is to grow trust in the global digital economy by empowering businesses of all sizes to implement slick and resilient verification journeys that increase customer conversions, prevent fraud, and reduce onboarding costs – all without adding unnecessary friction to genuine users.

The all-in-one KYC verification platform is built upon cutting-edge AI, trusted sources, and expert human reviewers, allowing us to offer an extensive and coherent array of checks, including AML & PEP Screening, Document Authentication, Biometric Verification, Multi-bureau Checks, Address Verification, and much more.

Why ComplyCube?

❇️ Trusted by startups and big names alike, including AXA, Lycamobile, and Citi.

❇️ 98% Client onboarding rate, helping you convert more customers and grow your business.

❇️ One-stop solution for everything you need to meet your AML and KYC compliance obligations.

❇️ Global coverage of 220+ countries, 10,000+ document types, and over 3,000 data points from trusted sources and partners worldwide.

❇️ A large set of features and checks, including PEP and Sanctions Screening, Adverse Media Checks, ID Document Verification, Biometric Checks, Liveness Detection, Government Database Checks, Address Verification, and more.

  • Scikit-learn Landing page
    Landing page //
    2022-05-06

ComplyCube features and specs

  • AML & Sanctions Screening: Yes
  • PEP Checks: Yes
  • Negative Media Screening: Yes
  • Watchlist Screening: Yes
  • Biometric Verification: Yes
  • Liveness Checks: Yes
  • Biometric Authentication: Yes
  • Electronic Identity Verification (eIDV): Yes
  • Electronic Know Your Customer (eKYC): Yes
  • ID Document Verification: Yes
  • Proof of Address Checks: Yes
  • Address Verification: Yes
  • Goverement Databases and Bureau Checks: Yes
  • KYC API: Yes
  • AML API: Yes
  • Age Verification: Yes
  • NFC Scanning: Yes

Scikit-learn features and specs

No features have been listed yet.

ComplyCube videos

ComplyCube Mobile SDK Demo - Easy and Secure Identity Verification

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

Category Popularity

0-100% (relative to ComplyCube and Scikit-learn)
Security & Privacy
100 100%
0% 0
Data Science And Machine Learning
Identity Verification And Protection
Data Science Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare ComplyCube and Scikit-learn

ComplyCube Reviews

  1. Perfect experience so far

    ComplyCube makes it easy to verify identities and stay compliant with regulations. It helps businesses onboard customers smoothly while following the rules. With simple tools to check identities and manage risks, ComplyCube is a great choice for any company needing to keep things legal and straightforward.

    👍 Pros:    User-friendly interface:|Customization|Efficiency
    👎 Cons:    Cost|Customer support
  2. Really impressive through and through!

    This was one of the most pleasant SaaS integrations I've ever experienced. Simple documentation, quick engagement from Sales all the way to Support. We wanted to launch our product in two countries, then scale to 16 within 4 months. ComplyCube was extremely supportive and provided us with KYC strategy and a platform that's flexible and useful for our business needs. Very pleased!

    🏁 Competitors: SwiftDil, Onfido, MetaMap, Yoti, GetID, Sumsub, Passbase, Ondato
    👍 Pros:    Easy to use|Simple yet powerful and efficient tool|Excellent support|Impressive ui|Easy integration|Comprehensive data
    👎 Cons:    Nothing that i can think of.
  3. Amazing identity verification platform and team!

    We've tried several SaaS platforms in the identity verification space, but we were left frustrated with complicated integration steps and not particularly unhelpful support and sales.

    ComplyCube (and shoutout to Vic and Lucas) were brilliant from the get-go! The API documentation is rich and easy to follow. Integrations took us a couple of hours and our clients are breezing through the onboarding process keep it up guys!

    🏁 Competitors: SwiftDil, Shufti Pro, Veriff, Passbase, Onfido, Yoti, Sumsub
    👍 Pros:    Excellent customer service|Super fast|Cost-effective plans|Global coverage|Iso-certified solution|Easy integration
    👎 Cons:    Large-volume pricing is not public, and we had to speak to the sales team to get a quote

Discover the Top 5 Identity Verification Providers in 2023
Onfido and ComplyCube stand out by having one of the broadest range of features on the market, including but not limited to sanctions & PEP screening, document verification, biometric authentication, device intelligence, and more. However, it is worth noting that some of the advanced features offered by Onfido are exclusively available to enterprise customers, whereas their...

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

Social recommendations and mentions

Based on our record, Scikit-learn seems to be more popular. It has been mentiond 27 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

ComplyCube mentions (0)

We have not tracked any mentions of ComplyCube yet. Tracking of ComplyCube recommendations started around Jun 2022.

Scikit-learn mentions (27)

  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 11 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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What are some alternatives?

When comparing ComplyCube and Scikit-learn, you can also consider the following products

Sumsub - One verification platform to secure the whole user journey

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Onfido - Onfido is the data-driven platform for intelligent background checking.

OpenCV - OpenCV is the world's biggest computer vision library

Veriff - Smart and scalable identity verification.

NumPy - NumPy is the fundamental package for scientific computing with Python