About Automated Feature Building

Automated Feature Building is a software platform from Pngme designed to change raw financial data into machine learning-ready features automatically. It provides rapid feature generation, industry-specific templates, and automated feature selection so developers can reduce feature engineering time from weeks to hours. This platform facilitates easy access to over 500 predictive features, enabling developers to integrate these features directly into their machine learning models. With its specialized functionalities, users can quickly adapt to various industry requirements, making it a versatile tool in the data science toolkit. Key capabilities: rapid feature generation industry-specific templates automated feature selection 500+ predictive features ML model integration Best for: developers that need efficient feature engineering for machine learning projects.

Automated Feature Building Details

Vendor
Pngme
Year Launched
2018
Location
Floor 4 - Lateral Capital Offices The Address, Muthangari Dr, Nairobi, Kenya
Deployment
cloud
Training Options
documentation
Countries Served
SubSaharan African Countries
Languages
English
Users
Data Scientists, Risk Analysts, Credit Managers, and Developers
Industries Served
Finance
Tags
Feature Engineering, Machine Learning (ML), Fintech, Credit Scoring, Alternative Data, Financial Inclusion, Risk Assessment, Predictive Analytics, API, Emerging Markets, Loan Decisioning, Data Science Automation.

Automated Feature Building's In-App Market Place

Does Automated Feature Building have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

1

Mini Apps

N/A

Pricing Options

Free trial
Free version
Request a quote
Promo Offer

Accepted Payment Currencies

USD ($)

Pros & Cons

  • Built to adhere to multiple data privacy regulations and is SOC 2 Type 1 compliant
  • Provides a lot of features that offer significantly deeper and multi-dimensional risk insights
  • Automates the most time-consuming step in ML
  • Highly effective at generating alternative data features for credit scoring the unbanked or underbanked populations
  • Pricing is not public
  • Institutions need robust processes to understand and validate the features for regulatory and ethical compliance.
  • The quality and volume of the features are dependent on the accessibility and completeness of the data ingested by the Pngme platform.

Automated Feature Building's Support Options

Automated Feature Building's Alternatives