List of Experian Ascend ML Builder Customers
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Since 2010, our global team of researchers has been studying Experian Ascend ML Builder customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Experian Ascend ML Builder for Apps Development from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Experian Ascend ML Builder for Apps Development include: OneMain Financial, a United States based Banking and Financial Services organisation with 9100 employees and revenues of $4.28 billion, Atlas Credit Co., Inc., a United States based Banking and Financial Services organisation with 20 employees and revenues of $2.0 million and many others.
Contact us if you need a completed and verified list of companies using Experian Ascend ML Builder, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Experian Ascend ML Builder customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Atlas Credit Co., Inc. | Banking and Financial Services | 20 | $2M | United States | Experian | Experian Ascend ML Builder | Apps Development | 2021 | n/a |
In 2021, Atlas Credit Co., Inc. implemented Experian Ascend ML Builder as part of an Ascend Intelligence Services engagement to develop and deploy a machine-learning credit risk model for consumer lending. The project targeted underwriting and credit decisioning in the finance function in the United States and aligns with Apps Development capabilities for model lifecycle management.
The implementation encompassed core model lifecycle modules including feature engineering, model training and validation, automated scoring pipelines, and production deployment orchestration. Experian Ascend ML Builder was used to build and operationalize scoring workflows that feed directly into lending decision flows.
Operational coverage focused on consumer lending workflows within the finance organization, integrating model scoring outputs into origination and underwriting processes to enable faster credit decisions. The technical architecture emphasized modular model artifacts and automated scoring endpoints to support continuous scoring and reproducible model inference in production.
Governance incorporated model validation, staged rollout controls, and production monitoring to manage model risk and ensure consistent scoring behavior. Atlas Credit Co., Inc. doubled approval rates while reducing credit losses by up to 20 percent during the Ascend engagement, linking Atlas Credit Co., Inc., Experian Ascend ML Builder, Apps Development, and consumer lending business functions.
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OneMain Financial | Banking and Financial Services | 9100 | $4.3B | United States | Experian | Experian Ascend ML Builder | Apps Development | 2019 | n/a |
In 2019 OneMain Financial implemented Experian Ascend ML Builder as part of an Experian Ascend Analytical Sandbox engagement to accelerate core credit risk modeling and reject inferencing, a deployment aligned with Apps Development use for finance and risk teams in the United States. The initiative focused on shortening model development and analysis cycles while improving portfolio insight for consumer lending operations.
The implementation centered on model development and prototype-to-production workflows within the Experian Ascend environment, including data preparation and feature engineering, iterative model training and validation, and automated scoring and inferencing for reject populations. Experian Ascend ML Builder was used to instrument machine learning model build and test cycles, enabling quicker experimentation and repeatable model pipelines consistent with Apps Development capabilities.
Operational coverage targeted OneMain Financials finance and risk functions across the United States, with the effort scoped to credit decisioning and reject inferencing workflows. The deployment leveraged the Ascend Analytical Sandbox for parallel experimentation and reduced time to insight, while model artifacts and scoring outputs were used by risk analysts and portfolio managers to refine credit strategies.
Governance emphasized controlled model iteration and analytics cadence, integrating validation checkpoints and analyst review steps into the development lifecycle. As a result of the Ascend engagement OneMain Financial shortened analysis timelines from as long as 180 days to under two weeks and achieved improved portfolio insight, outcomes that were explicitly reported in the engagement documentation.
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