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Analytics Data | Quantitative Analytics

StarMine Combined Credit Risk Model

Quantitative analytics dataset for StarMine combined credit risk signals and model-driven risk assessment.

Key facts for StarMine Combined Credit Risk Model

Coverage metric

Geography:
North America, Asia / Pacific, EMEA, Latin America and the Caribbean
History:
From 1998
Coverage count:
Legal entities - 57800 Public companies
Asset Class
Ordinary Shares, Equities

Delivery metadata

Data Frequency
Daily
Language
English
Delivery methods:
Excel, Deployed/Onsite Servers, API, Web Service, Cloud, Desktop, FTP, Bulk, Snowflake, Website
Data formats:
PDF, GZIP, XML, JSON, CSV, SQL, Text, Python, HTML, Bitmap, MPEG, User Interface, PCAP
Minimum service frequency
Daily

Overview of StarMine Combined Credit Risk Model

Description of the dataset

· LSEG provides company-level credit risk analytics through the StarMine Combined Credit Risk Model. We deliver one-year default probability, overall credit risk scores and comparative ranks to support issuer monitoring and credit screening. · Our framework blends market-based structural indicators, fundamentals-driven SmartRatios and text-based signals. LSEG exposes component model outputs so clients can understand the drivers behind each credit risk assessment. · We cover global publicly listed companies to support early-warning workflows, portfolio surveillance and comparative credit analysis. LSEG structures these risk measures for use by investors, risk managers and analysts seeking consistent company-level default risk insights.

Accessing the dataset

This dataset can be used by the following products. Talk to us to learn more about different packages and offerings.

Starmine Direct FTP

StarMine Direct FTP delivers LSEG StarMine's proprietary quantitative analytics and predictive models via secure File Transfer Protocol (FTP). The service provides transparent, research-driven equity and credit-risk analytics, including analyst revisions, valuation, momentum, earnings quality, smart money, M&A and sentiment models, to support quantitative investing, stock selection, portfolio construction and risk management.