Unparalleled accuracy
into risk exposure

When it comes to biodiversity, deforestation, human rights, labor standards, corruption, and environmental issues,
RepRisk’s unique perspective serves as a reality check for how companies conduct their business around the world.

This perspective, together with a transparent, proven methodology at the core and daily updates, ensures that our clients have consistent, timely, and actionable insights at their fingertips for peace of mind and performance.

Harnessing the Power of advanced AI with Humans in the Lead

As pioneers at the forefront of AI evolution, we embrace and seamlessly integrate developments to bring you maximum value.

Expert Human Intelligence
(HI)

Our team of 150+ expert research
analysts analyzes and curates each risk
incident using our transparent, proven
methodology — delivering quality, depth,
consistency, and actionable insights.

Supercharging quality
HI × AI

Bringing you the most trusted risk insights in the industry.

Advanced Artificial Intelligence
(AI)

Since 2007, AI has powered the speed and scale of
our risk data. With a pioneer mindset, our team of
60+ engineers continuously evolves our models
using the latest AI technologies — from
open-source to proprietary tools.

Expert Human Intelligence (HI)

Our team of 150+ expert research analysts analyzes and curates each riskincident using our transparent, proven methodology — delivering quality, depth, consistency, and actionable insights.

Advanced Artificial Intelligence (AI)

Since 2007, AI has powered the speed and scale of our risk data. With a pioneer mindset, our team of 60+ engineers continuously evolves our models using the latest AI technologies — from open-source to proprietary tools.

Supercharging quality
HI × AI

Bringing you the most trusted risk insights in the industry.

A proven and transparent research process
Helps ensure consistency over time by translating
big data into curated research and metrics.

Screening and identification

RepRisk screens, on a daily basis, over 150,000 public sources and stakeholders in 23 languages to systematically identify any company or project associated with a reputational, business conduct risk incident, per RepRisk’s research scope.

2,500,000+ documents are aggregated through advanced text and metadata extraction from unstructured content and undergo multilingual de-duplication and clustering processes, reducing incoming documents to approximately 150,000 daily.

Analysis and curation

150+ analysts review and approve the results of the screening process of automated tagging, relevancy scoring, and news analytics. Each risk incident is analyzed according to the following three parameters:

  1. Severity (harshness) of the risk incident or criticism.
  2. Reach of the information source (influence based on readership/circulation as well as by its importance in a specific country), based on RepRisk’s rating.
  3. Novelty (newness) of the issues addressed for the company and/or project, i.e. whether it is the first time a company/project is exposed to a specific ESG Issue in a certain location.

Quality assurance

Before a risk incident is published in RepRisk's dataset, it undergoes a quality assurance check and approval performed by a Senior RepRisk Analyst to ensure that the overall analysis process is in line with RepRisk’s trusted, proven, and transparent methodology.

Quantification

The final step in the process, the quantification of the risk, is done through data science. There are proprietary standard and customized risk metrics.

The RepRisk Index (RRI) dynamically captures and quantifies reputational and business conduct risk exposure related. The RepRisk Rating (RRR), a letter rating (AAA to D), facilitates benchmarking and integration of ESG, reputational, and business conduct risks. The UN Global Compact Violator Flag identifies companies that have a high risk or potential risk of violating one or more of the ten UNGC Principles.

Uniquely positioned to embrace and seamlessly
Integrate developments to bring you maximum value.

1. Training data

Two decades of highly accurate, domain-specific, human-labeled data.

2. Advanced machine learning

Trained and refined machine learning (ML) models filter out irrelevant data i.e., “the noise.

3. Human intelligence

Human analysts review, analyze, and approve the results of the screening process and work together with generative text models to develop the highest quality risk incident summaries as fast as possible.

4. Feedback loop

The ML models learn from the analysts and accuracy improves through a feedback loop.

Harnessing game-changing advancements is in our DNA
From generally available open-source and proprietary AI models, to innovating risk data processing and delivery.

Big data 2,500,000+ documents screened daily from 150,000+ sources in 23 languages Documents scraped from online sources and fed to machine learning (ML) applications Text classification ML reducer Named entity recognition Deduplication ML applications predict relevant and unique ESG risk incidents Irrelevant results discarded and predictions fed to the multilingual queue Results sent to the ML reducer Multilingual queue Human analysts Approved Documents sorted in priority order A team of 150+ human analysts: Two analysts review Confirm and correct ML predictions Assess severity, reach, and novelty Write risk incident summaries along with generative text models ESG Risk Platform, ESG Risk Monitor, or via RepRisk Data Feed Results are published to client-facing solutions
Big data 2,500,000+ documents screened dailyfrom 150,000+ sources in 23 languages ESG Risk Platform, ESGRisk Monitor, or viaRepRisk Data Feed
“We have set up our complete universe of portfolio companies to be monitored by RepRisk. To us, this is a great step forward in implementing ESG considerations in private markets, as we are able to monitor both the ESG issues of our portfolio companies as well as how the respective GP deals with these issues.”
LGT Capital Partners

Environment

Environmental Footprint

  • Climate change, GHG emissions, and global pollution
  • Local pollution
  • Impacts on ecosystems and biodiversity
  • Overuse and wasting of resources
  • Waste issues
  • Animal mistreatment

Social

Community Relations

  • Human rights abuses and corporate complicity
  • Impacts on communities
  • Local participation issues
  • Social discrimination

Employee Relations

  • Forced labor
  • Child labor
  • Freedom of association and collective bargaining
  • Discrimination in employment
  • Occupational health and safety issues
  • Poor employment conditions

Cross-cutting Issues

  • Controversial products and services
  • Products (health and environmental issues)
  • Supply chain issues
  • Violation of national legislation
  • Violation of international standards

Research coverage in 23 major business languages
Means RepRisk identifies risks at the local level –
so you can know early, be sure, and act faster.

RepRisk language coverage coming soon

+95% of the world’s GDP (2021) is covered by the 23 languages in which RepRisk conducts its research, based on the official language indicated per country.

Official language(s) covered by RepRisk RepRisk language coverage coming soon

+95% of the world’s GDP (2021) is covered by the 23 languages in which RepRisk conducts its research, based on the official language indicated per country.

A dataset unique in the industry dating back to 2007
With research and metrics updated daily, systematically covering public & private companies, emerging & frontier markets — delivering early risk signals at speed.

Research inputs Research outputs The world's most respected DaaS company for reputational risks and responsible business conduct Human intelligence Advanced machine learning Updated daily 150,000+ public sources and stakeholders screened daily 23 major business languages covered 150+ highly-trained analysts 298,128 public and private companies 93,463 infrastructure projects All sectors and industries All countries including emerging and frontier markets 108 risk factors mapped to the UNGC, SASB, and the SDGs 300,000+ risk assessments Two decades of data history from January 2007 8 million documents labeled 2,500,000+ documents screened daily
Input
Output

Two decades

of data history from January 2007

300,000+

risk assessments

8 million

documents labeled

108 risk factors

mapped to the UNGC, SASB, and the SDGs

2,500,000+

documents screened daily

All countries

including emerging and frontier markets

150,000+

public sources and stakeholders screened daily

All sectors

and industries

23

major business languages covered

93,463

infrastructure projects

150+

highly-trained analysts

298,128

public and private companies
Our methodology is trusted, proven, and transparent.
Learn how it works