Strengthening Risk Intelligence with Trusted News Data

Your customers—financial firms, compliance officers, and risk analysts—trust your platform to help them navigate financial regulations, ESG risks, and geopolitical threats. But if misinformation, biased sources, or AI-generated content slip through, they could be making critical decisions based on faulty intelligence.

Are you equipping them with credible insights—or exposing them to costly blind spots?

The compliance and business risks of unverified data

If you’re a product manager in charge of developing advanced risk intelligence solutions, you must ensure data authenticity for:

• Proper compliance – If your risk intelligence platform services organizations that must comply with strict AML and KYC regulations, providing inaccurate or inadequate data could lead to non-compliance, severe penalties, and hefty fines.

• Accurate risk assessment – Training models on flawed data may result in ineffective risk mitigation strategies.

How Data Credibility Impacts Risk Scoring and Decision-Making

Without trustworthy data, the insights your product provides can become unreliable, leading to serious consequences:

• Eroded customer trust and revenue – Users lose confidence in your risk assessments and turn to competitors.
• Damage to brand credibility – Inconsistent or inaccurate insights harm your reputation and customer retention.
• Frustration across teams – Product, data, and leadership teams struggle with misaligned insights and inefficiencies.
• Weakened competitive position – Competitors with broader coverage and more dependable data deliver stronger risk intelligence.

The Impact on Risk Scoring

Many risk intelligence platforms generate risk scores to assess business threats. However, if scores rely on undependable data, they can:

• Reduce risk score accuracy– False positives (flagging low-risk entities) and false negatives (missing real threats) lead to costly mistakes.
• Undermine decision making – Poor insights result in financial, legal, and reputational damage.

The Impact on Supply Chain Risk

A large electronics manufacturer uses risk intelligence software to monitor supply chain threats, including:

• Supplier financial stability
• Political events in key regions
• Supply and demand for critical components

If the platform misreads early signals of a semiconductor shortage, the manufacturer may fail to secure enough chips. When shortages hit, production stalls, leading to millions in lost revenue.

The Impact on Regulatory Compliance

Organizations rely on risk intelligence to detect suspicious transactions. Unverified data can create false positives, wasting compliance teams’ time, or false negatives, exposing the company to fines and reputational damage.

Improve risk score accuracy with AI-driven misinformation filtering

Ensuring data reliability is critical for accurate risk intelligence—but AI-generated misinformation is making this increasingly difficult.

Large language models (LLMs) like ChatGPT are used to quickly generate and disseminate misleading content that distorts risk analysis. Since unverified claims spread rapidly, fake news about corrupt investments on low-quality sites can sway market sentiment within hours, directly impacting risk assessments.

If a risk intelligence platform ingests this data, risk scores become unreliable. Integrating a news API with misinformation filtering helps prevent false positives, ensuring assessments are based on credible sources and real threats. You can use the fake news and satire news tags on Webz.io’s News API to weed out news sources that are not suitable.

Accelerate product development with structured news data feeds

Filtering out false information is only part of the equation. Risk intelligence platforms also need a scalable, structured approach to sourcing and managing validated data.

Companies developing risk intelligence platforms typically put product teams or data engineering teams in charge of finding, extracting, and cleaning reliable sources of verified data, including news data — which takes a great deal of time, especially if done manually.

Most teams use machine learning (ML) to speed up data collection and cleaning. However, even with ML, these processes still involve human intervention.

Your data management teams need a constant stream of relevant, high-quality news sources to make sure your users have enough data to track everything. You and your team are responsible for tracking changes to existing sources, verifying data accuracy, and tagging satire or misinformation campaigns correctly.

Leveraging structured news data feeds with reliability indicators for each article and source allows product teams to concentrate on enhancing platform features. This approach reduces false positives by ensuring risk models are built on accurate, trustworthy data, empowering data engineers to develop more efficient, precise models without interference from irrelevant or flawed information.

Enhance due diligence and ESG risk management with credible data sources

Beyond risk intelligence, structured and credible news data also plays a critical role in due diligence and ESG risk management.

Financial sector organizations in a wide range of industries  often need to manage risks related to due diligence and environmental, social, and governance (ESG).

Many consumer goods businesses source products from suppliers worldwide. A consumer goods business, and every other company, needs to ensure that companies in their supply chains follow ethical labor practices, have a minimal environmental impact, and are financially stable. Analyzing due diligence and ESG data is critical to evaluating these types of risks.

Assessing and managing due diligence and ESG risks requires verified data from trustworthy sources like corporate newsrooms, non-governmental organizations (NGOs), the United Nations (UN), and local government sources. Accurate, reliable data from these sources helps prevent false positives in risk assessments, ensuring that strategic choices are based on the most credible and relevant information available.

Data from these sources enhance risk management for several reasons:

• Credibility and reliability – NGOs, UN, and government sources typically conduct extensive research on a wide range of issues. These sources often possess in-depth knowledge and hands-on experience on specific topics, providing critical insights and reliable data not available elsewhere.

• Regulatory compliance – Many ESG regulations and frameworks require data from recognized public institutions. These sources typically conduct extensive research using established standards and methodologies. Public institutions typically provide trusted data companies can use to ensure regulatory compliance.

• Comprehensive coverage – NGOs, UN, and government sources provide broad data coverage for many areas of ESG and due diligence. You can obtain information about:
  • Environmental issues, such as deforestation, water usage, and waste generation
  • Social concerns like human rights, working conditions, health and safety
  • Governance matters such as bribery and corruption, board structure, and ethical standards

You can use the Webz.io News API to gather relevant information about due diligence and ESG from sources across the open web. We also offer additional APIs that you can use to track ESG-related mentions.

Help your customers avoid risk with trusted news data 

Every organization needs effective risk intelligence solutions to navigate constantly changing global markets without increasing business and legal risks. Trusted news data ensures that these solutions provide a 360-degree view of the potential risks financial sector companies face. And with the full picture they can make informed choices that meet compliance requirements, avoid costly penalties, and boost revenue.

Interested in learning more? Check out our whitepaper about the top challenges of monitoring regulatory risk.