Feedzai Recognized as an ESG Leader

Feedzai is proud to be included in the ESGFinTech100 list from FinTech Global,¹ a prestigious recognition of companies committed to developing ESG solutions for the financial services market. Our patented FairGBM open-source technology stands out among ESG providers (notably in the social pillar of ESG), demonstrating our commitment to the mission of keeping payments fast, secure, and fair. 

Key Findings

• Feedzai has been included in the ESGFinTech100 list, produced by FinTech Global.
• Feedzai was recognized for its FairGBM framework that optimizes machine learning models for both predictive performance and fairer decisioning.
• FairGBM addresses the critical social pillar of the ESG framework (environmental, social, and governance).
• As digital currency methods expand and focus on inclusivity, it will be essential to ensure fraud decisions are fair, transparent, and promote economic fairness.

What Is Feedzai’s FairGBM Framework?

FairGBM is a state-of-the-art, dual ascent learning framework designed to train Gradient Boosted Decision Trees (GBDTs). FairGBM is optimized to improve both predictive performance and decision fairness. It works by incorporating fairness constraints directly into the training process using Lagrange multipliers.2 

Essentially, it helps create high-performing models that significantly reduce bias. Its implementation is considerably faster compared to other methods. 

What ESG Challenge Does Feedzai’s FairGBM Framework Address?

FairGBM directly addresses an important social pillar challenge within the ESG framework: algorithmic bias and fairness in machine learning models. Specifically, the problem is that AI systems, particularly in high-stakes fields like financial services (fraud detection, credit scoring), can unintentionally perpetuate or amplify human biases present in the training data. 

If left unchecked, this can lead to discriminatory outcomes, such as denying services disproportionately to certain protected groups based on factors like age, gender, or race. FairGBM addresses this by enabling models to be optimized for both high performance and fairness simultaneously, thereby promoting responsible and ethical AI.

Feedzia’s FairGBM framework aligns with Feedzai’s TRUST Framework, built on the five key pillars of (Transparent, Robust, Unbiased, Secure, and Tested). The TRUST framework offers a practical roadmap for banks to integrate responsible AI into model development. 

By following the TRUST guidance, FairGBM can automatically identify machine learning models that are not only high-performing but also less biased, thereby eliminating the need for additional model training costs. The models are also transparent and explainable, ensuring they reach responsible decisions for all customers and compliance in the event of regulatory audits.

Balancing Speed and Fairness in the Era of Digital Payments

Ensuring decisions are both trustworthy and secure is critical as human spending habits change. With central banks exploring digital currencies, there’s a growing need for a trusted, inclusive, and universally accepted digital payment method. These designs aim to improve financial inclusion, offering risk-free value and better accessibility for unbanked populations.

However, this digital transformation also escalates fraud threats. In this environment, the core challenge for technology providers is to ensure that real-time fraud detection does not compromise fairness and transparency. Realizing the potential of digital centralized currencies hinges on effectively mitigating the risks of fraud, cyberattacks, and illicit activities. 

At the same time, the speed of digital payments creates new vulnerabilities, requiring a delicate balance of high performance and strong ethical standards, one that moves beyond a simple “either/or” choice.

Feedzai’s FairGBM framework demonstrates that effective fraud detection and strong ethical AI are not mutually exclusive. Both can be achieved simultaneously. The key lies in operationalizing ethical AI through frameworks like TRUST that emphasize transparency, robustness, security, and thorough testing. 

Feedzai is Shaping an ESG Future

By integrating principles such as fairness and accountability into the development process, companies can align ESG principles with innovation, thereby building greater client trust. This commitment ensures that the ongoing battle against fraud maintains both speed and fairness.

FairGBM will be essential to ensuring that risk decisions remain fair, transparent, and secure for all digital currencies and stablecoins. This inclusion in the ESGFinTech100 list is a further demonstration of our commitment to building a safer and fairer digital economy that benefits everyone. 

Additional Resources

• Blog: What Is Digital Currency? Types, Risks, and How to Protect Yourself

• Report: Global State of Scams Report 2025

• Solution Sheet: Secure Digital Currency Transactions

• Solution: RiskOps. Unify All Risk Signals to Stop FinCrime.