Boost the ESG Social Pillar with Responsible AI

Feedzai plays a vital role in the fight against fraud and financial crime. But that’s not all. We also deliver innovative solutions that empower banks to improve their social responsibility obligations. 

Here’s how our industry-recognized Responsible AI solutions enhance banks’ social commitments.

How Does ESG Apply to Banks?

ESG principles guide businesses to operate ethically, sustainably, and in accordance with human rights. This could mean reducing a company’s carbon footprint, avoiding unethical labor practices, or preventing discrimination.

ESG metrics not only focus on cross-sector issues like the transition to reduced carbon emissions. It also explores industry-specific topics like socially responsible lending, securing data privacy, and fair financial decisions for customers.

The social pillar of ESG aligns with Responsible AI by promoting fair and unbiased decisions in banks’ AI systems. By adopting Responsible AI, banks can proactively meet regulatory standards and show their commitment to social responsibility. These may include reducing the likelihood of bias, discrimination, and unfairness in their operations. This ultimately contributes to a more inclusive and equitable financial ecosystem.

ESG and Responsible AI Pressures Build for Banks

As banks pursue their mission with the increasing involvement of AI, they face new realities brought on by recent regulatory shifts and rapid-paced technological advancements.

A New Era of ESG and AI Regulations

The ESG landscape is evolving rapidly. Nearly 30 countries are implementing or will enforce mandatory ESG regulations. 

This surge in ESG regulations underscores the need for financial institutions to adhere to social guidelines, promoting transparency and anti-discrimination practices. It also coincides with a push for greater AI regulations for similar reasons.

First, the European Union’s AI Act imposes strict conditions on the development and use of AI. The measure aims to ensure safety, transparency, origin, environmental friendliness, and non-discrimination. Financial institutions, particularly in credit scoring models, face explicit scrutiny, emphasizing the urgency of responsible AI adoption.

Meanwhile, the US has taken steps recently to regulate AI. President Joe Biden issued a historical executive order requiring artificial intelligence safety and security assessments. The order will focus on consumer protection, bias mitigation, and studying AI’s societal impact.

Even technology firms that produce AI are calling for greater regulation. For example, ChatGPT’s creator, OpenAI, supports creating an oversight agency as part of the EU’s AI Act. The AI Act’s design ensures that AI systems used in the EU are non-discriminatory.

Adapting to the GenAI Challenge in Fraud Prevention

While GenAI promises enhanced customer engagement through advanced chatbots, it also opens doors to sophisticated fraud threats. This includes refined email phishing schemes and synthetic identity creation.

The emergence of tools like FraudGPT, derived from ChatGPT, raises the stakes. These programs can generate convincing fraudulent communications, making traditional detection methods less effective. Similarly, applications like LangChain leverage GenAI for hyper-personalization, potentially aiding fraudsters in tailoring their attacks using harvested data.

For fraud and financial crime prevention teams, this presents both a challenge and an urgent call to action. Banks must not only stay informed about the latest GenAI developments. They must also invest in advanced detection and prevention strategies. This includes:

• Enhanced Monitoring and Detection. Integrating AI-driven solutions that can adapt to and recognize the nuances of GenAI-generated fraud.
• Staff Training and Awareness. Ensure teams are aware of GenAI’s capabilities and risks so they can better identify and respond to threats.
• Collaboration and Intelligence Sharing. Working closely with other financial institutions and regulatory bodies to share intelligence about emerging GenAI threats and effective countermeasures.
• Ethical Frameworks and Responsible AI. Ensuring fair and transparent AI use in fraud detection requires strong ethical guidelines.

By proactively addressing these areas, banks can not only mitigate GenAI’s risks. They can also harness its potential to enhance customer experience and workflow efficiency.

Responsible AI is essential to any GenAI strategy, and we cannot overstate its importance. Financial institutions must embed Responsible AI principles into their GenAI strategy to GenAI’s fraud challenges. This ensures not only protection against emerging threats but also the ethical harnessing of this technology’s immense benefits.

How Current AI Models Fall Short

Traditional AI models may fail to improve productivity because of poor data or a lack of clarity. Regulators increasingly demand insights and transparency in AI algorithms and models to ensure fairness. This is a challenge many existing models struggle to meet. 

A dedicated FATE (fairness, accountability, transparency, and ethics) team unleashes the core of Feedzai’s approach to Responsible AI. The FATE team creates embedded responsible AI functionality integrated into Feedzai’s products. This ensures FIs can effectively prevent fraud and combat financial crime.

How Feedzai Stands Apart

Feedzai’s approach to responsible AI stands apart in three key areas.

Cloud and Automation as Enablers

Automation and speed are essential assets in the fight against fraud and financial crime. Feedzai takes a cloud-first approach to AI that empowers financial institutions to stay ahead of emerging threats. 

With quick access to new features and versions, FIs can respond rapidly to evolving risks. Feedzai’s Data Science capabilities further accelerate risk strategy development and bias reduction, enabling FIs to implement new detection models within days, not weeks.

Responsible AI Embedded in Feedzai

Over the years, Feedzai has launched numerous innovations to reduce bias in AI systems. We’re also committed to making the whole process more effortless based on transparency and traceability principles.

Feedzai’s commitment to responsible AI is evident in groundbreaking innovations like FairBand. This tool helps FIs identify less biased machine learning models without incurring additional training costs. Meanwhile, FairGBM, another Feedzai innovation, allows FIs to optimize predictive performance and fairness simultaneously. Financial institutions gain the best of both worlds.

A Centralized Approach to Risk 

Feedzai’s RiskOps platform and unified case manager provide a 360º view of risk. This centralized system allows FIs to conduct thorough investigations based on high-quality feedback. The result is data diversity which is crucial for distinguishing between fraudulent and legitimate behavior. This approach reduces customer friction and enhances the ability to combat threats posed by technologies like Generative AI.

A Proven Track Responsible AI Record 

Global recognition of Feedzai’s responsible AI commitment is widespread. Awards such as “Worldwide Leader in Responsible AI for Financial Crime Platforms” by IDC and “Tech for Good” from The Stack underscore our leading position. The FairBand innovation also secured “Fraud Prevention Innovation of the Year” by Fintech Breakthrough. These recognitions solidify Feedzai’s position as a pioneer in promoting fair and transparent decision-making.

As ESG regulations tighten and the threat landscape evolves, Feedzai’s innovative solutions empower financial institutions to make fair, transparent decisions. These decisions can align seamlessly with Responsible AI and ESG’s social pillar. 

AI regulation and ESG frameworks are just starting to take shape. That’s why banks should immediately focus on building a future with responsible AI safeguards against fraud and discrimination. Steps like these are vital to fostering a more inclusive financial ecosystem.