Aboitiz Data Innovation (ADI) announced that its joint non-mortgage fintech lending project with the UnionBank of the Philippines (UnionBank) and the Smith School of Business at Queen’s University in Canada on anti-discrimination law, artificial intelligence, and gender bias was recently listed in the Global Top 100 list of Artificial Intelligence (AI) solutions by the International Research Centre on Artificial Intelligence (IRCAI) under the auspices of UNESCO.
The Top 100 list is created by IRCAI to scope and showcase effective and impactful solutions that contribute to the 17 United Nations (UN) Sustainable Development Goals (SDGs) through the application of AI. IRCAI recognized the project’s applicability, credibility, and ethics in solving SDG1: No Poverty, SDG5: Gender Equality, SDG10: Reduced Inequality, and SDG17: Partnerships to Achieve the Goal, evaluating the research as “excellent”, placing it in the top 30% of projects on the Global 100 list.
“This recognition is yet another milestone achievement for our team,” ADI Chief Executive Officer Dr. David R. Hardoon commented. “Our study highlights the importance of addressing gender bias in fintech lending and that we need to rethink existing anti-discrimination laws that shall be applicable to AI systems to ensure fairness and equality. We’re proud to have our work recognized by IRCAI and UNESCO, and with its proven significance for the greater good, we hope that our findings will contribute to the continued development of more ethical and inclusive AI solutions.”
Recent studies have shown that the consumer lending market process is stacked against women and minorities. Recognizing the inequalities and imbalances in play, ADI carried out the study – based on a use case in non-mortgage fintech lending – engaging in explainable and responsible AI efforts. The study investigated whether excluding the use of gender information in assessing creditworthiness hurt or helped the groups they are supposed to protect. It ultimately revealed that using gender-related data results in a significant decrease in gender discrimination and increased profitability for the firm.
The project serves as a guide in improving anti-discrimination laws to ensure that Machine Learning (ML) models foster a fairer and more inclusive system, particularly for discriminated groups within the financial services industry, all the while increasing firm profitability.
“We are honored to be named one of the top 100 international AI solutions for achieving the 17 SDGs. The result of our study provides a strong basis for whether the use of protected attributes such as gender data should be allowed in fintech, particularly credit lending models. To achieve a win-win situation for both business and communities, it eventually comes down to the responsible collection and use of gender data where minority groups are treated with fairness and businesses achieve higher profitability,” said Dr. Adrienne Heinrich, Head of ADI’s AI and Innovation Center of Excellence.
As AI systems become more complex, achieving transparency, reliability, and interpretability can be a challenge. ADI has created proper guidelines to ensure ethical and proper AI use through its Explainable and Responsible AI (XRAI) Guidelines. The XRAI Guidelines include practical recommendations for leaders, team members, and stakeholders involved in the development and deployment of AI systems at ADI. These recommendations cover a wide range of topics, including data collection and management, model development and testing, human oversight and control, and the ethical implications of AI. The guidelines are based on eight main principles—transparency, explainability, repeatability, safety and security, robustness, fairness, accountability, and human agency and oversight. Ensuring reliable and responsible use of AI-driven technology is crucial, and the responsibility falls under businesses to actively address such concerns. This is a step in the right direction as ADI continues to encourage the operationalization of responsible AI, as well as promote trust in the technology, within and outside the organization