Discover how artificial intelligence (AI) and machine learning (ML) are reshaping financial inclusion for thin file consumers, overcoming credit challenges. Explore predictive modeling, alternative data analysis, and ethical considerations in this insightful article.

Discover the valuable lessons nature teaches us about fostering a healthy company culture that honors the uniqueness of each employee. Learn how to build a thriving 'forest' of a workplace through collaboration, inclusivity, and balanced leadership, leading to sustained success and a fulfilling workplace for all.

Learn how lenders can stay competitive during economic downturns by leveraging Zest AI's technology for faster, more accurate auto loan decisions. Discover the benefits of AI-automated underwriting, including increased efficiency, compliance, and customer satisfaction.

Discover the rich history of credit unions, the challenges they face in today's financial landscape, and the strategies they employ to ensure their endurance for another 115 years. Explore the role of technology, the quest to engage younger members, and the symbiotic relationship between small and large credit unions. Find out how these financial institutions adapt to changing times and why their legacy is set to continue empowering communities for years to come.

Discover how credit unions are offering better lending options during economic challenges like rising inflation. Learn about AI loan decisioning tools, resilience, and their commitment to equitable financial practices.

Explore the transformative power of AI and machine learning in lending, guided by the four crucial pillars of fairness. Discover how data, algorithmic decisioning, race estimation, and compliance come together to create a roadmap for financial institutions, consumers, and policymakers, ensuring not just compliance but a future of transparent, equitable, and bias-free lending practices. Join the conversation on promoting fairness in AI-automated underwriting and learn how technology can empower financial inclusion while eliminating systemic biases.