AI and Financial Inclusion: A Vision for the Future
Sopnendu Mohanty, co-founder of the Global Finance and Technology Network (GFTN), has urged banking institutions to harness the power of artificial intelligence (AI) not just for operational efficiency, but to promote financial inclusion for underserved populations. Speaking at the Fortune Brainstorm AI conference in Singapore, he emphasized that technology should not merely focus on automating layoffs but instead should aim to serve low-income communities often left out of traditional banking systems.
The Challenge of Traditional Banking Models
The traditional loan model employed by banks is heavily reliant on collateral, systematically sidelining millions of low-income individuals who lack guarantees. According to the World Bank, only 25% of people in low- and middle-income economies have access to formal loans as of 2024. Mohanty referred to this exclusion as “the elephant in the room,” highlighting a critical gap in meeting global credit needs.
AI as a Solution for Financial Accessibility
Mohanty advocates for the use of AI to create “credible, predictive, and golden behavioral data” as a substitute for traditional collateral. This innovation would enable banks to evaluate creditworthiness through alternative metrics, such as spending habits, employment history, and mobile usage patterns. By focusing on these factors, financial institutions could extend their services to those who have been historically overlooked.
The Role of GFTN in Emerging Markets
Supported by the Monetary Authority of Singapore, GFTN aims to guide emerging markets in effectively integrating technology within their financial systems. Mohanty points to Southeast Asian companies like Grab, Sea, and Goto, which utilize data from various e-commerce platforms to serve unbanked consumers. Additionally, he highlighted India’s Aadhaar system, which offers unique identification to residents, as fundamental infrastructure for identity verification.
The Ethical Implications of AI in Banking
The debate surrounding AI’s role in the labor market remains contentious. While banks continue to implement AI primarily for cost reduction, Mohanty warns against prioritizing efficiency at the expense of human capital. He emphasizes the pressing need to train a workforce capable of adapting to AI advancements, citing Singapore’s initiative to skill up to 15,000 AI practitioners across various sectors like retail, manufacturing, and healthcare.
The Dual Nature of AI in Finance
Mohanty’s perspective embodies the dichotomy within the financial sector regarding AI’s potential for both disruption and inclusion. While automation poses risks to job security, he believes that technology can democratize access to financial services if applied thoughtfully to poorly served communities. His focus on moving away from collateral-based lending aligns with a growing movement advocating for technological advancements that promote equitable growth.
Addressing Challenges in Implementing AI Solutions
Despite the promising future Mohanty envisions, significant challenges remain. These include concerns over ethical data usage, infrastructural gaps in emerging markets, and the need for regulatory frameworks that balance innovation with consumer protection. The pathway toward achieving meaningful financial inclusion through AI is complex, but the dialogue initiated by thought leaders like Mohanty is a crucial first step.