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AI and Fintech Mix for Financial Inclusion
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In today's world, digital and financial accessibility are basic necessities for people, and necessary conditions for achieving economic wealth. Financial inclusion, in particular, has long been recognized as a cornerstone for reducing poverty and boosting economic prosperity. However, due to geographical, economic, or societal constraints, traditional banking systems have often fallen short of reaching the underbanked populations.
Fintech has been a fundamental driver in the past decade to facilitate this. And now, thanks to the transformation coming with AI, it's possible to foresee a new acceleration in that direction by leveraging the power of machine learning and data analytics to extend financial services to those previously left at the margins. From generative AI-powered chatbots that offer financial advice in multiple languages to sophisticated algorithms that provide credit scores for the unbanked, AI and fintech are about to redefine the parameters of financial access.
Progress in Financial Inclusion and the Impact of Fintech
From mobile banking and payments to peer-to-peer lending and blockchain technology, fintech innovations have fundamentally altered the landscape of financial services, contributing significantly to the advancement of financial inclusion.
The latest data from the Global Findex Database of the World Bank, representing the most comprehensive source of data related to financial inclusion, reveals compelling data that underscores this progress:
![An infographic with the title 'financial inclusion' with a mobile phone showing an account on the left-hand side and a phone tranferring money on the right-hand side An infographic with the title 'financial inclusion' with a mobile phone showing an account on the left-hand side and a phone tranferring money on the right-hand side](/fibe/bilder/presse/newsletter/nl-12.6.24/fibe_2025_linkedin_info-grafik-financial-inclusion_1200-x-626-px_final_xxxldesk43.png)
Account Ownership: As of 2021, 76% of adults worldwide own a financial account, a remarkable increase from 51% in 2011. This growth represents a 50% increase over the past decade. In developing economies, account ownership rose from 63% in 2017 to 71% in 2021, demonstrating significant strides towards financial accessibility.
Gender Gap Reduction: The gender gap in account ownership in developing economies has decreased from 9 percentage points to 6, indicating progress towards gender equality in financial access.
Digital Payments: The adoption of digital payments has surged, with 57% of adults in developing economies engaging in digital transactions in 2021, up from 35% in 2014. In this sense, the pandemic accelerated the use of digital payments significantly.
Mobile Money in Sub-Saharan Africa: Mobile money became a key enabler of financial inclusion in the region, showcasing how mobile platforms can bridge financial gaps, particularly for women. Data from 2021 shows that 55% of adults possessed a financial account, with one in three individuals owning a mobile money account.
Despite these advances, challenges remain. Consider, for example, that only 55% of adults in developing economies could access emergency funds within 30 days.
The data points to a dual narrative: significant progress in financial inclusion driven by fintech, juxtaposed with persistent challenges that still need to be addressed - meaning that there’s still a considerable opportunity, especially in developing economies, to make an impact for the unbanked and the underbanked populations. Here’s how AI can assist in achieving that goal:
AI for Financial Inclusion: A Strong Ally for Fintech Companies
AI-driven solutions in fintech are paving the way for more personalized, accessible, and secure financial services.
For example, alternative credit scoring is emerging as a significant tool in enhancing financial inclusion and economic growth, benefiting consumers and lenders by utilizing AI and machine learning to process non-traditional data sources like utility bills and rent payments and evaluate creditworthiness. This new approach is particularly valuable for the unbanked—individuals lacking conventional financial services such as bank accounts and credit cards.
The traditional credit scoring model, which relies heavily on credit history, often excludes the unbanked, leaving them vulnerable to high interest rates and exploitation by informal financial channels. AI and machine learning significantly enhance the accessibility and efficiency of alternative credit scoring by rapidly processing vast amounts of data, turning a task that could take days into minutes or seconds. This speed and efficiency allow lenders to understand an applicant's creditworthiness more comprehensively and quickly.
Additionally, AI systems continually learn and improve, providing predictions on a borrower's ability to repay loans with a depth and accuracy unattainable by traditional models.
Another example is mobile banking apps that use AI to offer personalized financial advice and savings plans based on an individual’s spending habits and financial goals. These apps can help users from different backgrounds manage their finances more effectively, encouraging savings and investment, and ultimately contributing to their economic wellbeing.
In terms of accessibility, AI-powered chatbots can communicate in multiple languages and dialects, breaking down language barriers and making financial services comprehensible and accessible to a diverse range of users. These AI interfaces can guide users through the process of setting up a bank account, transferring money, or applying for a loan, all without the need for a physical bank visit, which can be a significant obstacle in remote or underserved areas.
On the security front, AI enhances the integrity of financial transactions through advanced fraud detection systems. These systems can analyze transaction patterns in real-time to identify and flag potentially fraudulent activities, protecting users from loss and identity theft.
However, it's important to highlight that while AI-driven solutions offer significant advantages, they also bring to light ethical and practical challenges. Concerns such as algorithmic bias and data privacy need urgent attention to prevent perpetuating inequalities or compromising personal security. Moreover, ensuring these technologies are accessible and understandable to all, particularly in underserved communities, is critical in accomplishing financial inclusion. Tackling these issues requires collaboration between policymakers, fintech firms, and AI technologists to create transparent, equitable, and secure financial ecosystems.
All in all, if the integration of AI in fintech promises more personalized, accessible, and secure financial services, along with substantial business opportunities for fintech companies, its success hinges on responsible and inclusive implementation.