This paper explores the dual impact of digital banks and alternative lenders on financial inclusion and the regulatory challenges posed by their business models. It discusses the integration of digital platforms, machine learning (ML), and Large Language Models (LLMs) in enhancing financial services accessibility for underserved populations. Through a detailed analysis of operational frameworks and technological infrastructures, this research identifies key mechanisms that facilitate broader financial access and mitigate traditional barriers. Additionally, the paper addresses significant regulatory concerns involving data privacy, algorithmic bias, financial stability, and consumer protection. Employing a mixed-methods approach, which combines quantitative financial data analysis with qualitative insights from industry experts, this paper elucidates the complexities of leveraging digital technology to foster financial inclusivity. The findings underscore the necessity of evolving regulatory frameworks that harmonize innovation with comprehensive risk management. This paper concludes with policy recommendations for regulators, financial institutions, and technology providers, aiming to cultivate a more inclusive and stable financial ecosystem through prudent digital technology integration.

There was a young lady called Aisha who lived in the wide and varied continent of Africa. Aisha dreamt of opening her jewelry store one day when she and her family resided in a tiny town. Yet she quickly saw that the absence of financial services in her town impeded her ability to accomplish her aspirations. Aisha and her family often encountered difficult and expensive processes even when they could visit banks despite traveling great distances. But suddenly, a miraculous event took place.

India does not have the most financially independent population. A large percentage of the population here doesn't even have a bank account. So you can confidently say that financial inclusion is severely lacking in our country. Financial inclusion is when every individual in a country is provided with equal access to all financial services irrespective of their background. Artificial intelligence's role in financial inclusion is that it is a system with no biases and can be considered fair.

Madam Ama Pomaa Boateng, the Deputy Minister of Communication and Digitalisation, says Artificial Intelligence (AI) is now driving global digital revolution and solving problems and challenges for emerging economies. AI is the ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment. Madam Boateng said this in Accra at the first face-to-face meet-up networking event on AI, organised by the Ghana-India Kofi Annan Centre of Excellence in ICT (GI-KACE). "Financial Inclusion using AI is a very good thing because it is part of the Sustainable Development Goals," she said. "It is actually seven out of the 17 goals that government and other institutions are working on by using AI to solve problems ….".

Two major trends Artificial Intelligence and Machine Learning are going to define the future of fintechs, said Soumya Rajan, Founder & CEO, Waterfield Advisors, at the FE Modern BFSI Summit. As for the emerging trends in the financial sector, Rajan noted two big themes, connectivity and computing, which are going to shape up the future. As far as connectivity is concerned, India has 750 million smartphone users, which is likely to become 1 billion by 2026. Rajan said that on the demographics front, the Gen Ys, and the Gen Zs are digital natives, which rely more on the technology for their financial services. In 2021, around 770 billion digital transactions happened globally, of which around 40 billion were with regard to mobile money.

Christine Wu, Managing Executive, Customer Value Management at Absa Retail and Business Bank, views artificial intelligence (AI) as an important enabler of the journey to a new banking model that is truly responsive to customer needs. "All areas of the bank's operations can benefit from AI – from the frontline, where we can make use of smarter profiling and customer interactions that are needs-based and tailored to a customer's profile, to customer servicing, where we can include clearer and more bespoke solutions to customers before they even ask – such as the automation of repetitive tasks," says Wu. AI is often defined as human-like intelligence achieved by machines – any system that "perceives its environment and takes actions that maximise its chance of achieving its goals". Advanced AI, according to experts, is also capable of learning and problem-solving. AI has been taken up enthusiastically across Africa, although the expert view is that it needs some fine-tuning to adapt to the African social and cultural environment. Still, the potential is as great in the banking landscape as it is in online and mobile transactions.

MANILA, Philippines, 16 February 2022 – Philippines-based alternative credit scoring company FinScore has become the first company to determine the creditworthiness of 100% of mobile subscribers in the country-- the highest market reach in the Philippine alternative credit scoring market. This followed the company's successful data-sharing partnership and completion of its integration with G-Xchange Inc. (GXI), allowing the company to calculate telco credit scores for mobile subscribers of industry giant Globe Telecom. FinScore's flagship service enables lenders, including commercial banks, neo banks, buy-now-pay-later (BNPL) platforms, digital lenders, and multi-purpose lenders to determine the creditworthiness of their loan applicants that have little to no credit data. Traditional credit scoring services only analyze a few data variables such as income level, homeownership, job title, and bank history. With over 70% of the unbanked and underbanked adult Filipinos, these traditional methods leave this segment underserved, with reduced ability to get approved for loans.

Did you miss a session from the Future of Work Summit? This article was contributed by Frederik Bussler, consultant and analyst. Around one in four American adults are underbanked, meaning they are underserved by traditional finance, and rely on high-fee alternative financial systems. For underbanked Americans, getting a loan or a credit card can range between being either difficult or next to impossible. For those who do have a credit score, it's often not a very high one.

Throughout history, society has debated the morality of debt. In ancient times, debt--borrowing from another on the promise of repayment--was viewed in many cultures as sinful, with lending at interest especially repugnant. The concern that borrowers would become overindebted and enslaved to lenders meant that debts were routinely forgiven. These concerns continue to influence perceptions of lending and the regulation of credit markets today. Consider the prohibition against charging interest in Islamic finance and interest rate caps on payday lenders--companies that offer high-cost, short-term loans.

But AI is laying the foundations to change that. Pioneers and FinTechs, followed now by some banks, are using AI to bring financial services to the unbanked, starting from "branchless banking" models, which are one hundred percent based on digital channels and with new business models leveraged in economies of scale. These companies are using AI to improve (and also create new) processes related to communication, fraud prevention, credit scoring and financial education.