UNLOCKING FINANCIAL INCLUSION WITH INTELLIGENT INFRASTRUCTURE

Think about a couple of financial services paradoxes in some parts of the African continent. You can buy a cow with your phone, but good luck getting a bank loan to start a dairy farm. We've mastered sending money through the air. However, traditional credit scoring still wants to see your great-grandfather's land deed. Or in a separate scenario where your vegetable seller accepts four different types of digital payment but might be considered 'uncreditworthy' by traditional banking standards. It's like having a PhD in quantum physics but failing introductory algebra because you didn't show your work the conventional way. These paradoxes aren't just unfortunate ironies but challenges that must be addressed.

‍

‍

There are distinct layers to the financial inclusion issue on the continent. One is as you can find in the larger cities of Cairo, Lagos, Nairobi, Johannesburg, and Kinshasa, where the often harped about high mobile penetration, mobile money apps, and extensive bank branch networks belie that a considerable portion of the 700 million African urban dwellers don't have access to valuable and affordable financial products and services that meet their needs - transactions, payments, savings, credit and insurance - delivered responsibly and sustainably. Moving away from the urban areas, the circumstances are far worse in semi-urban and rural communities.

‍

One of the core functions of financially robust systems that this essay seeks to spotlight is credit provision due to its role in supporting economic growth and how it can be a key lever to development on the continent.

‍

There are a few things about financial inclusion issues that Africa gets the hang of. First, is a cataloguing of the problems. There is an endless churn of academic research on the state of financial inclusion or lack thereof, and the accompanying policy pronunciation or two promising to attack the problem. For instance, during last year's President Dialogue by African Heads of State and Government and African Multilateral financial institutions, the conversation underscored the urgency to establish the African Union Financial Institutions (AUFIs). During the convening, the importance of establishing financial institutions focused on "improving Africa's access to capital, impartial debt management mechanisms, and fair credit and risk assessments were agreed upon. 

‍

Another similar example is in March 2022, when the African Union launched the "African Union's Women and Youth Financial and Economic Inclusion Initiative," aiming to unlock USD 20 billion to enhance financing opportunities and employment parity for at least 1 million African women and youth by 2030. This initiative underscores the continent's (at least verbal) commitment to front and centering access to credit as a development theme.

‍

The correct assessment is that these forums and arising commitments are honest, recognize the problem, are well-intentioned, and, if well-implemented, can drive meaningful economic growth.

‍

Furthermore, looking at historical implementations of some of these commitments, reforms that improved access to credit have contributed to some form of economic growth. Case in point: In the early 21st century, some African countries undertook financial sector reforms to enhance credit availability. These reforms led to an increase in credit extension, which grew impressively over a decade despite starting from a low base.

‍

How has this trended from the days of substantial progress? Consider the following insights from recent research on the subject below:

‍

Credit access in Sub-Saharan Africa has declined over the past 15 years, with private sector credit as a percentage of GDP dropping from 56% in 2007 to 36% in 2022. This is compared with East Asian and Pacific emerging nations, where credit provision grew rapidly over the same period, driving economic growth and rising incomes. Similarly, in Latin America, credit markets expanded GDP by 30% since 2007, surpassing Sub-Saharan Africa despite starting from a lower baseline. The stagnation of credit access in Africa highlights a significant growth gap that stifles private sector development.

‍

13 of 18 African countries have household debt below 10% of GDP, signifying untapped lending opportunities. Only a handful of countries—Nigeria, Tunisia, Morocco, and South Africa—have household debt ratios that approach or exceed the pre-emerging market average, but these still lag behind emerging and developed economies. This limited penetration of credit markets represents a missed opportunity for banks to finance household investments and catalyze broader economic activity.

‍

Why Traditional Models Fall Short

‍

It has to be accepted that traditional credit-giving sources can't meet the continent's needs. Prohibitive collateral requirements such as real estate and equipment make it difficult for ventures without such assets. In instances where they meet these loan application criteria, application systems prey on financial literacy levels or impose touch application conditions. Finally, borrowers who cross the first two hurdles must contend with the final level boss of high interest rates/borrowing costs. Nobody wins.

‍

Implications for Economic Growth

‍

On today's episode of stating the obvious, difficulties in accessing credit hinder individual and venture access to required funding to maximize economic opportunities. Find a few examples below: 

• Farmers struggle to adopt climate-adaptive technologies, leaving agricultural value chains vulnerable to climate effects.
• Reduced responsiveness to environmental and habitation difficulties encountered by poorer citizens who can't afford climate proofing, deepening already stark social and economic inequity.
• Young people, women and people living with disability, who are the most vulnerable, are more undermined due to a lack of collateral or other cultural barriers who usually lack collateral or face cultural barriers.

‍

So, while things have been done and continue to be done (or discussed at conferences) about the state of play, the most under-affected by any positive gains are essentially still the informal sector and vulnerable demographies, mainly because the nature of individual life, behavioral patterns, and commercial activity doesn't provide structured enough data for traditional providers to extend services to them. They, metaphorically speaking, don't have much of a kiss to build a dream on.

‍

However, the paradoxes introduced at the beginning of the essay suggest some level of infrastructure or mechanism upon which credit services can be delivered or at least rethought where the excluded are concerned.

‍

The Promise of Intelligent Infrastructure in Overcoming Credit Barriers

‍

The limitations to accessing credit aren't strictly because institutions providing credit want to be like Smaug in The Hobbit and jealously guard their resources but because these 'traditional' institutions often rely on formal credit histories and credit assessment models to assess the creditworthiness and make disbursement decisions.

‍

The challenges of credit access in Africa require a rethink in the solution delivery approach. This is where AI-enabled Alternative Credit Scoring (ACS) and intelligent financial infrastructure can play a critical role:

1. Alternative Data Utilization: AI can parse non-traditional user data, including mobile money transactions, utility payments, and social activity, to advise on credit eligibility
2. Quick and Seamless Application Processes: Where deployed versus existing systems, an ACS can simplify the application process (especially return applications), reducing the time and effort required for this step
3. Personalized Credit Offers: AI models can tailor loan products to individual needs, mitigating the mismatch between credit terms and borrower payback ability
4. Dynamic Risk Assessment: An ACS system's critical function in enhanced risk profiling is allowing financial institutions to apply more competitive and tailored interest (or other transaction fees) in alignment with market realities

‍

By addressing these structural barriers, AI can unlock access to credit, fueling economic growth and enabling resilience in Africa's most vulnerable sectors.

‍

However there is a need to further contextualize the cliched but courageous suggestion that AI can tackle the problem as is currently touted to do for every human challenge. We can take a critical look at how this may work.

‍

To examine AI’s workability, one has to establish very early that as with most things from religion, to e-commerce and cultural norms, on the route to adopting anything in Africa, one is most certainly expected to contend with a set of barriers opposite to the ones which they would encounter in any other part of the world, and to appropriate Murphy’s law the route to adaptation will have in it the most chaotic elements, at the most chaotic times and in the most chaotic manner. To employ a ‘Nigeria-ism’ - your father's AI in technologically advanced countries is not the same one that will work in Africa. 

‍

For an AI-enabled solution to work in theory, it has to recognize that Africa's credit access challenge isn't just a technological problem - it's a complex interplay of trust, infrastructure, and cultural dynamics. Therefore, an intelligent solution introducing an AI-powered credit scoring and access system has to work with, rather than against, Africa's unique social fabric. At its core, the system can combine backend AI capabilities with familiar tools and people on the user's end, building upon existing cooperative, savings and informal lending relationships deeply embedded in African communities.

‍

From a solution architecture perspective, one can imagine a dual-layer sophisticated AI backend that handles complex credit scoring and risk assessment, interfacing with a simple, chat/message-based frontend that feels familiar to users. 

‍

This way, the current, non-predatory substitutes for personal finance and MSME financing can maintain their role as trusted intermediaries and service providers but are now armed with AI-enhanced decision-making capabilities. The system progressively builds credit profiles by combining traditional financial data with alternative data points, all while respecting existing social trust mechanisms. Instead of asking low-tech users to access the solution in its most advanced technological form, it meets them where they are - on messaging platforms they use several times daily.

‍

This approach's usefulness is, as mentioned above, in its recognition that technological solutions in Africa must be built around existing trust networks and social structures, not in spite of them. 

‍

Consider a few design considerations to understand how this route can address typical Artificial Intelligence and Machine Learning implementation challenges.

‍

Infrastructure - An offline-first architecture ensures functionality even in areas with intermittent connectivity, while the customer messaging/SMS interface improves viability in low-bandwidth areas while providing continuous service availability

‍

Data limitations such as inconsistent or incomplete data can be mitigated 

• Progressive data collection strategy starts with basic, available data and grows over time
• Combines traditional financial data with alternative data sources like mobile money transactions
• Leverages existing informal borrowing records as a foundation
• Implements flexible input methods to accommodate both digital and manual data collection

‍

The system stores all transaction records in a safe and unchangeable digital ledger. It uses small, specialized programs to quickly collect and process data, even in areas with weak internet. All data is gathered into one central storage system, and smaller computers handle work locally when the internet is unreliable.

‍

AI combines different methods to analyze data. It uses smart models to examine traditional credit information and new types of data, like phone usage and social connections. These models can learn from one area and adjust to work in another, and multiple institutions can collaborate without sharing private data.

‍

The credit scoring system looks at many things, like spending habits, community trust, and mobile behavior. Taking farmers as an example, it can consider the timing of planting and harvest seasons while adjusting methods based on what works best in each region and explain decisions in simple ways to build trust and follow the rules.

‍

For a quick and dirty explanation of how a fit-for-purpose intelligent solution can work, consider integration. Simple tools connect to apps and websites to ensure everything stays updated in real-time. In the inevitable event of internet cuts, transactions can be updated later. As mentioned earlier, ubiquitous messaging is a user-friendly way for people to apply for loans and interact with the system.

‍

Trust and Adoption

‍

• Builds on existing relationships rather than trying to establish new trust frameworks
• Uses WhatsApp's (a hypothetical example) familiar interface to reduce technological barriers
• Maintains human interaction while augmenting their capabilities
• Incorporates local validation mechanisms to ensure culturally appropriate credit assessment

‍

Financial Literacy as Catalyst

‍

• A simplified user interface through family mechanisms reduces the learning curve
• Progressive feature rollout allows users to grow with the system
• Built-in educational components delivered through familiar channels

‍

Challenging the "Africa Is Not Ready" Narrative

‍

This solution directly confronts and dismantles the misconception that Africa isn't ready for advanced financial technology:

1. It demonstrates that innovation in Africa doesn't mean wholesale adoption of 'outside' solutions but rather thoughtful integration of advanced technology with existing social structures.
2. The high penetration of mobile phones and messaging across the continent proves that Africans readily adopt technology when it provides clear value and aligns with their needs.
3. Mobile money's success in Africa shows that the continent can leapfrog traditional financial infrastructure when solutions are appropriately adapted to local contexts.
4. The solution builds on existing networks and extends the frameworks in place at traditional providers.
5. This adaptive approach eliminates the need for technology to function at its most mature point immediately, allowing for gradual progression.

‍

What sets this solution apart is its recognition that Africa's unique characteristics are strengths to build upon, not obstacles to overcome. It shows that with the right approach, advanced AI technology can be successfully deployed in ways that respect and enhance existing social structures while solving real problems in financial inclusion.

‍

Conclusion

‍

The essay deliberately focuses on financial inclusion and, more specifically, access to credit. The concomitant effect of financial inclusion, i.e., economic development and built intelligent infrastructure, can be an essential foundation for building resilient, equitable, and prosperous communities in the coming decades. By harnessing AI-driven tools and alternative data, we can unlock opportunities for those historically excluded, fostering not just economic growth but also transformative change as evidenced by gender-focused financial products tailored for women in agribusiness and climate-conscious initiatives, or pay-as-you-go solar financing models, demonstrate that when financial systems are designed to prioritize inclusion and sustainability, they catalyze widespread benefits. 

‍

There is a lot of work for stakeholders—governments, financial institutions, technology providers, and development agencies- to have a great leap forward in terms of outcomes. Policymakers must create enabling environments for data-driven innovations while ensuring ethical safeguards. Financial institutions should seize immediate opportunities to pilot AI-enabled solutions that address inclusion gaps, starting with partnerships that leverage trusted local networks. Development organizations and technology firms can provide technical expertise and capacity-building, helping scale what works. Everyone involved can take steps forward to build a financial and other impactful ecosystem that solves home-grown problems and reflects African ingenuity, values, and potential. 

‍