Flag

We stand with Ukraine and our team members from Ukraine. Here are ways you can help

Get exclusive access to thought-provoking articles, bonus podcast content, and cutting-edge whitepapers. Become a member of the UX Magazine community today!

Home ›› Artificial Intelligence ›› AI for the Unbanked: How Technology Can Empower Rural Entrepreneurs

AI for the Unbanked: How Technology Can Empower Rural Entrepreneurs

by Thasya Ingriany
5 min read
Share this post on
Tweet
Share
Post
Share
Email
Print

Save

In rural areas, traditional banking often leaves entrepreneurs without the crucial financial tools they need. AI, however, is set to change this. By leveraging alternative data and automating local lending, AI creates new opportunities for financial inclusion among the unbanked. Learn how these innovations are closing gaps in rural economies, providing entrepreneurs with access to loans, and helping them build sustainable businesses. Uncover how technology and community efforts are coming together to fuel economic growth.

In many rural communities around the world, a lack of access to financial resources creates a significant obstacle to progress. Residents often rely on traditional methods of managing their money, such as keeping cash at home. While these practices offer a sense of control, they make it difficult to build a credit history or access loans from conventional banks. This lack of a credit profile can be a major hurdle, as traditional lenders depend heavily on credit scores to assess risk¹.

Consider Linda, a small-scale farmer in Southeast Asia. Like many others in her community, Linda dreams of growing her farm. However, the idea of saving beyond keeping cash at home feels like an insurmountable obstacle. Limited access to banks, or even the perception of limited access, discourages her. Even if a bank were readily available, hidden fees and minimum balance requirements can feel like a burden on her limited income. Past experiences or a general distrust of the banking system further complicate things. For Linda, the perceived control over her cash outweighs the benefits of formal banking, which can sometimes feel intrusive with its regulations.

Furthermore, this reliance on cash leaves Linda vulnerable in times of crisis. Imagine a family emergency or a crop failure. Without a formal account, Linda lacks the safety net of a formal financial system and is forced to turn to informal lenders with predatory lending practices. This not only traps her in a cycle of debt but also hinders her ability to build long-term financial security. Keeping cash at home also offers minimal returns, preventing her from growing her assets and accumulating an emergency fund.

This issue is widespread — only 27% in Southeast Asia have bank accounts, leaving millions unbanked.

Countries with developing financial infrastructure, like Cambodia, see even lower rates (See our Inclusive report here). Linda’s story isn’t unique. Millions face similar challenges, highlighting the urgent need for more inclusive financial systems.

While Linda might not meet traditional credit score criteria, alternative assessments based on her specific situation could be used. Examining both income and payment records can offer a clearer view of her financial trustworthiness².

If we imagine a future where this kind of information can be easily collected, how could AI help bridge the gap for people like Linda?

The Power of Groups, Enhanced by AI

In rural communities around the world, a powerful force exists: close-knit social networks. People readily support each other, reflecting a spirit of mutual aid. In Indonesia, this concept is called “gotong royong.” This strong sense of community is a key ingredient in the success of the Grameen Bank model, founded by Nobel laureate Muhammad Yunus in Bangladesh.

The Grameen Bank specifically targets individuals who lack traditional collateral for loans, often women living in poverty. Their innovative approach revolves around microloans — small loans starting at just USD25 — provided to groups, not individuals.

This fosters a strong sense of shared responsibility and community support. Each group member is accountable for repaying their portion of the loan, creating a powerful incentive for everyone to succeed. Imagine it as a team effort — if one member falls behind, it impacts the entire group’s ability to access future loans. To ensure accountability, loan officers from the Grameen Bank typically visit communities weekly. The loan amounts are kept small to prevent overextension, and repayments are structured as frequent, manageable installments. This frequent interaction also allows the bank to identify and address any issues within the groups early on.

How can we leverage technology to build upon this successful model and further empower individuals like Linda in similar situations around the world?

We explored the AI’s power that lies in analyzing alternative data sources. By considering things like consistent e-commerce cash-on-delivery payments or contributions to local savings groups, AI can create more comprehensive credit profiles for individuals like Linda, even without a formal banking history. This empowers lenders to assess creditworthiness beyond traditional models, ultimately helping more people build financial security.

Here’s how the Grameen Bank model works:

Grameen Bank Model with AI’s assistance

Here’s how AI can specifically amplify the power of groups:

Automated Group Formation and Management

AI can replicate the group lending model by automating group formation. It can consider factors like financial behavior based on digital footprints, and shared goals to create well-matched groups with a high likelihood of success. AI can also automate group management tasks like tracking contributions and monitoring repayment behaviors, freeing up resources for human interaction and support.

An AI system can automatically create groups of five or more people and then suggest specific actions to take if a member’s contribution is lacking

Real-Time Insights and Support

AI can analyze group dynamics and identify potential issues early on. It can provide targeted interventions or suggest support mechanisms to struggling groups before defaults occur. Additionally, AI can personalize loan terms based on the group’s overall risk profile, ensuring fair and sustainable lending practices.

By analyzing group dynamics, AI can identify risks early, suggest interventions, personalize loan terms, and promote sustainable lending

Conclusion

For generations, rural communities have thrived on “gotong royong,” a spirit of mutual support that has helped them weather challenges. The success of the Grameen Bank further underscores the power of strong communities in achieving financial inclusion. However, even the most time-tested traditions can benefit from a modern boost.

This is where Artificial Intelligence (AI) steps in. With its rise, we have a unique opportunity, not to replace “gotong royong,” but to make it even stronger. Imagine AI tools that analyze data from financial institutions and fintech companies, identifying creditworthy individuals who might not qualify under traditional systems. These AI insights can then seamlessly connect with existing social networks, empowering “gotong royong” groups to extend their reach and effectiveness. This would foster a more secure, transparent, and inclusive financial system within these communities.

Of course, such a vision requires careful planning and collaboration. The data used by AI needs to be reliable and reflect the specific situations of these communities. Additionally, we must determine the appropriate weight given to AI analysis within the decision-making process.

While the AI infrastructure for this purpose is still under development, fueled by data shared by financial institutions and fintech companies, the potential benefits are undeniable. As this infrastructure matures, it holds the promise of equipping rural communities with the tools they need to thrive — a powerful combination of tradition and technology that can bring greater economic stability and prosperity.


¹Bank, Asian Development. “Enhancing Small Enterprises’ Access to Finance: ADB’s Take.”, 1 Aug. 2014, https://www.adb.org/features/enhancing-small-enterprises-access-finance-adbs-take Accessed 17 July 2024.

²“Guide to Alternative Credit Scoring.” SEON, seon.io/resources/guides/alternative-credit-scoring/

The article originally appeared on Medium.

post authorThasya Ingriany

Thasya Ingriany
Thasya is a Creative Strategist at Sixty Two who excels in identifying growth opportunities and crafting narratives that resonate effectively with the Sixty Two audience, aligning these strategies seamlessly with Project Lima's overarching goals. Read more of her works on Medium.

Tweet
Share
Post
Share
Email
Print
Ideas In Brief
  • The article explores how AI can enhance financial systems for the unbanked by using alternative data to create accessible, user-friendly credit profiles for rural entrepreneurs.
  • It analyzes how AI can automate group lending practices, improve financial inclusion, and support rural entrepreneurs by strengthening community-driven financial networks like “gotong royong”.

Related Articles

Consistency in UI/UX builds trust and efficiency — without it, users feel lost. Learn how top brands maintain it and how AI can help.

Article by Rodolpho Henrique
Consistency in UI/UX Design: The Key to User Satisfaction
  • The article examines the role of consistency in UI/UX design for user trust and efficiency.
  • It showcases visual, functional, and interaction consistency in creating seamless experiences.
  • The piece warns about the negative effects of inconsistency, including confusion and frustration.
  • It promotes the use of AI and design systems to ensure consistency across digital platforms.
Share:Consistency in UI/UX Design: The Key to User Satisfaction
4 min read

If Mobile-First thinking has revolutionized the UX Design industry, AI-First is promising to be an even more spectacular kick in the pants.

Article by Greg Nudelman
The Rise of AI-First Products
  • The article explores how AI-powered operating systems are changing user interactions.
  • It covers AI-driven personalization, automation, and adaptive interfaces.
  • The piece discusses challenges like privacy, over-reliance on AI, and user control.
  • It highlights opportunities to design more intuitive and human-centered AI experiences.
Share:The Rise of AI-First Products
11 min read

AI is reshaping UX, and Figma may be sinking. As AI-driven systems minimize UI, traditional design roles must evolve — or risk becoming obsolete. Are you ready to adapt?

Article by Greg Nudelman
AI Is Flipping UX Upside Down: How to Keep Your UX Job, and Why Figma is a Titanic (It’s not for the Reasons You Think)
  • The article explores the fundamental shift in UX as AI-first systems minimize the role of UI, rendering traditional design tools like Figma increasingly obsolete.
  • It introduces the “Iceberg UX Model,” illustrating how modern AI-driven interfaces prioritize functionality and automation over visual design.
  • The piece argues that UX professionals must shift their focus from UI aesthetics to AI-driven user experience, emphasizing use case validation, AI model integration, and data-informed decision-making.
  • It warns that designers who remain fixated on pixel-perfect layouts risk becoming obsolete, urging them to adapt by engaging in AI-driven UX strategies.
Share:AI Is Flipping UX Upside Down: How to Keep Your UX Job, and Why Figma is a Titanic (It’s not for the Reasons You Think)
7 min read

Join the UX Magazine community!

Stay informed with exclusive content on the intersection of UX, AI agents, and agentic automation—essential reading for future-focused professionals.

Hello!

You're officially a member of the UX Magazine Community.
We're excited to have you with us!

Thank you!

To begin viewing member content, please verify your email.

Tell us about you. Enroll in the course.

    This website uses cookies to ensure you get the best experience on our website. Check our privacy policy and