About Michu Digital Lending
Michu is an AI-powered, uncollateralised digital lending platform from the Cooperative Bank of Oromia, designed to provide fast, working-capital loans to micro, small, and medium enterprises (MSMEs) in Ethiopia. Using Qena’s AI credit model and Coop Bank data, Michu aims to close Ethiopia’s MSME credit gap by offering repeatable, instant loans through mobile and web.
Their loan products include:
- Michu Guya: Daily/weekly loans
- Michu Kiyya: Informal/formal monthly loans
- Michu Wabi: Larger ticket loans up to 300,000 ETB
Michu helps millions of MSMEs in Ethiopia access the credit they need to grow and thrive, making it a leading platform for business lending in the region.
The Strategic Objectives of Michu Digital Lending Set to Reach
- Drive high-quality traffic to increase MSME loan adoption
- Improve loan application quality by using AI agents for borrower intent and engagement
- Reduce cost per borrower acquisition and increase loan conversion rates with AI agents
- Scale operations by automating loan cycles and support without increasing headcount
Main Pain Points
Low repeat usage
High acquisition costs
Limited MSME segmentation
Growth Enablers
TechMonk’s AI Customer Platform: The Key to Furnishka’s Success
1. MSME-Centric Segmentation Using CDP & Lending Data
TechMonk integrated its Customer Data Platform (CDP) with Michu’s core banking systems to build 360° profiles of MSMEs, analysing product mix (Guya, Kiyya, Wabi), repayment history, number of cycles, ticket-size trends, and gaps between loans.
Micro-segments included “graduation-ready” MSMEs, dormant but good-history borrowers, at-risk early-delinquency borrowers, new-to-credit MSMEs, and tagged groups like women- and youth-owned businesses, enabling precise, segment-specific journeys.
2. Agentic AI Journey Builders Across the MSME Loan Life Cycle
TechMonk’s Agentic AI powers the entire MSME loan lifecycle, starting with Acquisition & Onboarding through WhatsApp/SMS welcome journeys that educate new borrowers in their local language and guide them to the right product. In Origination & First-Loan Conversion, real-time AI support addresses documentation and loan product details, while intelligent follow-ups encourage completion.
Cross-Sell & Graduation to Larger Loans uses automated journeys to reward strong payers with higher loan limits, and Reactivation of Dormant Borrowers through targeted WhatsApp campaigns re-engages inactive MSMEs with new offers and incentives.
3. WhatsApp-First Agentic Engagement
TechMonk made WhatsApp the primary channel for MSMEs, offering a seamless experience covering education, application assistance, post-disbursement engagement, upsell, and collections. This approach catered to MSMEs who operate on mobile and prefer conversational workflows over complex apps. The use of AI agents ensured that all interactions were efficient, personalised, and scalable.
4. Support Automation + Human Handoffs
TechMonk’s AI agents handle routine pre-sales and post-sales queries, such as questions about product dimensions, lead times, delivery zones, and customisation options. For more complex inquiries, the AI agents direct the customer to showroom sales staff through a unified inbox. This increases the efficiency and ensures no leads are missed.
Value CreatedMichu Digital Lending Business Impact Post-Implementation
1. Higher Loan Conversion and Repeat Borrowing
The implementation of Agentic AI workflows led to an increase in average loans per active MSME, with some “graduated” cohorts seeing up to a 2–3x increase. This helped drive more revenue from existing customers through repeat borrowing.
2. Successful Reactivation of Dormant Borrowers
Reactivation campaigns converted 25–35% of dormant borrowers back into active users, often with higher ticket sizes. This resulted in more engaged borrowers and a boost to overall loan volumes.
3. Precision Targeting and Lower CAC
Through precision targeting of inactive and past borrowers, Michu reduced reliance on cold acquisition methods, lowering customer acquisition costs (CAC) by ~20–30%. This made borrower acquisition more cost-efficient.
4. Increased LTV with More Cycles and Larger Loans
The combined effect of more loan cycles, higher ticket sizes, and improved repayment behavior led to a 35–50% increase in MSME LTV in priority segments, increasing long-term revenue.
5. Enhanced Borrower Experience with Relational Credit
Journeys were tailored to reflect real cash-flow patterns, informal behaviors, and channel preferences, making digital credit feel relational rather than purely transactional. This increased borrower satisfaction and loyalty.
6. Efficient Engagement and Scalable Journeys
TechMonk’s AI-powered engagement transformed Michu from a simple disbursement platform to a relationship-driven lending solution, with engagement logic and journeys designed to scale across different MSME verticals, such as agri-businesses or women-owned enterprises.
Results & Impact-
+45–60%
25–35% Winback on Targeted Cohorts
20–30% Lower Cost per Active MSME
