Asset-Backed Lending Reshapes African Mobility Finance: Exploring the Moove Model

Buy a car, put it on the road, pay it off from your daily fares, and eventually own the vehicle. To an ordinary ride-hailing driver, the logic sounds simple enough. In reality, financing a commercial car across emerging markets is notoriously difficult. Traditional banks rarely lend to informal platform workers who lack steady payslips, audited books, or conventional collateral.

Rather than operating as a standard bank or a pure software platform, asset-backed mobility lenders act as direct vehicle underwriters. Understanding how this business model works in practice reveals why investors have poured hundreds of millions of dollars into vehicle financing across emerging markets, and where the financial pressures lie.

The Core Asset-Backed Vehicle Model

At its foundation, asset-backed lending means a loan is secured directly by a physical item with tangible market value. In mobility finance, the vehicle itself serves as the underlying collateral.

When a driver joins an asset-backed mobility programme, they do not receive a cash loan to buy a car on the open market. Instead, the financing company purchases the vehicle directly from manufacturers or dealerships, retaining full legal title and ownership of the car during the contract term.

The driver enters a revenue-share or drive-to-own agreement. They take possession of the car and earn income by providing rides on platforms like Uber or Bolt. Weekly or daily repayments are deducted directly from the driver’s earnings before the remainder is remitted to their account. Once the full term is complete, typically over 36 to 48 months, ownership of the vehicle is transferred to the driver.

This structure creates a closed-loop settlement system. By integrating directly with ride-hailing applications, the lender removes the risk of a borrower defaulting simply because they forgot or chose not to transfer their earnings to a bank at the end of the month.

Managing Credit Risk Without Payslips

In mature financial markets, credit decisions rely heavily on credit bureau scores and verified income histories. In emerging markets, where a large portion of the workforce operates informally, those metrics are absent.

To evaluate potential borrowers, asset-backed mobility fintechs use alternative underwriting data. They assess an applicant’s driving history, platform ratings, completion rates, and historical earning capacity on gig platforms. This data helps establish a prospective borrower's daily earning potential before a vehicle is assigned.

Risk management extends beyond software integrations. Because the lender retains ownership of the vehicle, it relies on hardware technology to safeguard the asset:

• GPS tracking: Continuous location monitoring ensures the vehicle remains within designated operational zones.
• Remote immobilisation: Lenders can disable the vehicle's engine electronically if contractual obligations or payment milestones are repeatedly missed.
• Automated maintenance schedules: Vehicles must be serviced at approved centre to preserve their market resale value.

If a driver decides to leave the platform or defaults permanently on their payments, the financing firm repossesses the vehicle, refurbishes it, and reassigns it to a new driver, protecting the lender's capital base.

Foreign Currency and Vehicle Inflation Pressures

While the asset-backed model solves early-stage credit risk, operating it at scale across African markets introduces severe foreign exchange and macroeconomic challenges.

Vehicles and spare parts are priced in hard currencies, primarily US dollars. Lenders typically raise debt capital from global institutional investors in dollars or euros to purchase these fleets. However, ride-hailing drivers earn their fares in local currencies such as the Nigerian naira, Kenyan shilling, or South African rand.

When a local currency depreciates sharply, the cost of servicing dollar-denominated debt escalates. If a financing firm passes that currency devaluation onto drivers by raising weekly repayments, driver earnings plummet, leading to higher default rates and platform churn. If the firm absorbs the currency loss itself, its operating margins shrink rapidly.

Furthermore, fuel price adjustments and general inflation directly affect driver profit margins. A driver paying significantly more for fuel has less net revenue available for daily vehicle repayments, exposing the lender to systemic credit risk across the entire fleet.

Who Wins and Who Faces Pressure?

The asset-backed mobility model shifts economic incentives across the urban transport ecosystem:

• Gig drivers: Gain access to new, productive assets and an avenue to eventual vehicle ownership without needing upfront capital or traditional collateral. However, they carry the burden of fixed daily contract costs regardless of platform demand or fuel price spikes.
• Ride-hailing platforms: Gain a steady supply of newer, more reliable vehicles and active drivers on their networks without spending corporate balance-sheet capital on fleet procurement.
• Asset-backed lenders: Generate reliable yield through direct platform deductions, but remain exposed to vehicle depreciation, high maintenance costs, local currency volatility, and complex fleet logistics.

The Long-Term Viability Test

As global interest rates remain elevated and emerging-market currencies face structural pressure, asset-backed mobility lenders are refining their operational workings.

To protect against fuel spikes and currency mismatches, mobility fintechs are increasingly shifting toward electric vehicles (EVs). Electric fleets lower operating costs for drivers by eliminating petrol expenses and reduce reliance on imported fuel, creating a more stable daily cost structure for vehicle repayments.

The ultimate test for the asset-backed model is balance-sheet resilience. As lenders expand across emerging markets, maintaining asset quality and managing foreign exchange exposure will determine whether vehicle financing fintechs can deliver sustainable long-term profits.