Can TraderMoni avoid becoming a waste of money?

With reports crowning Nigeria as the poverty capital of the world, any scheme with the objective of reducing poverty is worthy of evaluation beyond the dichotomy of “yet another waste of money” or unbridled praise. 

One such project is the TraderMoni scheme launched by the Nigerian government under its Government Enterprise and Empowerment Programme (GEEP). 

You may know it as the ₦10,000 loan program for SMEs that sparked equal ridicule and praise. 

But TraderMoni is much more; by providing collateral and interest-free microcredit access to Nigerians involved in petty trade, TraderMoni is expected to improve the incomes of the beneficiaries through the scaling up of their businesses. 

Conceived as a five-step loan from an initial ₦10,000 through to a final loan size of ₦100,000, beneficiaries graduate as they successfully repay loans.

Microcredit dates back to at least 1983 with the Nobel Prize-awarded Grameen Bank and now accounts for over 100 million customers and $100 billion in loans globally. 

The good news for Nigeria is that 30 years of experience should give us an idea of whether schemes like TraderMoni work. The bad news is that the evidence is not clear-cut; you could justifiably argue for or against the effectiveness of microcredit schemes in battling poverty.

One notable meta-analysis of microcredit studies published by the World Economic Forum (WEF) in 2015 pooled data from seven studies that incorporated randomised microcredit trials. The WEF found that while microcredit helped households navigate difficult times and didn’t have any systematic harmful effects, it simply, on the average does not lift people out of poverty over both the short and long-term. 

In effect, we can justifiably conclude that microcredit schemes like TraderMoni probably don’t solve poverty.

But why would TraderMoni fail to tackle poverty? 

Well, recipients may just not be good entrepreneurs, and giving them more capital does not change that. Also, some of the credit given could be diverted towards financing consumption. Meaning that even if the loan is eventually repaid, there may be no lasting improvement for that entrepreneur.

Even with the TraderMoni scheme standing on shaky ground, the government is nonetheless committed to running the project. Our focus should then be on getting as much bang as we can for the government’s buck, and one way we can do that is by leveraging on the data generated from TraderMoni.

Spurred on by the ambition to boost financial inclusion in Africa, Fintech companies are trawling through all sorts of user data to develop proxies for traditional credit scores which are missing in Nigeria. 

TraderMoni could play a significant role here as the Federal Government plans to reach two million traders within the next year, giving us a unique opportunity to get data on loan performance across the country. This is a treasure trove from which not only specific inferences can be made about the beneficiaries (user specific), but also broader deductions about that target demographic (population).

Data geeks would recognise that there may be some weaknesses in the dataset, e.g. to make better population inferences, some randomisation should have been built into the allocation of the loans. 

Nonetheless, the data quality here is still likelier to be much higher than what is available to individual startups at the moment, in addition to being at a much larger scale.

How exactly would this work?

The government would need to grant access to the collected data to private parties, possibly in exchange for a fee. One way it could do this is by selling anonymised data for the full loan portfolio to companies interested in population-based inferences. 

By anonymising the data, privacy concerns from the individuals are eliminated, while still allowing companies to progress with applications like new credit scoring models or customer archetypes that can form the basis for new financial products. 

Alternatively, traders can opt to make their data available to financial institutions as part of the process of signing up for new services, e.g. by disclosing their BVN as they graduate from smaller to larger loans.

Partnering with the private sector can produce other benefits. Beyond enabling private firms to create credit-scoring systems to unlock lending in Nigeria, high-quality TraderMoni loans can be securitised (bundled) together and sold to private investors. 

The funds raised from this can either be returned to the government’s coffers—therefore removing the default risk from the government’s account—or reinvested into the scheme in the form of new loans. In all these cases, the ensuing business transactions become part of a multiplier effect from the initial government investment in TraderMoni.

These discussions around disclosing data and securitising loans show the potential even a simple scheme like TraderMoni holds, as long as the government is willing to cede its perceived monopoly over poverty-tackling initiatives and work more with the private sector. 

This type of entrepreneurial state action (in addition to large-scale improvements in infrastructure) will be required for Nigeria to avoid the dismal prediction of being home to the largest number of poor people in the world by 2050.

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