By Christmas this year Ugandans will have placed over 5.5 trillion shillings in bets on everything from football games to whatever is on offer. This figure will rise to over 10 trillion in the next half-decade according to Denis Ngabirano the CEO of the Gaming and Lotteries Board. Last financial year ending June 2024, the figure was 4.2 trillion.
This is an astounding amount, but it points to how automation and algorithms can have an outsize effect on society. The leap in gambling numbers is a triumph of the technology that the lotteries authority is applying to monitoring bets but also the bespoke technologies that betting companies are increasingly relying on to enhance their offers. The government of Uganda happily takes 30% of this kitty in taxes but money really is not at issue here even if these figures pale in comparison to what the government in placing in management as agriculture funds within parishes around the country. The spread of algorithms across society is a window into the lives of Ugandans in a way that has no comparison in history. Moreover, that these algorithms that sit on the nearly 20 million phones are revealing suggest in some cases that we should revisit some of our assumptions about society and progress as we know it. One fact is that information on mobile phones, tablets and computers have virtually obliterated informality. The idea that the economy is made up of visible (formal and documented) parts and a hidden (and for some government planners) unfathomable parts is probably ancient history. Sitting on these phones and pegged to National IDs is gigabytes of information that curates the lives, work and entertainment of nearly half the population more than enough information to get under the skin of society. One of the revelations to be taken seriously aside from the spillover of money into the gambling sector is that certain values like trust, discipline are far more evident and run against the rhetoric that most Ugandans are lazy and untrustworthy.
Artificial intelligence and machine learning helped MTN Uganda to pioneer a successful model of unsecured lending the impact of which is yet to be determined. What is clear however is microloans borrowed from MTNs fintech startup MoMo Uganda and similar services by Airtel easily outmatch over the counter loans by traditional Banks combined. In interviews MTN officials credit the success of MoCash to computer modeling that assigns a personal credit score to an individual often based on an analysis of their history going back several years. The artificial intelligence tools use a wide and deep parameter of over 200 metrics including for example the individual’s device history, device type, geo-locations that reveal movement, app use that reveal preferences and mobile money history that indicates their income and expenditure. “Banks use just 10 parameters for example” said one official who added that the conventional wisdom that Ugandans don’t pay when they borrow was rendered obsolete by the model.
Today the MoMo company posts transactions of over UGX 5.6 billion daily and thus is the biggest single indicator of responsible borrowing where traditional lenders have often depicted borrowers as untrustworthy. Repayment rates are over 92% officials say some products have a default rate of just 2% or in other words a repayment profile of nearly 100%. The scale of this impact has not been properly quantified, but one take is that out of its 200 thousand agents, each supports 3 homes and that is just a tip. When the full ecosystem of MoCash and its sister products (almost 14 billion daily transactions) is analyzed, its impact on social welfare and the economy may yet tell us things about society that are essential to how life is lived alongside algorithms. On the subject of responsible borrowing for example it is saying here that trust and accountability in society is high under certain conditions. A MoCash user gets instant responses, has an individual relationship with their habits (credit limits rise with consistent payback) and there is freedom in how to execute one’s obligations. The data also confirms some truths powerfully; women are better borrowers and make up 70% of customers out of a loan book of UGX 30 billion with the average token size being 100,000.
In time MTN hopes to provide this treasure trove of data (anonymized) to businesses and government, which while it licenses and regulates the use of mobile phones and the internet, may not have insight into the intense bloodstream of data that minute by minute, hour by hour relentlessly builds a picture of what society. One can learn more about social support directly by observing in detail one’s connectivity, social media activity and mobile money history. That data is available now.
The average Ugandan whether wealthy or not exists in a compassion economy which is normatively well defined. Weddings, funerals, health crises, birthdays, school fees, bail money or just transport money are shared offerings transacted daily on the phone. Indeed, the healthcare industry would not survive without the social architecture that now thrives on the phone. Thus, the billions of shillings spent every year for medical care that are out of pocket costs often pooled by relatives and friends is digitally disbursed. Indeed, we can look closely about what algorithms are saying on how to solve some major problems and build new companies and wealth in this new era.
