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Two billion people in the world, most of whom live in emerging markets, do not have access to credit. They are excluded from financial systems because they have limited or no credit history. South African startup, Omnisient, which specialises in secure data sharing for businesses, wants to bring this section of the population into the economy by leveraging AI and alternative data like retailers’ rewards programs. A Financial Inclusion study by TransUnion showed that 20 million South African consumers were credit unserved and a further 7 million underserved. Omnisient was recently named one of the World Economic Forum’s 2023 Tech Pioneers. Co-founder and CEO of Omnisient Jon Jacobson told BizNews that with alternative data, banks can predict the likelihood of defaults and increase sales by 30%. He said this is a win-win situation for everyone involved: the retailer, the person who could never get credit, and the credit economy. – Linda van Tilburg
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Excerpts from the interview
Building a platform that addresses the challenge of data sharing while preserving privacy
Omnisient helps businesses to collaborate on data. Why aren’t they doing that anyway? The reason they’re not and really struggle is privacy. Privacy legislation kind of inhibits the way businesses move data around and share data. So, what we did was we built a platform that solves all the fundamental issues around privacy in terms of anonymisation, and personal information, protects businesses, and intellectual property, and then also protects them from hacking and breaching. You can think of us as a data analytics business. So, there are some key things that we solve by using those principles and one of them is financial inclusion. That’s why we’ve been included in the summer Davos event and the 2023 technology pioneers because what we are doing with our retail partners and our banking partners is managing to solve financial inclusion, especially access to credit, creditworthiness and solve that at scale by using other data, telco data, shopper data to build predictive credit risk scores. So, there’s an element of us that’s privacy and cryptography, there’s an element of research data, and there’s an element of us that’s AI and that’s all packaged into one platform.
Using alternative data to give ‘thin file’ individuals access to credit
A country like South Africa, it’s a fairly sophisticated credit economy. The credit bureaus globally determine whether somebody is right to get credit or not. In their world, they have two kinds of people, there are thick file and thin file and that’s just an old term from the days when there weren’t computers. A thick file means that there are loads of pages in the file, which tells you that we got enough information for a credit decision. For most emerging markets, I think it’s close to 2 billion people globally who don’t have access to credit. They would largely be considered financially excluded. They would either be a thin file or there just would be no data on them whatsoever. Then the problem becomes, how do you keep those people in the credit economy when there’s no data? This is normally the historical disadvantage and in a country like South Africa, it goes way, way back.
Enabling credit access for 8 million people South Africans through AI and alternative data
So, people in the South African economy in previously disadvantaged communities would have something like a stokvel that they would run with and that is based on the trust of a very close group of people that know each other well, normally from the same village or area and there’s no interest involved. But it’s a lending system and creates kind of a discipline in the way that money gets spent. But there isn’t access into this other world and if you could tap into that other world which is the credit economy, not in the way that payday lenders do it, which is 50% interest rates on top of a small loan, but through the banks. The banks are heavily regulated and so the interest rate you’re going to get from a bank is going to be a lot better. But the bank is very, very rigorous around credit and offering credit. They would normally offer credit to the thick files. When we bring alternative data into play, for instance, in a retailer’s rewards program and if that retailer is serving low-income people, we’ve already shown there are roughly 8 million additional people in the South African economy who could be offered credit.
Sponsoring education, private sector is better at solving problems
A business is about karma. So, you kind of have to give and take and we do it because the private sector, especially in a country like South Africa is probably better placed to solve some of the problems the country experiences. You don’t have to do that at a massive scale, but if I can put 17 or 34 or 51 kids through education because education is at the root of solving most of the world’s problems and if another business does that, we don’t need the government’s education department to figure this out. The systems are there, the schools are there, the model- C school systems are there and are very, very strong. But in the one school that we are sponsoring, when I spoke to the headmaster, R 4.5 million of fees are not getting paid because the parents can’t afford it, then the school has to figure out what to do. They don’t want to pull the kids out of school and some of these kids are performing incredibly, very strong in STEM or very strong in drama or something else. They are talented kids.
Part of what we’re doing is giving back. We’ve set up a bursary fund to sponsor kids and at this stage, we are sponsoring 17 kids for education at one of the model-C schools. We are very, very keen to grow that fund.
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