‘There are 400 million people in sub-Saharan Africa that don’t have formal credit files’: Pngme’s Brendan Playford
- Africa is seeing the launch of a lot of new financial services and fintech.
- That provides an opportunity for companies like Pngme to standardize and support financial data sharing.
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2020 was an interesting year for African financial services. We saw Stripe buy Nigeria’s Paystack, its largest acquisition anywhere, and other firms raise significant venture capital.
Pngme is one of the firms contributing to the next stage of growth on the continent. Brendan Playford is founder and CEO of the firm, which offers a unified financial data API for Africa. As financial services mature, the various platforms, networks and institutional ecosystems need a way to standardize and share their customers’ financial data.
Brendan joins us on the podcast to talk about African fintech and what’s been happening there of late. We talk about where the opportunities are and where the market may head over the next few years. Lastly, we drill down into Pngme’s product offering, strategy, and expansion plans.
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The following excerpts were edited for clarity.
We've had Pngme going for around two and a half years, creating individual data profiles in Sub Saharan Africa and more broadly now, to give people better access to finance and allow financial institutions to assess credit risk more intelligently.
The genesis story
I was very fortunate in 2007. With a previous company I had in the UK, I got the opportunity to go out to Tanzania and Kenya to participate in some community biofuel projects. I was in renewables at the time, and was out there for about five years. I met lots of entrepreneurs. Ultimately, with the financial crisis, a lot of the people I was working with became financially constrained. There was a big devaluation of the Kenyan shilling and Tanzania shilling, which put people in some pretty uncomfortable positions, and the community projects that were being built ultimately didn't work out because of the crash of crude oil.
While I was there, I would end up lending short term loans to some of the entrepreneurs and business people I was working with out there. The communities would always get paid back and see really, really positive upside to the financial support or assistance I was able to provide.
Fast forward six years on to 2013. I got into the early blockchain space. I was an early bitcoin miner, and was involved in that first wave of early adopter cryptocurrencies, like Etherium. And when I moved to the US from the UK, I moved here and realized when I landed on the ground that I had no credit score or credit record. I was effectively a credit invisible individual. I've seen similar problems in the countries I've worked in.
So, I built up some experience working in the Valley, in San Francisco. A really big opportunity came around in 2017-2018 to bring together distributed computing technology and some new data science techniques to create alternative financial data profiles for individuals that could be used to assess risk.
Africa has one of the highest densities of mobile money, specifically in Kenya, Nigeria, and Ghana. And that particular data set was really suitable for the models we're building and had a lot of opportunity in greenfields for us to provide a good testbed for the technology we're building.
If you look at the credit invisible space, from a macro perspective, there are two and a half billion people globally that are credit invisible -- in the US, there's 135 million that come into that bracket and in Europe, it's a little bit more. In Sub Saharan Africa, around 6% of the population have credit files.
Specifically in sub Saharan Africa, around 2007, a well known platform called M-Pesa launched in Kenya. M-Pesa is technically this mobile money platform that relies on a channel called USSD, which is an SMS platform to allow individuals to text money to each other with feature phones before smartphones became really prevalent. It went from zero to 27 million users in about three or four years. At its peak, it transacted 80% of Kenya's GDP. That sort of mobile money platform has grown globally to 90 countries and around 270 providers, including MTN Airtel, Vodacom, and many others.
In creating SMS based services, it transacts around a trillion dollars annually and has a billion users. So this mobile money ecosystem has been growing sort of 30 to 35%, year over year. On top of that platform, we've started seeing a huge proliferation of innovative financial products, from savings to loans to peer to peer wallets and things like that, just growing at a crazy rate. Within that space, you've got huge fragmentation. On top of mobile money, you have a lot of data being created. That data is often spread between five or seven accounts on average for an individual. And it's very, very challenging to really get a good deep understanding of what a user's behavior is, from a financial perspective, when you're looking at this type of data. It's really limited the penetration of more sophisticated financial products beyond payments. We're seeing the requirement to build more value-add products on this platform, driving more data driven insights from banks, fintechs, microfinance banks and some of the bigger mobile money operators.
We found this fit early on where we're able to use user-permissioning, like what Plaid does, but from different channels to get aggregate financial data into a user profile or financial identity, and allow that user to share that through our open API with banks, fintechs, or other financial institutions.
Building an African fintech startup in San Francisco
One of the biggest issues we had starting off was that our main core base in San Francisco was a long way away from our markets. And we've overcome that by identifying good talent in the market, including business and sales leaders. One of the biggest challenges is the way the data is structured in Africa, so what we set out to do early on with Pngme is with our API, to provide a Plaid-like experience with all of the data outputs, with a machine learning AI layer of insights on top of it. So taking the raw transactional data when it's been structured, and providing this value add layer of machine learning features, credit features and behavioral characteristics that can just be queried. It removes a lot of the heavy lift on the infrastructure build, and some of your long tail, machine learning features development that can take engineers up to six months to develop for credit models. So we do a lot of that. They vary, but those features can be plugged straight into scorecards.
One of the biggest challenges is when you're looking at the three markets we operate in (and in Q1 2021, we are expanding into Europe and the US to cater for credit invisible people) is the data is completely non-homogeneous. So you're looking at anywhere up to 3000 to 4000 data sources, with anywhere between four to five million data points that all have different structures -- we have very complex machine learning pipelines for our data that use a mix of NLP and various other technologies to extract all of the financial information from our data set and then extract behavioral characteristics. And it ends up being structured as if you would query a user's bank account through Plaid, but it could be coming from mobile money or an agent network, or from some SMS data that we scraped from certain markets. The biggest challenge has been building a platform that scales to the volume of data that we have going through it in a way that's sustainable and can manage and accommodate the growth we've been seeing.
My vantage point over the last eight years led me to believe that data should be self sovereign. It's one of those kind of tenets whereby we live in a world that's been built around technology that monetizes us as the product, like Google and Facebook. The new paradigm has my mind shifting very rapidly -- the next 10 to 15 years are going to be centered around the user being able to opt out of that system and into a system where they own their own data. And they can control, or at least understand, where it's being used and what it's been used for. Obviously, GDPR and other regulations lay a good regulatory foundation for this, but there's still many markets that are a long way behind where GDPR is.
So for us, one of the core parts of our platform is a little bit like Klarna. Klarna does a great job of providing an open banking API for e-commerce and funders. But ultimately, the end user can still kind of manage their profile, see what they purchased. That's analogous to what we do: we have our open API that gives the data to the financial institutions. We sell that data to the financial institution. But the user has an app interface that allows them to control how they use their data, where their data is used, see where their data is used, and get value.
One of the core value propositions we found across our platform was that the consumer wants to understand their finances more, so as they can navigate their way to financial health or wellness using credit, and then later, more sophisticated products to accumulate wealth. The financial institutions want to use that data to identify the best or new customer segments to grow into and expand or increase their bottom line. And really, for us, putting the customer at the center of that creates a lot more transparency.
We believe it's going to open up more efficient markets, and ultimately lead to a world where people create their own data profiles that they can opt in to monetize that. So, in the way that data is monetized for analytics or third party purposes, if a user has a new profile, they may well be able to opt into a program where they can earn some sort of reward or income for their data profile being used elsewhere.
Expanding into Europe
One thing that we've really seen over the last nine months with COVID has been very much this widening of the gap between underserved individuals who struggle to access finance and the capital that's flowing into the economy to alleviate liquidity constraints. The money printers are wearing away injecting stimulus now. Within that ecosystem, there is a layer of individuals that are unable to access credit through that, and the demand for credit products in that segment is incredibly high.
I cannot understate the demand there: it's pretty obvious that there is a large swath of capital that is on the sidelines looking to be deployed and get yield. We bridge that gap between that capital and the individual by making that risk transparent and it may well be, for example, from my perspective, I'm still credit invisible in the US. I still couldn't go and get a mortgage because I don't really have the right credit age. I'm not sort of up in that six to seven year credit age bracket and I don't have an established credit holder to add me to their credit card here as an adult.
We're seeing a lot of inbound interest from financial institutions in Canada, the US and Europe, looking to try and figure out ways that they can serve this segment.
We're in this phase at the moment where we've just started working with quite a few significant banks and a couple of global credit bureaus focused on Africa. But we really see those opportunities growing into a global footprint over the next 12 months. So leap frogging out of these markets into secondary markets, where some of our banks and customers at the moment, including these larger credit bureaus, operate. We see that as a really, really interesting opportunity for scale.
On the technology side, we're processing around 10 to 15 million data points a week at the moment. We expect to see that scale pretty exponentially, which is going to lead to the creation of some really interesting technology, which we're pretty excited about, especially on the distributed computing side.
One thing that's really developing and evolving in the blockchain space right now is decentralized finance. You see early grassroots movement for DeFi. We see there's a big opportunity to cater to the DeFi space, where at the moment, most of the lending there uses collateral, like a cryptocurrency asset. There's this notion of being under-collateralized in the space and we see a very strong fit with our platform, where we'll be able to provide both KYC and transparency and ID information plus risk assessment for these DeFi platforms. This should lead to a massive opening up of that space, a really big opening up of yield and opportunity for accessing credit.
So, for us, the next year is about scaling our technology, looking forward to what would be our Series A in the new year. And then more broadly, really rolling out our services to other other verticals where we can continue to serve this large segment of credit invisible, underserved individuals and give them more information. Our brand narrative is helping people navigate their way to financial wellness or financial success, and really driving that forward with as many opportunities to access the best credit or best financial products possible.