There is a line from this podcast session that has stayed with me since we recorded it earlier this week. Yannick Lefang was explaining why he was never in a hurry to build Kasi Insight fast.

“Data is like wine,” he said. “The older it gets, the better, the more expensive it is.”

He meant it as a competitive strategy. But it is also, I think, a philosophy — and it explains almost everything about how Kasi Insight has been built over the past nine years and why it is genuinely difficult to replicate.

Yannick Lefang is the Founder and CEO of Kasi Insight, and he is, without question, one of the most unusual founder stories I have encountered in the African technology ecosystem. Born in France. Raised in Cameroon. Educated in Canada as an electrical engineer. Over a decade spent in financial risk management at TD Bank, one of North America’s largest institutions. A seven-month advisory engagement with the IFC working with banks across East, Southern, and West Africa. Then, in 2017, he decided to build something Africa had never had: a high-frequency, pan-continental consumer intelligence platform.

The result is a company that now tracks consumer sentiment, brand performance, economic signals, and retail dynamics across 21 African markets, conducting over 120,000 interviews annually and generating 80 million data points. The Kasi Index of Consumer Sentiment is distributed on Bloomberg and Refinitiv — making it one of the very few Africa-originated economic indicators to sit alongside global financial data at that scale. Think about that for a second. It’s a really big deal!

The Grandfather Who Taught Him Everything That Matters

Every great entrepreneur has a formation story. Yannick’s involves a grandfather who never went to high school, ran a farm, a hardware store, and a retail shop in a small Cameroonian town — and who started putting a twelve-year-old Yannick to work every school holiday.

“From the age of 12,” Yannick told me, “I’ve been running businesses. My grandfather would pick me up after school, bring me to his shop. Eventually he started paying me. Eventually I started running one of the stores when he was travelling.”

The man learned Italian from priests who came into the shop. He once flew unannounced to Switzerland to visit family — a gesture his grandchildren still cannot quite believe. He walked from his home province to another as a young man. He told Yannick’s parents, when they worried about him moving to Canada, that Canada was closer than that walk had been.

“I still don’t believe I’m more intelligent than my grandfather,” Yannick said. “Yet he did not even go to high school. But he understood from observation.”

That observation-first mindset — watching behaviour, spotting patterns, acting on what the data is actually telling you — is, Yannick will tell you, exactly what Kasi Insight is built on. The connection is more than rhetorical. It is the founding logic.

From Medical School Expulsion to Electrical Engineering to Financial Risk

Yannick was not supposed to be an engineer. He was admitted to the Faculty of Medicine at the University of Benin. He lasted three months before a political dispute led to him and another Cameroonian student being expelled — for reasons, he told me with characteristic dryness, “that had nothing to do with me.”

Engineering became the second option. He then moved to Canada, to the University of Ottawa, where he would eventually graduate cum laude, he discovered that engineering and problem-solving were a better fit anyway. “Engineering is about teaching you how to solve problems,” he said. “Deconstructing, reconstructing, being systematic about it.”

His first job out of university was at Nortel — which, as every technology person of a certain age will remember, collapsed almost overnight. That collapse, and a friend’s tip about the demand for quantitative engineers in banks during the height of the credit derivatives boom, pushed him toward finance. He arrived in Toronto with roughly two months’ rent, applied for one job, and got it within two weeks. Every subsequent role came from business cards he collected at a single industry event.

At TD Bank, he rose from valuation analyst to enterprise market risk manager over a decade. His most vivid memory from those years: joining a new team and discovering — two weeks in — that his group was at the centre of a USD 100 million write-down linked to Lehman Brothers. He spent 36 hours at his desk without leaving, reconciling positions across CDOs and CLOs to prove to the market that the exposure was contained. “Those were probably the best one and a half years of my career in banking,” he told me. “The intellectual challenge. The products. Banking used to be fun.”

The Founding Logic: Africa Was Driving Blind

The International Finance Corporation (IFC) advisory role brought Yannick to Africa for the first time in a professional capacity. What he found was a continent making major financial and economic decisions with almost no real-time feedback loop.

“I spent my career in banking with Bloomberg terminals, Reuters, data sources,” he said. “I’m sitting there and thinking: if you’re a central banker in Africa, what data do you actually have? You’re driving blind.”

The original idea was an inflation tracking basket — he sent his brothers to market every weekend with product lists, manually compiled data, and built indices for Cameroon. A professor told him each product needed at least 100 observations to be statistically valid. He did the math, realised it was not viable, and pivoted to survey data. A mentor pushed him to formally incorporate the company.

He did all of this while still at TD Bank — evenings and weekends. Cameroon was the starting point, but it proved logistically brutal. Then, over lunch, a Kenyan colleague suggested he speak to her cousin in Nairobi. That cousin became his partner. Kenya changed everything.

“The speed at which we were able to do things here kind of blew my mind,” Yannick said. “The quality of the talent. It was the first time for me to realise that Africa was bigger than Cameroon.”

When COVID Hit, Kasi Was Already Tracking It

One of the most striking moments in our conversation was Yannick’s account of how Kasi Insight experienced the COVID-19 pandemic.

Because Kasi tracks the consumer sentiment index on a monthly basis, the team saw the signal in December 2019 — before the pandemic was declared, before the first African case was reported. The index started dropping. “We asked ourselves: is the pandemic, which at that point was a Chinese issue, impacting Africans? We looked at it as an opportunity for African brands to capture.”

Three months later, it was a global pandemic. Kasi was already doing weekly webinars on African consumer data, positioning itself as the data signal in a moment of enormous uncertainty. Yannick was in South Africa recently when two strangers at a CMO breakfast saw his badge, recognized the name, and said: “Kasi — from COVID. I was watching the webinar every day.”

That, he said, proved something he already believed: data creates confidence in markets. “If you look at the US stock market, it goes up and down — but people still invest, because they have visibility. That visibility is the data.”

The Platform Built Because Tableau Was Too Expensive

Some of the best product decisions in history have been made not by ambition but by constraints. Kasi’s analytics platform is one of them.

Yannick looked at Power BI. He looked at Tableau — which would have cost him thousands of dollars per user before he had made a single dollar. “There’s no way that’s going to work,” he told himself. So he built his own — open source, owned entirely by Kasi, specifically architected for the challenge of building historical survey data series rather than transaction data. “When I show it to people, they’re like — I’ve never seen something like that. Because it was uniquely built for our unique challenges in Africa.”

He also built the data collection infrastructure from the ground up. Over 1,500 people on the ground monthly, incentivized across every market, conducting surveys that are not online-only — because this is Africa, and assuming digital-only access is how you get data that doesn’t reflect reality. Quality checks at every stage. Country by country, market by market, year by year.

“Think about Safaricom,” he said. “Michael Joseph went and built those towers bit by bit. That’s why today you have to follow them. There’s no magic. There’s no shortcut.”

The Research That Should Be On Every CRO’s Desk

Kasi’s latest research — “When Consumers Whisper, Credit Markets Listen” — demonstrates something that should fundamentally shift how banks and financial institutions in Kenya think about credit risk management.

The Kasi Index of Consumer Sentiment leads changes in Kenya’s non-performing loan ratio by one to three quarters, with the strongest predictive correlation at a three-quarter lag. When consumer confidence falls, NPLs follow — the question is only when, not whether. The divergence that has opened up since 2021 — Kenyan banks reporting near-record profits of approximately KSh 82 billion while consumer financial health deteriorates — is a warning sign, not a success story.

Yannick was direct about what this means for investors: “One of our indices is also predicting returns on the JSE in Johannesburg. I can look at consumer sentiment and predict NPLs. I can position myself right.”

That is not market research. That is financial intelligence at the level you would expect from a mature capital market information provider. The fact that it is being produced from Nairobi, for Africa, by an African-founded company — is, frankly, remarkable.

The Bloomberg of Africa — and Why He Is Not in a Hurry

I asked Yannick where he sees Kasi Insight in five to ten years. His answer was immediate.

“We have the opportunity to become the Bloomberg of the continent.”

Bloomberg is a data company with a distribution and media layer on top. Kasi has the data. It has a growing distribution relationship with Bloomberg and Refinitiv. What sits between here and there is a matter of product and time — and Yannick is comfortable with both.

“The companies that would pay us a million dollars to do what we do are not yet born,” he said. “These young people building businesses today are going to be the ones who need this. I’m building the foundation.”

He has never raised institutional money. He built the entire company, initially, from his own salary — he estimates around $10,000 to start. “The notion that we need capital to build companies on the African continent is wrong. You can start with what you have.”

His advice for young people was characteristically grounded. Go spend a day with the women selling food to construction workers. Understand their businesses. “What you’re going to find will blow your mind and change the way you look at these women and the opportunities on the continent.” The real Africa, he said, is not the Africa that makes it into the headline indices. It is the informal market, the street-level entrepreneur, the observation-led businessperson — the people who remind him of his grandfather.

What I Took Away

I have been saying for years that Africa’s biggest problem is not a shortage of talent, capital, or ideas. It is a shortage of decision-quality information — the kind of real-time, structured, validated intelligence that decision-makers in mature markets take for granted.

What Yannick Lefang has spent nine years building is exactly that. Nine years of primary data across 21 markets that cannot be recreated at any price. A platform built from constraint and owned entirely. A research capability that is beginning to shift how banks think about credit risk. An ambition — Bloomberg of the continent — that is large but not irrational.

He told me early in our conversation that when you want to know what you should be doing with your life, you should ask yourself: if you had a magic stick and could do anything, what would you do? His answer, sitting at a TD Bank trading desk with 10 years of risk management experience and a view of Africa with no reliable consumer data — was clear. He went and built it.

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