Wysemarket CEO on why prediction markets could change how Africa understands collective expectations

Prediction markets are gaining attention as a way to capture what people collectively expect to happen, from politics and economics to sports, entertainment, and technology. As platforms such as Kalshi and Polymarket see growing global activity, the model is also beginning to take shape in Africa.

Nigeria-based Wysemarket is among the platforms building around this opportunity, allowing users to make predictions on outcomes across entertainment, politics, sports, culture and other areas.

In this interview, Oluwafemi Laniyan, CEO and Co-Founder of Wysemarket, discusses why prediction markets are becoming increasingly relevant, how they can complement traditional research and what their emergence could mean for Africa’s growing digital information economy.

Why are prediction markets becoming increasingly relevant at this point?

We are living in an environment where information moves faster than ever, and expectations can change almost as quickly. A development in politics, a product announcement, a sporting event or a cultural moment can change what people expect to happen within hours.

Prediction markets provide a way to capture some of those changing expectations in real time. Instead of only asking what people think at a particular moment, they create a mechanism for observing how expectations change as new information emerges.

What does this add to the way businesses and researchers already gather information?

Prediction markets should not be viewed as a replacement for traditional research. They can complement it.

Surveys and polls are useful for understanding what people think at a particular point in time. Prediction markets can provide a continuously changing view of what people expect to happen. That distinction becomes important when you are dealing with questions where new information can quickly change the outlook.

For businesses and researchers, the opportunity is to consider market expectations alongside surveys, social listening, historical data and other forms of research.

There is growing research around the ability of prediction markets to aggregate information. Why is that important?

People have information that is often distributed across different places and communities. One person may understand a particular industry, another may have deep knowledge of a cultural trend, while someone else may be following a political or economic development very closely.

Prediction markets provide a mechanism for some of that dispersed knowledge to come together. The resulting market signal does not mean the market is always right, but it can provide another perspective on how informed participants collectively view an uncertain outcome.

Why do you think this model has particular relevance for Africa?

Africa is home to the world’s most digitally native and adaptive population. People across the continent are already deeply engaged in conversations about politics, sports, entertainment, business, technology and culture.

By launching Wysemarket, we aren’t just giving users a platform to forecast; we are giving them a stake in the future.
The opportunity is to build around the behaviours and conversations that already exist rather than simply replicating platforms built for other markets.

What does that opportunity look like in everyday life?

Every day, people are making predictions. They debate which artist will have the biggest song, which team will win an important match, whether a particular policy will be implemented or what could happen to the economy.

Those conversations happen in group chats, on social media, in offices and in communities. They represent a form of collective knowledge, but much of it remains fragmented.

Prediction markets can provide a structure for turning some of those expectations into measurable signals.

You have described collective intuition as a data asset. What does that mean?

Our goal is to turn collective intuition into a valuable data asset that empowers individuals and informs markets across the continent.

The important point is that people are not simply making random guesses. In many cases, their predictions are informed by what they know, what they have observed and the information available to them.

When you bring those individual perspectives together in a structured market, you can begin to see how collective expectations form and how they change over time.

Could this eventually become useful to businesses beyond the people participating in the markets?

There is certainly potential for that. Businesses are constantly trying to understand what consumers, markets and communities expect to happen next.

Imagine a company tracking an emerging cultural trend. It could look at consumer research, social conversations and other conventional data, while also considering what a prediction market is showing about expectations around that trend.

The value is not in replacing one source with another. It is in bringing different signals together to build a clearer picture.

How important is the quality of the market itself to the information it produces?

It is extremely important. The quality of a prediction market depends on the quality and diversity of participation, the clarity of the questions being asked, the availability of information and the overall design of the market.

A market with limited participation may not produce a strong signal. That is why prediction-market information should be treated as another source of evidence rather than an unquestionable forecast.

The objective is to create markets where people have good reasons to participate, where outcomes can be clearly verified and where the information generated is meaningful.

What does building a prediction market specifically for African audiences allow you to do differently?

It allows us to ask questions that are relevant to the people who live here.

Africa has its own cultural moments, political developments, economic questions, sporting events and entertainment trends. These are things people already care about and have opinions on.

The opportunity is to create a platform where those expectations can be expressed and measured within an African context, while also building a product that reflects how people on the continent interact with digital services.

Where do you see prediction markets fitting into Africa’s broader technology ecosystem?

Femi Laniyan: African technology has done a lot to solve practical problems around payments, commerce, mobility and financial access. There is another opportunity emerging around information.

As more Africans participate in digital platforms, they are generating an enormous amount of knowledge, opinions and expectations. The next layer of technology could be about organising some of that information and making it more useful.

Prediction markets can be part of that evolution. The bigger opportunity is understanding what people collectively expect, how those expectations change and what that information can tell us about the future.

What do you think will ultimately determine whether prediction markets become an important part of that information economy?

It will come down to whether these markets can consistently produce useful information. That requires credible outcomes, informed participation, good market design and the ability to show that the signals generated have value beyond the prediction itself.

For Africa, there is an opportunity to build this around questions that are genuinely relevant to the continent and its people.

If we can turn the conversations people are already having into structured information, prediction markets can become more than a way of forecasting outcomes. They can become another way of understanding how people see the future.