How African fintech startups can leverage artificial intelligence in their operations

This time last year, Web3 and Blockchain were all the rage and if you didn’t know, you were seen as missing out. Never mind that the use cases weren’t that defined.

Fast forward a year and AI is the new kid on the block. At every turn, you’re bombarded with tweets from people promising you’ll be out of business if you don’t get on the AI ​​train. Not even escaping to LinkedIn offers respite.

Unlike web3 and its siblings, AI has clear use cases and some of its applications have significant potential. My colleague, Bolu, recently wrote an article about AI’s potential uses. Today I explore some applications of AI in the fintech space, its drawbacks and challenges.

What is artificial intelligence?

I would set the scene by attempting a definition of artificial intelligence using the poster child ChatGPT. According to ChatGPT, artificial intelligence (AI) is the ability of machines to perform tasks that typically require human intelligence, such as recognizing speech, making decisions, and solving problems.

AI can do this because it is fed data that helps it detect and analyze patterns. As I mentioned earlier, AI can be used in literally any field to identify patterns and make decisions. For example, an AI chatbot can act as a robo-advisor, helping individuals decide which asset to invest in.

How can African fintech startups use artificial intelligence?

The first question I had after thinking about possible applications of AI in fintech was whether any startups were already working on artificial intelligence. Africans tend to be on the consuming side of such innovations, but luckily there are a few startups already using AI to figure out things like credit scoring and fraud detection.

Victor Irechukwu, Head of Engineering at OnePipe confirmed this and says that OnePipe already uses artificial intelligence for fraud detection and prevention and biometric verification for its customer KYC implementation. It also uses natural language processing for conversational transactions.

So how can artificial intelligence be used in fintech? Irechukwu identifies five main areas fintechs can explore – biometric verification, compliance and regulatory reporting, customer acquisition and retention, credit scoring and risk assessment, and finally, fraud detection and prevention.

Babatunde Akin-Moses, CEO of fintech startup, Sycamore adds two areas – personal marketing and securities trading.

The five areas mentioned by Irechukwu are major headaches for any fintech startup. Take, for example, credit scoring and risk assessment. Nigeria has low credit penetration and despite the best efforts of fintech startups, many Nigerians still do not have access to credit.

According to Irechukwu, AI can analyze customers’ data to evaluate creditworthiness and assess risk, which can help lenders make more accurate decisions and reduce the risk of default.

On the other hand, fraud detection and prevention can do with AI’s help. In March 2023, Techpoint Africa reported that Flutterwave had lost huge sums in a hack. Reports have since emerged showing that fintech startups are working on a fraud prevention model.

A recent report by Kaspersky also claims that 37% of Nigerians have lost money while using online banking channels. AI can help identify and prevent these fraudulent activities.

What challenges will fintech startups face when using artificial intelligence?

It is easy to understand that using AI can solve all the problems that fintech startups are currently facing, but that is not the case. There are a few challenges that come with the territory, with access to data, a challenge mentioned by all the experts I spoke to.

Yvonne-Faith Elaigwu, operations manager at OnePipe explains that access to data can be a big challenge for fintech startups and shared an experience with a fintech startup she worked with previously.

“You have to feed the model enough data so it can identify patterns and make decisions. I remember working with a company a few years ago that was trying to use artificial intelligence to help lenders make lending decisions.

“The biggest obstacle was access to data because many people did not have a sufficient financial ‘digital footprint’ from which to draw information. Hopefully, the spread of fintechs working to bank the unbanked and underbanked across Africa will somehow solve this problem with access to data.”

We have a running joke Techpoint Africa editorial about the challenges of finding data, but more importantly, finding accurate data. Irechukwu substantiates Elaigwu’s point.

“AI models require large amounts of high-quality data to be effective. In the fintech area, there can be challenges in accessing quality and managing this data considering that AI models are only as good as the data they are trained on, he says.

He adds that fintech startups will also have to contend with regulatory considerations when deciding how to use AI in their operations, while being able to explain how it works to the relevant stakeholders.

So far, African startups have not taken the lead in AI, but since these are still early days, there is a chance that they could play a big role going forward. “While we may not be at the forefront of developing the technology itself, we can certainly find creative uses for it. As with most technologies, it is those who find the most practical and useful applications that win the market. Not necessarily those who develop the underlying technologies. I would say that African fintechs can certainly take part in the conversation in a very meaningful way,” says Akin-Moses.