Africa’s fintech landscape in Africa has experienced remarkable growth in recent years. Despite a significant number of citizens still lacking bank accounts, concerted efforts from companies, government entities, and industry stakeholders have aimed to bridge the gap.
Kenya’s M-Pesa serves as a prime example, initially targeting the unbanked with mobile money services and now offering extended features like purchasing goods with data balances and credit facilities. Despite progress, there’s more work to be done for long-term sustainability.
In a collaborative effort, pan-African payment infrastructure company Kora and fintech news platform Finextra released a report highlighting insights from industry experts on Africa’s fintech ecosystem. The report emphasizes that substantial investments in groundbreaking technologies, particularly AI, will facilitate genuine financial inclusion and positively impact the continent’s economy.
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AI’s Crucial Role in Africa’s Fintech Landscape
AI’s transformative potential is widely acknowledged, and several countries, including South Africa (736 companies), Nigeria (456 companies), and Egypt (246 companies), are focusing on AI development.
Within fintech, AI can enhance customer service for retention and acquisition purposes. Implementing conversational chatbots, for instance, can streamline customer support, freeing human agents to handle more complex issues. AI can also assess creditworthiness, reducing loan default risks. However, AI usage must be accompanied by strict data privacy compliance and regulation adherence.
The report highlights that governments should take an active role in AI regulation to foster growth while safeguarding national interests.
About AI
Artificial intelligence (AI) refers to the capacity of digital computers or computer-controlled robots to execute tasks commonly linked with intelligent beings. This term is often used to describe the endeavor of creating systems equipped with human-like cognitive processes, including reasoning, comprehension, generalization, and learning from past experiences.
Since the emergence of digital computers in the 1940s, it has been proven that computers can be programmed to accomplish intricate tasks, like proving mathematical theorems or excelling in chess. Nevertheless, despite advancements in computer speed and memory, no programs have achieved the full scope of human adaptability or handling tasks reliant on extensive everyday knowledge.
However, specific programs have reached the proficiency levels of human experts in certain tasks, resulting in AI applications such as medical diagnosis, search engines, voice/handwriting recognition, and chatbots.
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