Flora Oladipupo
AI Researcher
Lagos, Nigeria
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Flora Oladipupo is a tech enthusiast passionate about driving inclusivity and innovation in artificial intelligence and data science. She has cultivated expertise across multiple areas, including Data Analytics, Natural Language Processing (NLP), Machine Learning, and Artificial Intelligence, with a focus on creating impactful solutions that cater to low-resource languages and underrepresented communities. Aside her technical side of professionalism she is also a community manager in the Microsoft Learn Student Ambassador community, Women TechMakers (WTM) Community where she is passionate about teaching and mentoring others in the field of AI serving as an AI advocate.
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Leveraging AI for Financial Inclusion amongst Low-Resourced Language Speakers in Africa
This is a lightning talk to create awareness on the use of AI for Financial Inclusion in Africa
AI's effectiveness is rooted in data, and it promises lasting solutions to everyday problems. However, if the data used isn't tailored to specific groups, these solutions may not be accessible or inclusive. This shows the importance of developing AI solutions for speakers of low-resourced languages, particularly in Africa.
Focusing on the business and financial domain, AI offers numerous ways to bridge the financial inclusion gap, specifically finding application in providing financial advice and scam mitigation in this space. In Nigeria, speakers of local dialects often miss out on crucial financial information, as such messages are typically tailored for English speakers. This leaves out individuals whose primary languages are Yoruba, Hausa, Igbo, etc.
This talk aims to shed light on AI models that can be used to build these solution i.e GPT models, Llama-model, Mistral model etc which have originally been built for high-resourced languages but can be fine-tuned on these low-resource languages for further downstream application like that of the Financial inclusion.
AI can bridge these gaps by use of large language model (LLM)-powered chatbots capable of answering questions in local dialects. This means an average local dialect speaker could use their device to seek financial advice on managing their money. Imagine a scenario where a market seller who speaks only yoruba brings out her device to consult the bot on how she should invest her money into her business and the response is also in her local dialect. Additionally, LLMs can offer real-time responses to fraudulent messages or calls, protecting these individuals from scammers.
By raising awareness of AI's potential in Africa, data-driven solution providers can collaborate to create impactful solutions in the financial and business domains. These solutions helps to bridge the gap and disparity existing between AI and Finance in Africa.
Credit Risk Assessment using Power BI
This session shows how the Power BI Key Influencer chart can show the factors that drive metrics. This can be used in an assessment to predict credit risk for potential credit loans without building a Machine Learning model from scratch.
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