Local Chapter Addis Ababa, Ethiopia Chapter
Coordinated byEthiopia ,
Status: Completed
Project Duration: 17 Aug 2023 - 17 Sep 2023
Open Source resources available from this project
Project background.
Financial decision-making can be overwhelming and challenging, especially for individuals who lack financial literacy. The lack of knowledge and resources can lead to poor financial choices, resulting in debt, bankruptcy, and financial instability. With the rise of digital banking and finance, there is an opportunity to leverage AI to provide personalized recommendations to individuals to make informed financial decisions.
The problem.
With the vast amount of financial products and services available in the market, individuals find it challenging to navigate and choose the right ones to meet their financial goals. Moreover, the financial industry is often seen as complex and intimidating, making it challenging for individuals to make informed decisions. The AI chatbot will provide personalized recommendations to individuals based on their financial goals and preferences, making it easier to make informed financial decisions.
Project goals.
Project plan.
Week 1
Thorough analysis of financial products and services, research existing Fintech AI chatbot frameworks, and definition of scope objectives and success criteria and focus on gathering a diverse and relevant dataset for training the chatbot. The dataset should cover a wide range of potential user queries and responses.
Week 2
Set up development environment and tools, design conversational flow of chatbot and UI and It is important to ensure the dataset is properly cleaned and formatted to remove any inconsistencies or biases and analyze and visualize the dataset to extract valuable insights
Week 3
Once the dataset is ready, the next step is to train the chatbot model using machine learning techniques. This involves selecting an appropriate algorithm or model architecture and feeding the prepared dataset into it. The trained model should then be evaluated using various metrics to assess its performance and make necessary improvements.
Week 4
After the model is trained and evaluated, it needs to be integrated into a chatbot framework or platform. Deploy the chatbot to a production environment where users can interact with it. then Optimize chatbot’s user experience
Learning outcomes.
1. Learn NLP and chatbot design and implementation
2. Gain knowledge of financial products and services
3. Develop problem-solving skills
4. Learn about designing ML algorithms and conversational design
5. Learn about data analysis and visualization
