Creating a Personal Financial Advisory System Through NLP

Start Date: August 17, 2023 | 3 years ago

Challenge 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.

Goal of the Project

The project goals are:

To provide personalized financial recommendations to individuals.
Improve financial literacy and decision-making skills.
Foster transparency and trust in the financial industry.
Enhance user experience and engagement on finance.

Project Timeline

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.

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

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.

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

What you'll learn

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

First Omdena Local Chapter Project?

Beginner-friendly, but also welcomes experts

Education-focused

Duration: 4 to 8 weeks

Open-source

Your Benefits

Address a significant real-world problem with your skills

Build your project portfolio

Access paid projects (as an Omdena Top Talent)

Get hired at top organizations

Requirements

Good English

Suitable for AI/ Data Science beginners but also more senior collaborators

Learning mindset

Application Form

Application Closed.