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Open FinAL will become an AI-empowered open-source financial adaptive learning tool designed for learners by learners to provide financial analytics capabilities at a low cost. The tool will provide students and retail investors (i.e., individual investors) with an adaptive learning experience where they can learn and explore investment concepts and financial analytics tools, beginning with a simple set of learning modules and tools and gradually progressing toward more complex modules and advanced tools. The software and learning modules will adapt to the users knowledge, investment goals, and risk preferences.
The following is a more comprehensive version of the product vision
Open FinAL is governed by two roadmaps. The product roadmap governs the priority in which product features will be built. Please follow this roadmap. If you would like to see other features not listed on the roadmap, please see the section below. The ecosystem management roadmap governs how management of the open-source ecosystem around the product will be implemented. These two 5-year roadmaps are based on customer discovery data and should not be altered without further customer discovery that validates new directions of the product.
To contribute feature ideas or to see other's ideas for features, please see the Issues section of this repository. Your ideas are welcome and will be considered for future roadmap updates. Please tag your feature ideas as "enhancements" so they are easy to find. Roadmap features are selected through customer discovery activities to ensure that the roadmap stays well-aligned with users' needs.
Open FinAL is developed by students through class or extra-curricular projects. The surrounding ecosystem is also managed by students through projects. If you are contributing to Open FinAL, please see the Project Startup Guide.
Students should also carefully follow the Project Termination Guide to ensure that project startup for the next group of students is smooth.
This software is provided "as is" without any warranty of any kind, express or implied. This includes, but is not limited to, the warranties of merchantability, fitness for a particular purpose, and non-infringement.
The authors and copyright holders of this software disclaim all liability for any damages, including incidental, consequential, special, or indirect damages, arising from the use or inability to use this software.
The authors of this software are not financial experts. This software should not be used to replace the expert advice of financial professionals. The information and functionality of this software is for research and educational purposes. Consult a licensed professional for investing advice.
All gratitude to the Michigan Tech students who worked on this project to develop IT and FinTech knowledge and skills through their coursework and share their contributions.
- Jeffrey Wall - Faculty Advisor
- Divy Patel - Graduate Research Assistant - March 2024 - April 2025
- Yaman Aljnadi - Graduate Research Assistant - January 2025 - April 2025
- Students at Michigan Technological University in MIS 4100 - Emerging Technologies: Fall 2023
- Students at Michigan Technological University in MIS 3200 - Systems Analysis and Design: Spring 2024
- Students at Michigan Technological University in MIS 4100 - Emerging Technologies: Fall 2024
- Students at Michigan Technological University in BA 5200 - IS Management and Data Analytics: Fall 2024 and Fall 2025
- Students at Michigan Technological University in MIS 3200 - Systems Analysis and Design: Spring 2025