InvestBack
InvestBank: Simplifying Financial Management with Personalized Insights, Data, and Advice.
Created on 10th November 2024
•
InvestBack
InvestBank: Simplifying Financial Management with Personalized Insights, Data, and Advice.
The problem InvestBack solves
InvestBank simplifies financial management by delivering only the most critical features, tailored to the individual user. Unlike traditional financial or investment apps that can be cluttered and complex, InvestBank offers a streamlined experience, helping users manage and understand their finances with ease. Users can leverage three main features:
-
AI Chat helper for user
Chat where you will talk to an artificial intelligence that we can see today in various places, but this time, it will be trained with personalised data based on user data, in order to provide answers much more in line with it and always in an economic context given the nature of the project. -
Centralized economic data
Normally bank applications we can see many features which most users do not use, and because of this, many go unnoticed, therefore, this application solves in a minimalist way what we believe are 3 features that today are very sought after by the user, a chat with artificial intelligence trained with their economic data, graphs where you can see relevant data based on their own data against others and tips for all of the above. -
Simplicity for economy
As well as the above, at InvestBank we solve this problem that exists in most applications in areas of economics, such as investment applications with overly complex learning curves, banking software with a multitude of features or mobile applications with very irrelevant things. Here only 3 features are important and with a simple and customisable interface.
Challenges we ran into
-
Setting up integration with Banks
The integration with different bank API's has been the biggest challenge of the project, which we have had to postpone taking it into account for a future version, prioritising the MVP prototype. We will use it for a greater wealth of information for Big Data. -
Big Data use cases integration with AI
Managing large amounts of personalised data with the artificial intelligence model we have trained from an LLM is a big challenge in order to show interesting data from flat information without utility and personalising it with a model already trained with contextualised information. -
Chat response performance
The responses are fast until you require more information and it slows down, it is not something very noticeable, but in some flows it has been difficult to improve it due to the system of nodes that we have implemented.
Tracks Applied (1)
Best use of GitHub
GitHub Education