This project is being completed as independent project interns for SK Telecom. We are working on Finnq, a FinTech startup owned by SK Telecom and Hana Bank that seeks to disrupt the South Korean FinTech industry.
Specifically, our project - brainstormed by our team and agreed upon as having the capability to add value to Finnq - seeks to personalise user experience through use of a classification model
We will be using Python3 for a number of reasons:
- Readability.
- Support libraries for data science.
- Object oriented.
- Learning opportunity for future.
The types of packages we plan to use include: statistics, random, numpy, matplotlib,scikit-learn, among others.
Nota bene: We will not be using Finnq data, nor will we try to represent Finnq data to a high degree of accuracy. In other words, the model will not tell us information about existing customers.
The point of this model is to provide an example of how a user persona approach could be beneficial for Finnq upon being applied to Finnq data. The data fields provided by Finnq will only be useful in considering the type of data Finnq collects so that we can supplement our model further to make it more accurate in personalisation.
- A white paper: to show the statistical analysis/data gather process, the model used, the rationale behind the model, and a guide for implementing the model on Finnq's data for the future.
- The model itself.
- A short presentation that represents our whitepaper research in a presentable format.