Making the most of your KiwiSaver
How can we make Financial Literacy fun whilst learning about making the most of your KiwiSaver?
Go to Challenge | 1 team has entered this challenge.
Team Name:
Hedwig
Team Members:
WISER
Project Info
Team Name
Hedwig
Team Members
Kenny , Petr , Alec , Joy
Project Description
Problem
KiwiSaver enrolments of the age group 14-19 are steadily decreasing.
Teenagers do not have enough understanding of KiwiSaver and how it could help them plan for their future.
There are very limited mediums and resources for teenagers to learn about KiwiSaver without encountering unfamiliar jargon and sophisticated concepts.
Solution
By creating an engaging, interactive, fun-to-play visualisation tool customised to our target audience, we bridge the communication gap between teenagers and government.
This application is designed to be a journey planner, where the customer will start their adventure by setting up their goals for the future. Using the data related to their aspirations, the app provides visualised information about how KiwiSaver could be their best friend along their journey. To make it more engaging, we created Hedwig the owl who will be the user's companion and assistant. Hedwig will introduce important information about KiwiSaver and the significance of early investment. The uniqueness of the app, comes from the data visualisations, where users would not be puzzled by the jargon or abstract values of savings, but will be presented with clear, impactful and meaningful graphs, which can be easily interpreted by anyone even with basic levels of financial/mathematical literacy.
Ultimately the app will increase teenagers' awareness of KiwiSaver, its benefits and the importance of it.
Data Story
The data our team has used for our project mainly comes from Stats.NZ, which included New Zealand 2018 Census dataset and 2019 Detailed Household expenditure data set . The most of data resources had aggregated information with census containing very limited number of professions, summarised in 7 different categories.
For our project we had to find more detailed job salary datasets for the New Zealand population, thus we used SEEK.com.nz to find average earnings of 300+ different jobs and 20+ industries.
To account for the cost of life we used the Household expenditure dataset from Stats.NZ, we then calculated a scalar factor to find how the cost of living of each region changes with respect to national average.
We then used that data to make our predictions as accurate as possible.
In future we plan utilising additional data including creating an API to provide real-time information.
Team DataSets
Household expenditure statistics: Year ended June 2019
Description of Use This data was used to create a scalar factor to represent the cost of living in different areas of NZ
KiwiSaver statistics by year
Description of Use This data was used to identify the issues related to KiwiSaver and decrease of teenager investment.
Hedwig Dataset
Description of Use The Salary table has average Salaries across NZ taken from SEEK.com. House Price Table wasn't used in the solution due to lack of time. Expenditure data is the cost of living in each region with respect to the national average. National average and weekly living costs from Stats.NZ Detailed Household expenditure dataset were used.
A guide to salaries in your industry
Description of Use The data was used as expected job salaries that users would receive after selecting the job.
Subnational ethnic population projections, by age and sex
Description of Use This data was used to ensure that our interpretation of KiwiSaver data was correct, that indeed there is a decrease in opt-ins of teenagers.
Challenge Entries
Thinking Outside the Box
This challenge is about showing your artistic side. Use data to create something artistic which fits into any of the 2020 GovHack Themes
Go to Challenge | 5 teams have entered this challenge.