Our financial future
How might we use publicly available data to safeguard citizens’ financial future?
Go to Challenge | 11 teams have entered this challenge.
Team FinVenger
FinVenger will change the way Australian youth plan their HELP debt repayment and secure their future by efficiently planning their investment strategies towards their financial goals.
From the dataset; we have observed the presence of defaulters even in the age group of 60+ years. This can be inferred as an outcome of limited financial knowledge and lack of awareness with regards to financial planning in a person’s early stages of their career.
There is a definite need for a digital platform, where by using predictive and adaptive analysis of a person’s financial history, they are able to obtain an overview of their overall financial health in terms of assets, debts, spend figures, investment potential and their own risk appetite that is derived using multiple parameters.
Our solution - FinVenger; is an omni-channel digital solution that leverages the historically available datasets and provides a detailed personalized solution that enables today’s Youth to not only invest smartly, but also see a timeline view of the projected financial figures along with the risk analyzers.
AI/ML based saving and investment features will enable the user to start repaying the debt voluntarily even before they reach the payable slab, so that the time required to repay the debt is reduced and the user becomes debt-free earlier.
We also provide access to a team of highly recommended financial mentors who are available to guide the user throughout their journey.
So, start saving - start investing and SECURE YOUR FUTURE!!!
Description of Use This data gives us details on day-to-day person’s expense which will help application to understand person expenses in relationship with his incomes. With this application will run various AL/ML based algorithms to provide person with suitable strategies to plan your future
Description of Use These data helped in understanding at what age people in Australia tend to put personalized contributions in the Supers
Description of Use This data helped in understanding the geography wise income distribution and taxes.
Description of Use This data has the information related to people income by age which helped in identifying on average how much money they earn yearly. This will be crucial part of data in the application to put person in right category based on the details shared.
Description of Use This data helped in understanding in last year what methods people adopted to lodge their taxes.
Description of Use This data was used to see lost and unclaimed supers. With help of this, root cause was identified for these lost like youth showing interest in early days of their careers because of which they lose track of their super accounts
Description of Use This data helped in understanding the HELP outstanding debt amount and debtors. Through this data various information relating to the age range, income range, outstanding debt range is analysed to see what segment needs more help in their finances and clear out their debts early.
Description of Use Based on this data, algorithms will be built which will do predictive and adaptive analysis not just considering historical data for individual, it will use data of all individual having same circumstances such as age, income bracket, job area, spending, debt and various other factors which determine person’s financial health. Based their actions and past data it will suggest suitable strategies which a person can adopt.
Go to Challenge | 11 teams have entered this challenge.