Team Name:
Team Waikato
Team Members:
Team Waikato
This presentation explores the use of a large language model (LLM) to analyze personal bank transactions and grocery spending, offering insights into spending patterns and identifying opportunities for savings. By categorizing expenses into essential and non-essential items, the LLM provides actionable recommendations for reducing unnecessary spending. The system highlights high-cost categories and recurring expenses, helping users make informed decisions such as switching to budget-friendly alternatives or cutting back on non-essential purchases. This approach empowers individuals to better understand their financial habits and optimize their personal finances over time.
We used the Household expenditure survey from the NZ 2023 Census to help the large language model understand the spending pattern to contrast against our own expenses.
the dataset is available in the source code url
STATSNZ,CEN18HOU017,1.0+all.csv
STATSNZ,HESHES003,1.0+all.csv
STATSNZ,HESHES006,1.0+all.csv
#Are higher energy prices avoidable?
Eligibility: New Zealand Only
Go to Challenge | 6 teams have entered this challenge.
Empower Kiwis to be better with their money.
Eligibility: • The tool must not act as a financial advisor such as providing financial advice on Kiwisaver, Investment options, Insurance and mortgages or any other loans. Datasets to Highlight: • National Household Savings Rate (Stats NZ or similar sources) • Consumer Spending Patterns (government open data) • Household Debt-to-Income Ratios • Financial Literacy Data (survey-based datasets) • Investment Behavior and Trends (regional data from Stats NZ)
Go to Challenge | 6 teams have entered this challenge.
