Predictive Financial Analysis of University of Liverpool's Annual Accounts: A Python Data Pipeline

Overview

A data analytics project completed in the role of an external analyst engaged by the University of Liverpool to review its annual financial statements. The brief combined hands-on Python development - data processing, visualisation, and predictive modelling - with a written report translating the statistical output into actionable financial recommendations.

What I did

• •Wrote a Python script to read and process raw income and expenditure data from CSV files
• •Calculated total annual income, total annual expenditure, and annual profit/loss across the full time series
• •Built four+ charts to visualise trends over time (e.g. annual income) and compare categories within a given year, highlighting the dominant expenditure items
• •Fitted linear regression models to total income, total expenditure, and profit/loss, and used them to forecast each figure for 2023
• •Built a bonus interactive dashboard consolidating the regression forecasts alongside the key charts from the exploratory analysis
• •Wrote a 1,200-word report summarising the findings with supporting chart screenshots, critically evaluating the trends and their likely underlying causes
• •Cross-referenced the analysis against the University's 2022 Annual Report to support a set of financial recommendations

Skills & tools