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Maria Jofre

Maria Jofre

BEng MSc Operations Management University of Chile
Casual Lecturer; PhD Candidate

The University of Sydney
NSW 2006 Australia


Bio

Maria joins us from Chile where she studied Industrial Engineering and a Master’s Degree in Operations Management. The topic of her Master’s thesis was crime prediction on public areas using multivariate logistic regression based on landscape characteristics. She worked for 2 years before becoming a PhD student, first in a consulting agency and then in Westpac. Her passion for research motivated her to pursue a doctoral degree in Statistics applied to Criminology and Justice.

Newsroom articles

  • Maria Jofre on Radio National 16 Nov 2016

    ABC Radio National Science Show

    Maria Jofre was interviewed on Radio National’s The Science Show about the mathematics of criminal behaviour in business.

See all Newsroom items for Maria Jofre


Thesis working title

Corporate Fraud Prediction

Corporate fraud is a global concern representing a significant threat to social stability and national security. Several accounting scandals account for this reality, exposing how vulnerable are individuals, businesses and governmental institutions when dealing with the catastrophic consequences of this type of crime.

In recent years, data-informed quantitative models have been developed to detect and prevent corporate fraud. Although the existing techniques have improved the detection rate of fraud offences, these are very limited and can be improved in terms of accuracy and efficiency.

Accordingly, the main objective of this study is to create a practical and impartial analytical tool in order to differentiate between fraud and non-fraud companies by assessing the likelihood of corporate fraud using publicly available information.

Supervisor: Richard Gerlach

2016

5
Conference Paper/s

Jofre M, Scharth M and Gerlach R 2016 'Complete Subset Logistic Regression for Corporate Fraud Detection', Australian Statistical Conference ASC 2016, Canberra, Australia, 9th December 2016

Jofre M and Gerlach R 2016 'Fighting Financial Statement Fraud Through Predictive Analytics', American Society of Criminology Annual Meeting 2016, New Orleans, United States, 19th November 2016

11
Seminar Paper/s

Jofre M 2016 'Breaking the Wall of Corporate Impunity, Falling Walls Labs Australia, Canberra, Australia, 24 August 2016

2015

5
Conference Paper/s

Jofre M, Gerlach R and Christodoulou D 2015 'Machine Learning for Financial Statement Fraud Detection', 2nd Conference on Business Analytics in Finance and Industry BAFI 2015, Santiago, Chile, 16th December 2015

Jofre M 2015 'Financial Statement Fraud: Key Features and Market Reaction', 1st Winner International Statistic Poster Competition ISPC 2015 Industrial Engineering Student Council, Petra Christian University, Surabaya, Indonesia, 26th June 2015

Recent Units Taught

  • BUSS1020 Quantitative Business Analysis

    2017: S1,

  • QBUS5002 Quantitative Methods for Accounting

    2017: S1,
    2016: S2,
    2015: S1, S2,

  • QBUS6810 Statistical Learning and Data Mining

    2017: S2,