This project was written in collaboration with Paolo Caggiano for the Data Science Lab course in the Master’s Degree in Data Science.
Financial literacy is an important topic that offers a picture of people’s knowledge about basic financial concepts. In this project, we aim to investigate financial literacy and struggles with various financial instruments across the general public. To do so, we used data from the OECD International Network on Financial Education, enriched with data obtained from a research study conducted by Banca d’Italia. This questionnaire has a structure very similar to the surveys banks submit to their clients when opening an account, which makes it well-suited for this kind of research. We aim to provide useful insights for banks and other financial businesses interested in the socio-demographic aspects associated with different financial attitudes and levels of knowledge among the Italian population. In particular, our focus is on financial literacy and the impact it has on how clients manage their money.

First, we developed a model to understand which factors are most associated with financial literacy. The results showed a positive association with both age and education level, and better results for males. These insights could help financial businesses design campaigns aimed at improving general financial knowledge, targeting those most in need. Improved financial knowledge, as highlighted in the subsequent models, results in greater interest in financial services.
In the second section, we took an in-depth look at Retirement Plans. We believed it could be valuable for a bank offering such services to understand which socio-demographic variables best explain individuals’ confidence in their retirement planning and their use of secure financial tools. We found that individuals from southern Italy and the islands tend to have less confidence in their plans and rely on more precarious tools. Additionally, age and employment status were key variables in explaining both confidence and tool usage. Gender appeared relevant only for tool selection, not confidence. Naturally, our research variable, the knowledge score, had a significant impact. For businesses marketing retirement services, it is useful to know which population groups struggle most with these issues and therefore need targeted support.
In the third section, we focused on services related to personal finance. These services help individuals manage their savings and expenses. We found that poor savings management is associated with living in southern regions or islands, being unemployed, or having low financial knowledge. Furthermore, younger, unemployed individuals with limited financial knowledge are the most in need of such services, as they would struggle to handle an unexpected expense. Similarly, services like the establishment of an emergency fund would be particularly beneficial for individuals from the south and islands, as well as for younger people and those with low financial knowledge, as they lack the tools to protect themselves from sudden income loss.

All these issues were addressed using complex statistical models developed with R.

Further information about the decisions we made, the dataset, and the models can be found in the official report.

• Download Report
• Download R code Report
• View in Github

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