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According to the Organisation for Economic Co-operation and Development, financial literacy is the process by which individuals seeks their well-being by acquiring knowledge in personal finance and through the use of assimilated learning on ways to deal with money and financial products, improve their standard of living and the society to which they belong (OECD, 2005). This study is in line with a worldwide effort to apply financial literacy (Mitchell and Lusardi, 2011). The main research problem explored is how to systematize the financial planning professional’s knowledge to consider the specific profiles and respect the needs of each individual. These professionals are expensive and could not be accessible by all peoples in a country.
In summary, financial literacy is composed of eight areas of knowledge, which can be divided into basic and advanced, as shown in figure 1. The first step should be to search for motivation and basic numeracy skills, and then, it seeks to structure a budget plan to guide the proposed goals in the project that motivated the beginning of learning. Also, new consumption habits are needed when the budget planning is started and constantly monitored, mainly for debt management and the construction of an emergency reserve. With these steps properly executed, the advanced steps are knowledge related to risk management, investments, and retirement (Lusardi & Mitchel 2010; Seeber & Retzmann, 2016; Marin & Notargiacomo, 2019).
Figure 1. Financial literacy training structure (Marin & Notargiacomo, 2019)
Lusardi and Mitchel (2010) determine that, for the first area of knowledge (self-motivation), there are two basics motivations for an individual to seek financial literacy: the accumulation of wealth to satisfy a desire or need, such as the realization of a project, and planning for retirement. Both are salutary given that the first reason reaches the achievement of self-esteem, the top of Maslow’s motivational pyramid (Maslow, 1943) when all individual needs are properly satisfied, and the fullness of personal well-being is reached. The second reason is comparable in importance, given that the lack of funds in elderly life makes the individual more vulnerable to the adversities caused by old age, such as health problems and reduced mobility, as well as more dependent on public policies to supply such personal deficit (Rooij et al., 2011).
A study developed by Drexler, Fischer, and Schoar (2014) supports these areas in a summary of financial literacy training programs. It starts with the Savings area and understands the motivations to start it (Self-Motivation), setting saving goals, and continuing with Consumption, Debt Management, Account Separation (budget Planning), and Estimation Methods. These studies reinforce that the effectiveness of this training process depends on the constant efforts of students in monitoring their accounts budget and expenses.
This article contribution is to present a system architecture and prototype capable of integrating artificial intelligence tools to consolidate this training pattern through the acquisition of expert’s knowledge, also to reduce the amount of effort that finance students have to expend to maintain financial control in their lives and, be an independent solution capable of unifying the users’ financial data sources. The next section explores the related concepts and works relevant to this proposal. After that, it has presented the architecture of the STIMA system (an Italian word for esteem and estimation), a multiagent intelligent tutoring system for basic financial literacy training and monitoring, its structures of agents, and then presenting the system used for the inference engine that uses an interpretation of its self-language to list the nodes registered by experts. A technical test was performed with a database previously labeled to validate the system’s accuracy and performance, and then a test user was followed by a tutor within 4 months to infield validations, and finally, the test results and possible improvements of the system are discussed in the conclusions.