Strengthening of Financial Profiles in Latin America: From the Lack of Interest to the Proposal of a Web Platform for Remote Advice

Strengthening of Financial Profiles in Latin America: From the Lack of Interest to the Proposal of a Web Platform for Remote Advice

Asdrúbal López-Chau, Laura Angélica Décaro-Santiago, Valentin Trujillo-Mora, Felipe Casto-Medina, Elvira Ivone González Jaimes, Rafael Rojas-Hernández, Maria Guadalupe Soriano-Hernández
DOI: 10.4018/978-1-6684-5624-8.ch013
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Abstract

The financial profile of natural and legal persons allows financial institutions and financial services companies to identify the level of default of credit applicants. In this way, maintaining a healthy financial profile is derived from a positive history and status, the result of good financial decisions. In Latin America, the vast majority of people pay little attention to strengthening this type of profile, and it is a subject that is rarely addressed on the most popular social media platforms. In this chapter, a search for opinions of Latin Americans regarding the financial profile on the Twitter social network was made, finding that there is a very small number of responses to publications on this topic. Therefore, a web platform is proposed to provide advice on this important issue. The general design of a module for text analysis using sentiment analysis and machine learning techniques is also proposed.
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Introduction

The Sustainable Development Goals (SDGs) involve actions related to the access and management of financial resources of individuals and small businesses, both to address needs in poverty reduction (SDG 1), improve health and well-being (SDG 3), achieve decent work and economic growth (SDG 8) and reduce inequalities (SDG 10) (United Nations Development Programme, 2022). In this way, actions aimed at strengthening the Financial Profile (FP) of individuals, as a whole, is an ingredient for addressing various problems that afflict humanity.

There have been many proposals to improve the FP of people that translates into financial efficiency (inclusion, liquidity, resilience, and achievement of goals), an element that contributes to maximizing the perception of Financial Well-being (FWB) (Clark et al., 2020; Consumer Financial Protection Bureau, 2015, 2019. However, with the progress of studies, it is identified that education through providing knowledge is not enough, since it requires a persistent combination of behaviors and financial attitudes that result in healthy decisions. In addition to personal conditions, the contextual component is also a determinant of FWB that encompasses policies, laws, programs and the supply of products and services to offer advantages to consumers of financial services (Camilla et al., 2020; Comisión Nacional Bancaria y de Valores, 2021; Hougaard et al., 2019); although, for the purposes of this research work, the approach is focused on learning and effort at a personal level.

That said, it can be identified that the FP includes a network of variables that in turn have implications for the perception of FWB. Although there are proposals to measure knowledge, behavior, and attitude as part of financial literacy, generally these are closed questionnaires, focused on very specific topics, whose results come from a performance evaluation such as “The Big Three” of a self-perception assessment or a combination of both (Allianz, 2017; Cliff et al., 2012; Kalmi & Ruuskanen, 2018; Lusardi & Tufano, 2009).. Additionally, these instruments do not specifically capture the state of liquidity, resilience, and position in the scope of people's goals, which allows profiling them (Hougaard et al., 2019).

In early stages of the research conducted by the authors of this chapter about financial profiles in Latin America, it was found a lack of responses on publications on social networks about this topic. This attracted attention of the authors, because one of the hypotheses was that population was interested on this strengthening their financial profiles, and therefore, the development of courses was necessary.

Given this situation, it is necessary to collect sufficient information through alternative tools (instead of questionnaires or interviews) that offer the opportunity to identify the polarity of opinions, practices, interests, concerns, expectations, and motivations. More than identifying what the individual knows about the subject, it is to know how he/she has incorporated the subject of personal finances into his daily life and therefore his perception regarding his current financial efficiency and its consequences. In this study, the search for information on strengthening financial profiles began on web pages and social networks that allow downloading of data.

For financial topics, there are many web pages; however, in a vast majority of them it is not possible to have interaction between users, that is, they are not web platforms. The situation becomes more critical for Spanish, since there are very few web platforms for advice on financial matters, and as far as we know, there is not one dedicated to strengthening the financial profiles of the population of Latin America. On the other hand, although social networks have attracted an immense number of users, and the number of interactions per minute between users is huge, there are few options of specific-purpose social networks, and considerably less interaction between users in these platforms. This occurs not only in strengthening financial profiles, but also in others such as software development, see for example (Magoutis et al., 2015). For these reasons, the objectives of this chapter are as follows:

Key Terms in this Chapter

Interest Score for a Term: It is a score assigned to a search term that indicates the interest of people based on the number of responses to a post on a social network or web platform.

Web Platform: A software system that allows users to register and interact with the application and between them.

Software Architecture: It refers to the structure of a software system, its non-functional characteristics; the rules to build or construct it; and the guidelines that developers can follow to improve the performance, increase security, or scalability of the system.

Financial Profile (People): Set of characteristics and persistent indicators, which reflects the degree of inclusion in formal products, the level of liquidity, the capacity of resilience in the face of fortuitous events and the status in the construction and achievement of goals, which affect the perception of the Financial Well-being of the Individual.

Machine Learning: It is an area of artificial intelligence aimed to develop algorithms to give computers the capabilities learn to solve some types of problems from the data provided.

Sentiment Analysis: It refers to the process of analyzing documents, voice recordings or other types of data that contain opinions about something or someone (expressed in natural language), and detecting the polarity (positive or negative) of the data.

Data Collection From Web Platform Methodology: This term refers to an ordered set of steps to systematically collect data on some web platform.

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