Framework: Financial Technology (FinTech) is an industry composed of diversified firms that combine financial services with innovative technologies. The research question and main goal are attempting to answer whether they are more similar to traditional banks or trendy technological firms deploying their innovativeness to favor financial inclusion and sustainability. Justification: Evaluators may wonder if FinTechs follow the typical evaluation patterns of bank/financial intermediaries or those of technological firms. Preliminary empirical evidence shows that the latter interpretation is the one consistent with the stock-market mood. Objective: This study goes beyond the extant literature, analyzing the differences between FinTechs and traditional banks in market valuation, and showing the potential for digital interaction and cross-pollination of complementary business models. Methodology: The differences will be empirically analyzed with the stock market valuation and the multipliers associated with these firms. Results: The main contribution of this paper is that the appraisal approaches of FinTechs follow those of technological startups, having a revenue model much more scalable than that of a typical bank. FinTechs may so provide a solution for sustainable finance with microfinance and crowdfunding among others. FinTechs and traditional banks may eventually converge towards a common market exploiting co-opetition strategies.

Gender policies concerning the composition of board of directors are included in the legislation of many countries, especially promoted by the European Commission to reach gender equality in the processes of decision making. On the other hand, in the last decades, sustainable development problems caused by economic progress have enhanced the interest in environmental policies. Using the data from top Spanish listed companies, from 2003 to 2017, we test if the higher number of women on their board influences corporate social responsibility (CSR), through the disclosure of reports following the Global Reporting Initiative guidelines and the inclusion in the Dow Jones Sustainability Index. By using probit models and instrumental variable estimation to address endogeneity and reverse causality problems, we find that the female presence in management positions is positively linked to a voluntary disclosure of CSR reports and the inclusion in a sustainability index, which supports gender legislation.

The objective of this study is to determine the impact of artificial intelligence (AI) on the earnings before interest, taxes, depreciation, and amortization (EBITDA) of firms as a proxy of their financial and economic margins by improving revenues and minimizing expenses. This impact is positive on the market value and scalability by improving the economic and financial sustainability of companies. The methodology is based on a business plan that considers the savings obtained by a traditional firm implementing AI. Specifically, a sensitivity analysis will demonstrate that AI savings impact key parameters, leading to economic and financial sustainability. Additionally, a mathematical interpretation, based on network theory, will be produced to provide and compare the added value of two ecosystems (without and with AI that adds up new nodes and strengthens the existing ones). The main contribution of this paper is the combination of two unrelated approaches, showing the potential of AI in scalable ecosystems. In future research, this innovative methodology could be extended to other technological applications.

Zadeh’s fuzzy set theory for imprecise or vague data has been followed by other successful models, inclusive of Molodtsov’s soft set theory and hybrid models like fuzzy soft sets. Their success has been backed up by applications to many branches like engineering, medicine, or finance. In continuation of this effort, the purpose of this paper is to put forward a versatile methodology for the valuation of goods, particularly the assessment of real state properties. In order to reach this target, we develop the concept of (partial) valuation fuzzy soft set and introduce the novel problem of data filling in partial valuation fuzzy soft sets. The use of fuzzy soft sets allows us to quantify the qualitative attributes involved in an assessment context. As a result, we illustrate the effectiveness and validity of our valuation methodology with a real case study that uses data from the Spanish real estate market. The main contribution of this paper is the implementation of a novel methodology, which allows us to assess a large variety of assets where data are heterogeneous. Our technique permits to avoid the appraiser’s subjectivity (exhibited by practitioners in housing valuation) and the well-known disadvantages of some alternative methods (such as linear multiple regression).

After describing the main features of the Spanish companies belonging to the FinTech, InsurTech, and PropTech sectors, the main objective of this study is to analyze whether their B2B/B2C business models are related to the existence of sustainability plans. Specifically, this paper analyzes whether the existence of a sustainability department is a determining factor for the business model adopted by the Spanish FinTechs, InsurTechs, and PropTechs. By using the multinomial logit regression, other factors such as the current closeness of companies to the sustainable development goals (SDGs), the sensitivity to domestic and European FinTech/InsurTech regulations, and the perception of FinTechs about such European regulations are debated before conclusions are drawn for a future research agenda.

In general terms, decreasing impatience means decreasing discount rates. This property has been usually referred to as hyperbolic discounting, although there are other discount functions which also exhibit decreasing discount rates. This paper focuses on the measurement of the impatience associated with a discount function with the aim of establishing a methodology to compare this characteristic for two different discount functions. In this way, first we define the patience associated with a discount function in an interval as its corresponding discount factor and consequently we deduce that the impatience at a given moment is the corresponding instantaneous discount rate. Second we compare the degree of impatience of discount functions belonging to the same or different families, by considering the cases in which the functions do or do not intersect.