Impactos da aplicação de inteligência artificial na formalização de contratos de financiamento de veículos em uma instituição financeira

Abstract

Financial institutions are always searching for innovation in credit agreement formalization processes, in order to follow strict audit tests, as well as serve clients in shorter terms. For this reason, they look for tools to improve their operation, to come out of traditional products offered by the market, enhancing the way they manage their information. Currently, contract formalization processes require a large-scale human interaction, resulting in errors and rework in the process. In this sense, this Technical Report (TR) presents an analysis in a medium-sized Financial Institution, in the segment S3 of prudential regulation of the Financial National System (NFS), initializing an automation in the formalization process of vehicles financing contracts, that will allow the use of Artificial Intelligence (AI) in the future. The analysis compares the traditional model, valid in the institution until March 2014, with the current one ("hybrid model"), which uses some AI elements, highlighting their impacts. The paper also analyzes the impacts in the use of model with a complete AI application. This type of study has not been extensively explored in Brazil yet, and the most commonly observed studies focus mainly on the legal validity of these contracts (Azeredo, 2014). Before the practical application of the findings, the main financial and organizational impacts of the application of AI to a specific process were identified, as well as the necessary adaptations to the processes for partial or total AI application. It is expected that this report contributes to the field of information management in financial institutions of different sizes that need to change processes in this direction. The reporting method was based on a qualitative approach, with the availability of publicly available data, as well as visits to specialized companies that do this kind if work for financial institutions.