财务指标分析:数字银行与合并银行的比较

Rayssa Kawanne dos Santos, Maria Helena da Silva Gonzaga
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摘要

目前有可能发生第四次工业革命,人工智能,工业4.0,在金融市场上也不会有什么不同。金融科技公司或新的创业公司致力于创新和优化金融市场服务,有望彻底改变巴西的分支机构。然而,在多大程度上可以相信它们的模式作为合并机构具有盈利能力和效率?由此,本工作旨在通过财务指标分析在巴西运营的两家主要银行Itaú和Bradesco的资产负债表和损益表,并将其与唯一一家在圣保罗证券交易所上市的金融科技公司Inter进行比较。因此,这项工作的主要目的是核实这些机构的经济和金融指标之间是否存在差异。结果表明,杠杆指数差异最大,Inter平均为9.10,Itaú, Bradesco平均为10.08,10.85;固定资本,interbank占比平均为1.45%,其余分别为7.56%和5.58%;除净资产收益率外,在该指标中,interbank的统计平均百分比为9.76%,Itaú为16.36%,Bradesco为15.88%,这可以从金融机构在租赁业务的确认和计量、信贷业务相关收入以及其他可能导致指标增减的变量的结构差异中得到证明。在使用的其他指标中,发现了不同的统计结果,但没有统计相关性。
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AN ANALYSIS OF FINANCIAL INDICATORS: A COMPARISON BETWEEN DIGITAL BANK AND CONSOLIDATED BANKS
Currently there is a possible fourth industrial revolution, with artificial intelligence, industry 4.0 and it could not happen differently in the financial market. Fintechs or new startups work to innovate and optimize financial market services, promising to revolutionize the branch in Brazil. However, to what extent can it be trusted that their models have profitability and efficiency as consolidated institutions? From this, this work aims to analyze, through financial indicators, balance sheets and income statements of two major banks operating in Brazil, Itaú and Bradesco, and compare them with Inter, the only fintech listed on the São Paulo stock exchange. Thus, this work has as main objective to verify whether there is a discrepancy between the economic and financial indicators of these institutions. The results showed that the biggest differences are in the leverage indices, with Inter averaging 9.10 and Itaú and Bradesco, respectively, 10.08 and 10.85; fixed capital, with Inter Bank having an average percentage equivalent to 1.45% and the remaining 7.56% and 5.58%; in addition to the return on equity, in this indicator Inter Bank has a statistically average percentage of 9.76% and Itaú 16.36% and Bradesco 15.88%, this can be justified by the structural differences of financial institutions in relation to the recognition and measurement of leasing operations, revenue related to credit operations, and other variables that may contribute to the increase or decrease in indicators. In the other indicators used, different statistical results were found, but not statistically relevant.
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