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Abstract
The influence of fintech is beginning to be felt in the banking sector and capital markets. This article surveys its development and its impact on efficiency, banking market structure, strategies of incumbents and entrants, and financial stability. Fintech has a welfare-enhancing disruptive capability but regulation needs to adapt so that the new technology delivers the promised benefits without endangering financial stability.
Fintech may be understood as the use of innovative information and automation technology in financial services.52 New digital technologies automate a wide range of financial activities and may provide new and more cost-effective products in parts of the financial sector, ranging from lending to asset management, and from portfolio advice to the payment system. In those segments, the impact of fintech competitors is beginning to be felt in the banking sector and capital markets.53 However, the fintech sector is small in comparison to the size of financially intermediated assets and capital markets, and lags behind in Europe, both in level and growth rate, compared to the US or China. In the European Union (EU), only the UK has a significant development. Even the largest ñntech market, in China, is of marginal size compared to the overall country financial intermediation. In the EU, much of fintech is concentrated in the United Kingdom. Furthermore, fintech in Europe tends to be based domestically and with very limited cross-border flows. This is in contrast to the US and China where new entrants can develop the economies of scale of serving a large market.
With the generation of new business models based on the use of big data, fintech has the potential to disrupt established financial intermediaries and banks in particular. Big data can be treated with algorithms from artificial intelligence (AI), profiting from advanced computing power (including cloud computing, mobile storage through the cloud, and mobile hardware, which allows continuous accessibility). Machine learning is a variant of AI that allows computers to learn without an explicit program; "deep learning" refers to the attempt to derive meaning from big data using layers of learning algorithms. The result of the application of the new techniques could be lower costs of financial intermediation and improved products for consumers. For example, fintech facilities may help to better assess the creditworthiness...