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Financial technologies form the heart of considerable disruptive innovation. Fintech is the emerging financial infrastructure for modern business. Big data are the feedstock for artificial intelligence (AI) that drives many fintech sectors – start-up finance, commodities and investment instrumentation, payment systems, currencies, exchange markets/trading platforms, market-failure response forensics, underwriting, syndication, risk assessment, advisory services, banking, financial intermediaries, transaction settlement, corporate disclosure, and decentralized finance. This chapter demonstrates how analyzing big data, largely processed through cloud computing, drives fintech innovations, scholarship, forensics, and public policy. Despite their apparent virtues, some fintech mechanisms can externalize various social costs: flawed designs, opacity/obscurity, social media (SM) influences, cyber(in)security, and other malfunctions. Fintech suffers regulatory lag, the delay following the introduction of novel fintechs and later assessment, development, and deployment of reliable regulatory mechanisms. Big data can improve fintech practices by balancing three key influences: (1) fintech incentives, (2) market failure forensics, and (3) developing balanced public policy resolutions to fintech challenges.

There does not exist any precise definition of ‘development’. In view of the indispensability of an interpretation of this concept a degree of speculation seems to exist in a development process. This is the reason this chapter has been included in this work. No scholar has precisely defined ‘development’ and ‘developing’ countries. It is believed that indigenous people know best what would be most suitable for them for development of their country. However, any discussion of these topics becomes incomplete, controversial, etc. in the absence of any precise definition. This chapter is no exception to this although an attempt has been made to outline development.