Blockchain for Islamic Social Responsibility Institutions

Blockchain and smart contracts are forming new systems to record and manage businesses with less need for intermediaries. The new systems are expected to offer high level of governance with lower cost as compared to the traditional technologies. While there is a continuous effort to apply this innovative technology in several businesses, Islamic finance in general—and Islamic social finance in particular—are facing few challenges that could be solved by such innovations. Islamic social finance institutions such as waqf are facing some challenges in enhancing its governance structure to ensure Shariah compliance as well as economic efficiency. This chapter explains how blockchain and smart contract technologies can help these institutions for better governance, lower transaction cost, more transparency, and higher trust, hence enhancing the business flexibility and market accessibility. It also presents some related cases that are currently under development as an evidence for the practicality of these technologies in the Islamic social finance arena.

FinTech and SMEs

In this chapter, a study about how Italian SMEs understand and use FinTech technologies is presented. The study focuses on FinTech-aided banking services, in particular, due to the fact that these are, at present, the most widely used FinTech technologies available in Italy. The study shows how, despite FinTech entering Italy only in recently, the Italian SMEs market is very active and fruitful for digital companies. In the last years, a continuous growth of investment has seen the development of FinTech technologies in multiple areas, such as mobile networks, big data, trust management, mobile embedded systems, cloud computing, image processing, and data analytic techniques.

Crypto-Currency

This chapter sheds light on the future of crypto-currencies in the world as they have become a major part of trading and are now being adopted by leading investment firms as a new way of buying and selling. Despite the substantial security risk in crypto-currency trading, it has become the most traded commodity. Many new crypto-currencies are being introduced that attract investors. Banking institutions in USA and other leading countries have started to take part in investments in crypto-currency as it has revolutionized financial technology.

Algorithmic Machine Learning for Prediction of Stock Prices

Stock markets and relevant entities generate enormous amounts of data on a daily basis and are accessible from various channels such as stock exchange, economic reviews, and employer monetary reports. In recent times, machine learning techniques have proven to be very helpful in making better trading decisions. Machine learning algorithms use complex logic to observe and learn the behavior of stocks using historical data which can be used to predict future movements of the stock. Technical indicators such as rolling mean, momentum, and exponential moving average are calculated to convert the data into meaningful information. Furthermore, this information can be used to build machine learning prediction models that learn different patterns in the data and make future predictions for accurate financial forecasting. Additional factors that are being used for stock prediction include social media influences and daily news on trading stocks. Considering these qualitative and quantitative features at the same time result in improved prediction models.

Security and Privacy in FinTech

Financial technology (FinTech) has dramatically changed the way of banking and financial services. Computer programs and other technology which used to provide and enable financial services is named as FinTech. However, these services face several security and privacy issues while providing financial services to the users. These services and applications must be secured to enhance the acceptance and usability of these services among the users. The main aim of this research is to provide a policy framework to ensure the security and privacy of user information in financial technology, since FinTech applications and services carry quite sensitive data of its users. This policy framework provides a comprehensive set of policies to secure FinTech services. These policies must be implemented in each organization providing FinTech services.

Fintech and Shariah Principles in Smart Contracts

FinTech, or financial technology, is an emerging technology in financial transaction. It is disruptive technology which is changing the banking behavior for stakeholders. The thriving emergence of FinTech not only affects the conventional finance industry but also Islamic finance industry, as Islamic finance sector is also embracing FinTech as part of financial revolution. Thus, the Islamic FinTech emerges as faith-based FinTech. This is because Islamic FinTech claimed to comply with Shariah principle in their mechanism and smart contract. There is limited discussion on smart contract and Islamic FinTech and its Shariah principles. Hence, the Shariah principle in smart contract of Islamic FinTech need to be addressed. This chapter tries to delve into the smart contract concept in Islamic FinTech and Shariah principles in the mechanism. The review found that smart contract is currently in the early stage and so is Islamic FinTech. The scholars agreed that FinTech is a Maslahah (interest) to mankind's benefit. However, the smart contract is still in discussion and review.

FinTech and Stock Market Behaviors

This chapter examines the effects of high-frequency trading (HFT) and algorithmic trading (AT) activities, which represent important technological developments in financial markets in the past two decades, on Borsa Istanbul in terms of volatility. To clarify stock market behaviors in terms of volatility, asymmetry, and risk return after the BISTECH transition, the GJR-GARCH-in-Mean and I-GARCH models were used. The dataset consists of the daily stock return series of the main and sub-sector indexes of Borsa Istanbul, covering the period from October 24, 2012 to June 1, 2018. Although there are mixed results for the sub-indexes, it is observed that in the post-BISTECH period, volatility increases significantly in the BIST 100 and BIST 30 indexes, where AT and HFT activities are used more frequently. In particular, the duration of volatility returns to average after shock increases about seven times for BIST 100 and about eight times for the BIST 30 in the post-BISTECH period. Overall, the results indicate that AC and HFT activities may have disruptive effects on financial markets.

FinTech for Digital Financial Services

The introduction of FinTech into Africa's digital financial services environment has provoked a controversy as to whether the innovative technology should be assimilated by banks and other financial service providers or not, thus creating uncertainty about the future of FinTech on the continent. This chapter, therefore, examines the issues, controversy, and problems surrounding the debut of FinTech and suggest ways to make the technology acceptable in order to harness its potentials for the overall benefit of the African society.

Volatility Estimation in the Era of High-Frequency Finance

Over the last two decades, ultra-high frequency (or tick-by-tick) transaction data has become increasingly available. This surge of high-frequency finance data has brought disruptive revolution that makes modeling asset prices as continuous-time processes more possible than ever before. This is because we can now witness market microstructures and stock market volatility over tiny time intervals. This chapter reviews some general frameworks like realized volatility (RV) in estimating the latent volatility and their recent developments in the era of high-frequency finance. New empirical facts are presented to help lay the foundation for creating intraday volatility models that can overcome noise interferences in high-frequency finance data. These facts also help explain some stock market anomalies like volatility jumps and flash crashes, which favor intraday RV over the traditionally used daily RV as a reliable physical measure of market risk.

Emergence of Insurance Technologies (InsurTech)

Technology advances at an incredible rate all around the globe. Financial technologies (FinTech) are defined as production of services that combine financial services and technology. A subdimension of FinTech, insurance technologies (InsurTech) is a system built with the purpose of creating solutions for the insurance sector using a technological approach. Making it easier for the insurance companies and the insured to manage their contracts, minimizing the risks involved, and allowing for the development of innovative technologies, InsurTech is simply the technology of insurance business. For the policy owners, these technologies bring with them the benefit of cost-effective policy solutions. This chapter focuses on the possible impact of insurance technologies on the insurance sector. Explored in this study are the estimated transformation of the insurance sector with insurance technologies and the problems likely to occur as a consequence.