D. (Daniel) Liebau

Joi Ito, current director of the MIT MediaLab, describes vividly in his book

“Whiplash” (Ito and Howe, 2016) how the pace of change is accelerating. Emerging

technologies like Blockchain, Artificial Intelligence (AI) and eventually quantum

computing may not be (fully) adopted yet but show significant potential to affect

humankind’s wellbeing and influence across many industries such as healthcare

(Azaria et al., 2016), automotive (Luckow et al., 2016) as well as finance (Yermack,

2016).

The phenomenon of distributed ledger technology (DLT) may disrupt the financial

industry globally. In 2008 Satoshi Nakamoto published the world-famous “Bitcoin”

whitepaper (Nakamoto, 2008) introducing the concept of a tamper-resistant,

decentralized and “trustless” ledger to the world. Since then, digital assets and their

respective markets based on Blockchain are continuously developing, reaching

nearly $300 billion in market capitalization in early July 2019 – which is already

larger than many countries’ total amount of bank-notes in circulation; Switzerland,

for example, is nearly 79 billion CHF or $80 billion (Swiss National Bank, 2019).

AI is yet another disruptive innovation impacting the financial industry. In his

recent book “AI Superpowers” (Lee, 2018) argues that we have now moved from the

age of AI discovery (focused on research) to one of AI implementation that is all

about the application of the technology to real-world problems. FinTech startups,

established financial services firms and technology giants providing financial

services all leverage AI and machine learning. They apply it to a varied set of

problem statements from stock selection to customer interactions.

Application of these novel technologies and re-invention of (business models) based

on them for the benefit of stakeholders is commonly known as innovation. Thus, my

PhD research proposal is at the intersection of innovation, finance, and information

technology (for example blockchain and artificial intelligence).

This proposal outlines the three papers. In Paper one I propose to study how to deal

with the adverse selection and moral hazard problems associated with Security

Token Offerings. In Paper two I propose to explore the success factors of novel

financial services institutions that can deal with digital assets & cryptocurrencies. In

Paper three I focus on the use of machine learning to make sense of sentiment data

influencing cryptocurrencies price movements (other than Bitcoin).