Impact of AI on Financial Markets
Fintech & AI
The Fintech Industry is booming since since 2016 with China and USA leading the Market. This sharp acceleration is the consequences of the growing capabilities of Bid Data treatment and storage due to the Machine Learning and Artificial Intelligence. Indeed, the high capability of IT engineer to compute and storage allow today to record and process the amazing quantity of big data and thus allow to fuel algorithms and make them become more reliable than before.
The uses of Artificial Intelligence in healthcare, automotive, security and retail has already made its prove, however, the remaining questions is more sociological than technical namely, does AI will replace or be used only as a support tool to help managers and humans more generally in their decisions- making? Is it possible that AI completely replace the tasks of employees within the Banking System?
AI has already been used in Fintech for High Frequency trading for more than 30 years now, but the access of data was not that easy and accurate than today. Today, AI allows better customization of the experiences for customers, provide more efficiency, increase the productivity and allows an overall cost reduction by reducing the number of intermediaries and counterparties.
AI trading may replace sooner or later high frequency trading
The Financial market is today mainly driven by an army of computers and quantitative statisticians developing trading algorithms based on statistics and technical approaches. Artificial Intelligence will provide investment opportunities based the work of a neural network, constructing new trading patterns and trends based on previous experiences and on the markets sentiments.
AI trading will allows to develop tailor-mad investments through Chat-bot
The time of calling its Financial advisor or its Broker is revolute. AI will allow any retailer or professional investors to customize his / her investments based on personal criteria. And everything could be done on distance via a Chat bot (chat agent). Indeed, programmers can design easily learning algorithms that use client’s information and data to determine and highlight investing habits or preferences (sector / industry / liquidity / maturity / risk profile …) in order to make recommendations. Allowing to any investors to have a robot-advisor available 24/24 and 7/7 is a service that most of clients will value. Chatbots could be also implemented to help customers to decide investing among a vast range of products based on its personal investor profile.
Governance & Money / Risk Management
This is where AI may need some support through more quantitative algorithms that focus more on investment decisions-making rather than investment opportunities. However, we can imagine that an AI algorithms could optimize an investors’ portfolio allocation based on his / her expectation of risk, performance and maturity.
Since its debut in 2009, blockchain technology was first used for decentralized cryptocurrencies but is now finding new applications in banking, financial markets, insurance and lease contracts, as well as accounting. Blockchain is, in fact, an open, distributed ledger which records transactions and it is useful in applications which require a proof of originality and an explicit timestamp, increasing transparency and trust.
AI in Fintech, the Future
Legislative changes are encouraging fintech development. In Europe, the Payment Service Directive (PSD2) expected to be in force at the beginning of 2018 will allow clients to authorize the access of third parties to their bank accounts for payments. This legal framework will ensure both a universal compliance standard, secure payments and more data available to clients.
There is a clear advancement towards using more technology in the financial sector not only to increase productivity but to create a more personal relationship with the customer, more lucrative portfolios, and even a decentralized money system. Yet, we are still far away from the day when finance professionals, risk managers, and quants can actually fear for their jobs. Right now, AI can be compared to an intern, sitting quietly, running errands and learning.