Historical financial market data is the time series data from the past. It is one of the most important and the most valuable components for speculating about future prices. With more data, hence more information is available, it is possible to make better conclusions about what will happen in the next time period. ANN/Deep Learning algorithms can "learn" the complex relations between the financial time series by analyzing large amounts of market data.
I Know First is an AI fintech company that provides state of the art self-learning AI based algorithmic forecasting solutions for the capital markets to uncover the best investment opportunities. The company provides daily investment forecasts based on an advanced, self-learning algorithm. The AI Algorithm was developed by Dr. Lipa Roitman, who will also be speaking at the summit, a scientist with over 20 years of research and experience in artificial intelligence (AI) and machine learning (ML) fields, who leads our Research & Development team to further develop and enhance the algorithm.
Blockchain and AI are two of the main technologies that are producing major changes in a wide variety of industries today, paving the way for both new areas, and methods, of innovation. There still remains a lot of mystery however, or perhaps simply untapped potential, surrounding both of these fields when considered separately. Therefore, it is understandable that there is an even bigger puzzle to solve when considering the relationship between Blockchain and AI.
In a report from Forrester Research, it is explained that the future of financial services will require industry leaders to 'focus on digital business reinvention delivered as application programming interfaces (APIs), and partner with FinTechs to create new ways to engage customers'. These updates and transformations will range vastly from some companies launching mobile payment apps, to tackling complex consumer journeys 'such as mortgage applications and insurance claims, and incorporate predictive analytics into more intelligent personalized product advisors.'
The ability to successfully and consistently predict the stock market is, obviously, a gold mine which technologists have been working towards for many years. Thanks to recent rapid developments in deep learning algorithms, more individuals and companies are able rely on stock market forecasting from artificial intelligence, as the technology has begins to predict better than the pros. We spoke to Yaron Golgher, CEO and Co-founder of I Know First, to learn more about algorithmic forecasting.
What comes to mind when you think of AI in Finance? Fraud Detection? Algorithmic Trading? AI has already undoubtedly made huge contributions to the efficiency and accuracy of many financial practices, but there are also lots of new ways that AI is being implemented to alter traditional methods within retail and commercial banking, insurance and many more industries within the financial landscape.
Technology and economics often go hand in hand. The invention of the steam engine in the 1800s and early computer chips in the mid 20th Century generated copious amounts of economic growth. AI has a unique ability to improve both the capital and labour levers in the economy. According to a study done by Accenture, AI will double economic growth by 2035.
Cybersecurity is a growing concern in our densely connected, high-tech world, and the financial industry is a prime target because it contains a significant amount of money, not to mention potentially valuable customer data. Statistics from PwC show a 130-percent increase in fraud incidents, all of which cause monetary losses and other disruptions for financial brands. However, analysts wonder whether artificial intelligence (AI) could finally stimulate meaningful progress in reducing such issues and others like them.
Last week at the Deep Learning in Finance Summit in London, we were joined by some of the leading minds working in AI to disrupt the financial sector. With speakers from Barclays, LV=, Prudential, HSBC and many more, we learned how the most cutting edge deep learning technologies are being applied in industry. I spoke with Adam McMurchie, who is currently working in the digital innovations studio at RBS.
Trend training is a concept that has been circulating in the financial world for some time now. At its core, it involves monitoring certain aspects of the market and identifying patterns that could turn out to be advantageous to your investments. For example, let’s say there is a new start-up that experts say it has a huge potential to become a big player in the IT sector. Due to the buzz, investors will rush to put money into it in hopes of turning a profit. Inversely, investors will take their money back if the company is suddenly surrounded by bad publicity.
While many people have written on the jobs that may get lost in the roll out of Artificial Intelligence, I prefer to reflect on the thousands of new jobs that are being created to (i) design and feed AIs, (ii) assess the technical and economic viability of fintech projects, (iii) enhance the quality of third party data sets or (iv) simply communicate a realistic view of what AIs can and especially cannot do and then structure business models which mitigate the weaknesses of current AIs.
Companies in almost every industry continually depend on technology to ensure they meet stakeholder needs and remain competitive in a demanding marketplace. The financial sector is no different. Below, we'll look at several ways the businesses within it are tapping into technology to achieve notable gains.