Virtual assistant and Artificial Intelligence (AI) is fundamentally transforming our interaction with technology. It first began with Siri in 2011 gaining popularity over the years and has now evolved not only in the smartphone operating system but also in a range of many different forms. Successful companies have also incorporated AI assistants, for example, Microsoft has Cortana and Kensho has Warren. Digital assistance has become a more embedded element in our everyday user experience (UX). AI is the most significant general purpose of technology in this era. AI revolves around products that affect our daily lives as consumers. It’s now a common phenomenon when you see a car that can park itself, a robot defeating a globally-renowned chess player, a device that responds to tomorrow weather and even drones.
A virtual, digital or voice assistant is essentially an app or agent that lets users interact with technology using their natural language. It allows the user to give tasks, commands or even ask questions. Natural language processing is the ability of a program to recognize, understand and process human speech in real time. Machine learning, on the other hand, is enabling a program to learn from data and find hidden insights without being specifically programmed where to look. A digital assistant exists in many forms, be it a desktop or a smartphone, specific apps and services or within a connected speaker.
A chatbot is also a form of Artificial Intelligence which uses text-based chat. Chatbots help customers do things such as get customer support information, book travel, complete E-commerce transaction and shop. AI can anticipate market trends by using the latest research and continuously learning from it and improving its model. AI software will bring tangible benefits to the masses.
The spectrum of virtual advisers and assistant start from those with low complexity and technological integration that simply provide information such as chatbot, to the once that are more complex and integrated and can even provide advice. Some examples include robo-advisers for portfolio management, wealth management and insurance plan section, personal shopping bots, security bots and customer support bots. Robo advisors are digital platforms that use mathematical algorithm and technology to select efficient portfolios based on client needs automatically.
Given the quantitative nature, accurate historical data and high volume of the finance world, the sector is better suited for automation and artificial intelligence. AI ingest anything that can help it understand global trends: this includes tweets, financial data, international monetary policies, news, earning numbers or books. AI keep track of all this information around the clock never tiring and perfecting its predictions. Investment firms and financial management are starting to adapt to AI. AI technology can potentially outperform traditional players.
In the past few years, Robo Advisors have been gaining a lot of traction. Robo advisory is generally about saving cost and using systematic and unbiased approach. Clients complete a comprehensive online questionnaire to determine their investment goals, time horizon, and risk tolerance and then robo advisor translate this into investment logic. The clients’ money gets invested automatically in a well-diversified portfolio of exchange-traded funds with the right mix of bonds, stocks and real estates which is rebalanced periodically. Some of the key benefits of Robo advisory are a Lower minimum investment and lower fees for portfolio management, more effective management of investments and transparency of performance. Robo advisory will not just be to replace human jobs but will help redefine new positions to free up time for new roles and positions which will be created as the manner in which products are used.
For any good investment or trading, research is paramount. The trading research was traditionally done by humans particularly the research analyst. The analyst would run a complete study digging up historical data and how the market responded in each case. The study also involved human memory which has its limitation. The major problem with this approach was that you could lose the first trading opportunity when the results were back. The research analysts’ fee was also relatively high. The analyst can also be biased, sensitive and can easily make mistakes. In the case of algo-trading, the knowledge of how to program in specific programming languages is necessary which takes a long time to learn.
The research assistance on Traderiser has you covered in this regard. The platform utilizes blockchain technology. It is very fast and answers all your statistical questions about the financial market. The software purely relies on data and statistics and not human based intuition and justifications. The platform also uses artificial intelligence and have developed their natural language processing framework geared toward the financial sector. With this feature, they provide a user-friendly experience. It simplifies the research process, all you have to do is “just ask the question” as opposed to the current financial market system of report creation. It also enables the user to explore the market with ease and test more trading ideas. Traderiser allows customers direct access to services and monitor the market 24/7 to give accurate, informed and researched information.
In conclusion, with AI, firms can organize and understand data and be able to research what the data is portraying, and its predictions can help clients to invest and make good returns. Traderiser is shifting from the paradigm of traditional research roles and making them absolute. The world is evolving, and artificial intelligence technology is the future so do not be left behind.