Five Ways Artificial Intelligence Is Disrupting Asset Management

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Algorithmic trading using financial models has a rich multi-decade history, and artificial intelligence (AI) is the new emerging trend in the asset management landscape. Traditional trading algorithms were built to exploit specific opportunities, whereas the new generation of algorithms use the power of AI to truly act as independent agents participating in market action, and working day and night in a way that humans simply can’t match.

AI is a mixed bag of tricks including machine learning, deep learning, conversational interactive systems, and various other “bot” technologies. And the investment landscape is also being affected by AI- after all, AI can read and understand billions of pieces of data, which means one can spot trends better with its aid. It will help investors, portfolio managers, sovereign wealth funds (SWFs), and other financial institutions to predict the future prices more accurately and without the burden of emotional investing. AI-driven asset management will shift the capital of investors in emerging markets from traditional approaches to these lower cost, more diversified, and higher return investment vehicles.

At Investifai, the AI driven investment management company that I founded, our highly proprietary deep machine learning systems can identify and quantify smart investment opportunities with no human intervention, and with better outcomes than traditional portfolio balancing approaches. Further, it utilizes sophisticated machine learning models and powerful computational capabilities to process and monitor huge amount of data; to act in the face of opportunity or crisis quickly and effectively. Here are five ways that we believe AI is transforming the asset management landscape- expect disruption, growth, and above all, smarter investment portfolios:

1. BLACK BOXES The traditional investment view is that the traders oversee the algorithms, and they point the algorithms at an asset management task to produces returns. However, in AI asset management, there are instances where it is the AI telling the humans what to do, with little indication of why these trades have a positive expected return. The most significant challenge faced by portfolio managers is uncertainty. However, the strategy side of asset management has long been the domain of humans and human-made models. With AI, the uncertainty is handed to an algorithm where the predictions and timings are automated to the point where the human may not even be in the loop on why a transaction is being placed. This advanced technology has begun to change as AI takes an ever-greater slice of the asset management business, encroaching further and further into the strategy domain that was once the exclusive domain of human analysts.

2. ROBO-ADVISORS, ETFs, AND OTHER LOW-COST MANAGEMENT STRATEGIESThe emergence of AI offers a solution to handle different real-world investment portfolio management problems, such as uncertainty and financial time-series predictions, which were until now fundamentally handled by skilled investors. The main outcomes of this shift should be lower management fees, as the AI-based managers have a very scalable offering, and higher returns, as algorithms never sleep, and they should make fewer mistakes than humans do. The versatility of the AI architecture is such that it efficiently manages globally diversified investment portfolios that may include not only equities and bonds, but also alternative investments such as gold, real estate, natural resources, forex, cryptocurrencies and many other investment options, at a relatively lower cost.

3. VAST OPPORTUNITY FOR AI IN EMERGING MARKETSRecently, the UAE and Saudi Arabia set on a mission towards the AI-driven transformation for various sectors in the GCC region by 2031. Both countries launched their AI strategies and are set to invest US$96 billion and US$135 billion respectively on AI and Internet of Things (IoT) of the respective countries. Investigate has decided to go to market in the region in order to take advantage of this historic market opportunity to shift assets from traditional to AI-managed portfolios.

4. BALANCING ACTIVE AND PASSIVE APPROACHES AI is now able to bring the best of passive and active investing worlds into one portfolio. The ability to trade risk and reward at the turn of a dial will revolutionize the asset management game, enabling institutional investors and fund managers alike to take complex positions in the market while maintaining a high-level ratio of stable and growth investments. With AI-driven asset management, both consistent and stable returns or high risk for high reward conditions can be programmed into a dedicated AI engine, and adjusted by the investor over time, as their risk tolerance often shifts over the long-term.

5. SENTIMENT ANALYSIS With the wealth of data available through social media data mining, AI trading algorithms now have a new window into the fundamentals of brand value, customer loyalty, and much more.

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