Investing has long been a complex and often overwhelming process, requiring extensive research, analysis, and decision-making. However, with the rise of artificial intelligence (AI), there has been growing interest in using AI algorithms to manage investments. Can AI be the investment manager of the future? Let's explore the research and real-time experiments to find out. According to a study published in the Journal of Banking and Finance in 2020, robo-advisors, or AI-powered investment management services, can provide cost-effective and personalized investment advice to clients, particularly for those with limited investment knowledge or smaller portfolios.

The search for alpha can take us to some unusual places -- perhaps none more so than the 13th century works of Thomas Aquinas. His philosophical maxim, "Finitum non capax infiniti" -- "The finite cannot comprehend the infinite" -- makes a compelling argument for an entirely undifferentiated source of alpha: artificial intelligence. To apply this postulate to AI: While there are some types of AI that humans can comprehend, there are others that, because of their complexity and high dimensionality, are beyond the ken of human intelligence. There are clear signs that we have reached a tipping point where certain types of AI have surpassed the human mind: The finite (humans) cannot comprehend the infinite (advanced AI). Yet because of a deep-seated industry bias that investment results must be explainable, investors have been slow to accept the superhuman capabilities of advanced AI and, as a result, are failing to consider unique sources of alpha that could provide better investment outcomes.

Humans have always welcomed other beings in finance: over twenty years ago, some of the best Wall Street traders were outsmarted by Raven, a chimpanzee who picked stocks by throwing darts. Her index, called MonkeyDex, became one of the biggest sensations at the turn of the century after delivering a 213% gain. Perhaps because animals are not so easy to fit in offices, people have turned to other kinds of brains to choose equities. Big institutions are resorting to artificial intelligence (AI) to analyse stocks collating all sorts of information coming from a plethora of sources. In fact, while investments could previously be assessed based on financial reports and share price movement – what is called structured data – markets have been heavily influenced by unstructured data over the past few years.

Digital fraud is a widespread problem, with fraud losses totaling more than $1.45 trillion annually around the globe. A fraud attack against a bank or business occurred every two minutes on average in 2019, for a total of 59,627 attacks that year. What's more, these figures do not take into account the innumerable schemes launched against individuals. The pandemic has only exacerbated the fraud threat as bad actors exploit economic uncertainties to scam individuals from all walks of life. One especially popular method of digital attack is authorized push payment (APP) fraud, which sees bad actors impersonating trusted merchants or officials and demanding payment from victims for goods or services.

ONLY 10 per cent of fund managers or analysts have used AI or Machine Learning in the past year, according to a 2019 CFA Institute survey of the adoption of Artificial Intelligence (AI) in the investment management industry. People may wonder why investment managers are late adopters of...

Get the Deloitte Insights app. Since February 2020, there has been a dramatic shift in the operating environment of financial markets, with increased volatility, repricing of assets, and transitions of favored asset classes. Uncertainty abounds for investment managers. According to one hypothetical stress scenario, individual managers may have seen assets under management fluctuate by up to one-third in the United States as outflows and valuation changes have affected many during the pandemic.1 Even before the emergence of COVID-19, the situation for investment managers appeared ripe for change.

AI is making strides at many levels in the world of investment management. Investors may already be riding the wave of artificial intelligence, unaware of the many ways they've been integrated. There are three main levels where AI is making a mark, says Amit Gupta, a managing director in Accenture's capital market industry group. At the first level, firms are using AI in back-office administrative tasks like net asset value calculations, reconciliation, settlement operations. At the second level, they use it in front-office tasks like client targeting and management, profiling of clients, personalization of service.

Some industry experts argue that machine learning (ML) will reverse an increasing trend toward passive investment funds. But although ML offers new tools that could help active investors outperform the indexes, it is unclear whether it will deliver a sustainable business model for active asset managers. Let's start with the positives A form of artificial intelligence, ML enables powerful algorithms to analyze large data sets in order make predictions against defined goals. Instead of precisely following instructions coded by humans, these algorithms self-adjust through a process of trial and error to produce increasingly more accurate prescriptions as more data comes in. ML is particularly adaptable to securities investing because the insights it garners can be acted on quickly and efficiently.

NEW YORK–(BUSINESS WIRE)–Allianz Global Investors ("AllianzGI"), one of the world's leading active investment managers, announced today that the AllianzGI Artificial Intelligence & Technology Opportunities Fund (the "Fund") has completed its initial public offering. The Fund raised $615,000,000 in its common share offering, excluding any exercise of the underwriters' option to purchase additional common shares. The Fund commenced trading on the New York Stock Exchange ("NYSE") on October 29, 2019, under the ticker symbol "AIO." The Fund is a diversified, limited-term, closed-end fund whose investment objective is to provide total return through a combination of current income, current gains and long-term capital appreciation. The Fund has a limited term feature pursuant to which it intends to terminate on or about October 29, 2031 (the "Dissolution Date").

AI will be a quantum leap for reinsurers, redefining the concepts of risks that have always been part of the reinsurance industry. FERMONT, CA: Artificial Intelligence (AI) has been rolling out at a remarkable pace in the insurance and reinsurance industry. This growth occurs at the intersection of three major technological trends, such as the rise of big data, the normalization of human-machine interconnection, and advancements in machine learning. However, the growing use of AI raises numerous risks. For example, in an accident caused by an autonomous vehicle, who is responsible for the algorithm behind the software–the user, the manufacturer, or the creator?