Kara Frederick, tech director at the Heritage Foundation, discusses the need for regulations on artificial intelligence as lawmakers and tech titans discuss the potential risks. Despite the challenges it faces, the financial sector stands to benefit greatly from artificial intelligence (AI) integration. In terms of technology adoption, the financial advisory and wealth management industry has been slow. Despite the rapid advancement of AI and technology, many advisers have continued to use old systems that, in some cases, date back decades. This failure has limited the improved management of client assets in a fast-changing economic environment.

JIFFY.ai & Docupace: "Docupace, the leader in cloud-based fintech digital operations software for the wealth management industry, and JIFFY.ai, the innovative provider of true end-to-end intelligent automation applications, announced the companies are jointly developing the wealth management industry's most powerful suite of automation solutions; deploying leading-edge capabilities such as intelligent document processing, artificial intelligence (AI), robotic process automation (RPA), as well as machine learning and advanced analytics to deliver benefits at scale across enterprise operations." Michael Pinsker, founder and president at Docupace, stated, "Docupace and JIFFY.ai are leveraging our collective wisdom to take the most advanced technologies and pointing them directly at our clients and the wealth management industry's biggest pain points and most common issues of operational inefficiencies." RISE Financial: "RISE Financial, a subsidiary of Siebert Financial Corp., a provider of financial services, announced that it has completed the acquisition of a 20% equity stake in Hedge Connection, the only woman-owned fintech company offering a patented enterprise capital introduction SaaS solution through its product Fintroz. As part of the transaction, RISE Financial acquired the right to purchase up to the remaining 80% of Hedge Connection. Hedge Connection's powerful Fintroz platform allows hedge fund managers to connect with a global pool of institutional investors and retain control over how their information is shared while helping allocators to streamline due diligence. The Fintroz platform provides RISE Financial and its division, RISE Prime, with a technology solution to efficiently scale a comprehensive capital introduction program for clients."

There are expected to be 7.7 million more high-net-worth-individuals (HNWIs) in the world by 2023, according to a report by wealth data business, Wealth-X. This equates to $20.9trn of newly created wealth in the next five years, presenting a huge growth opportunity for the global wealth management industry. As such, we've decided to compile a short list of interesting statistics on the global wealth management industry – taking into account the current state of the industry, future growth prospects and what HNWIs expect from their advisors. We also take a look at how wealth management firms are using technology, and how they plan to do so in the future, considering aspects such as the use of AI and robo-advisors. The strongest-growing region in 2017 was Asia, which posted a 19% increase.

Use of AI within wealth management has the potential to revolutionise a sector struggling with digital change, but according to Tim Waterton, VP of UK Business at M-Files, any use of automation must be applied smartly and not simply for the sake of it. The wealth management sector is facing a growing need for technology-led change, driven by a new generation of wealth. AI could hold the answer, but many wealth managers are struggling when it comes to implementation. A recent poll amongst 500 private wealth executives shows that AI represents both a major challenge and opportunity, with over a third (36 per cent) of respondents admitting they have struggled to capitalise on the technology. Waterton agrees that AI has the potential to transform the way wealth management professionals deliver services to clients and streamline their processes, but also advises caution relating to over-automation.

Much has changed in the wealth management industry since robo-advisors first made their appearance a decade ago. Talk of disrupting the advisor-client relationship has given way to a new generation of innovative technology solutions that enhance and augment the fundamental ways that investors invest and advisors advise. Today, robo-advisors can be seen as part of a broader movement to digitize wealth management, embodied in the term: WealthTech. Technology derived from wealth management firms, research tools that generate investment solutions, and platforms to support financial advisors -- all fall under WealthTech. Finance is becoming a technology play.

Much has changed in the wealth management industry since robo-advisors first made their appearance a decade ago. Talk of disrupting the advisor-client relationship has given way to a new generation of innovative technology solutions that enhance and augment the fundamental ways that investors invest and advisors advise. Today, robo-advisors can be seen as part of a broader movement to digitize wealth management, embodied in the term: WealthTech. Technology derived from wealth management firms, research tools that generate investment solutions, and platforms to support financial advisors -- all fall under WealthTech. Finance is becoming a technology play.

Robo-advisors are currently a prominent topic in fintech as they are disrupting the wealth management industry with their easy-to-use low-cost passive investment management service, which has grown in popularity amongst investors. However, 'robo-advice' is no longer just specific to the wealth management industry. According to Diederick Van Thiel, co-founder of Dutch fintech company AdviceRobo, banks could also use'robo-advice' to predict the creditworthiness of its customers, through the use of artificial intelligence and machine learning. This could be especially beneficial for challenger banks that tailor their services primarily towards millennials who may have limited credit history or no credit score at all. In this case, using the traditional model of assessing a customers credit risk, by taking into account 16 variables of structured data, would not be an effective way of predicting a customer's credit risk.