Artificial intelligence, internet of things, blockchain, virtual reality and modern tech are rewriting the future of work continuously. Are we really moving towards a future that will make our workplaces way more efficient? Before technology started rewriting the future of work, all types of work in various enterprises was handled manually. Employees worked hard for long hours, and this was considered the most important work ethic. But technology has brought about substantial changes in the ways traditional workplaces have operated. For example, in banking, most transactions and operations were handled manually by the employees.
Developments in Artificial Intelligence (AI) and Distributed Ledger Technology (DLT) currently lead lively debates in academia and practice. AI processes data to perform tasks that were previously thought possible only for humans to perform. DLT acts in uncertain environments to create consensus over data among a group of participants. In recent articles, both technologies complement each other. Examples include the design of secure distributed ledgers or the creation of allied learning systems distributed across multiple nodes. This can lead to technological convergence, which in the past, has paved the way for major IT product innovations. Previous work highlights several potential benefits of the convergence of AI and DLT but only provides a limited theoretical framework to describe upcoming real-world integration cases of both technologies. We aim to contribute by conducting a systematic literature review on the previous work and by providing rigorously derived future research opportunities. Our analysis identifies how AI and DLT exchange data, and how to use these integration principles to build new systems. Based on that, we present open questions for future research. This work helps researchers active in AI or DLT to overcome current limitations in their field, and engineers to develop systems along with the convergence of these technologies.
R&C: To what extent are compliance departments turning to new technologies to help manage financial crime risks? Compared to legacy compliance systems, what kind of opportunities does the latest financial technology offer financial institutions (FIs) in identifying and responding to suspicious activities? LaScala: We have seen an increase in compliance departments leveraging new technologies to manage financial crime risks. Tools, such as machine learning (ML), artificial intelligence (AI) and robotic process automation can increase effectiveness and efficiency of anti-money laundering (AML) programmes. Specifically, they can help automate repetitive tasks and produce more valuable alerts so that compliance departments can better identify risk and spend more time investigating potentially suspicious activity.
This article about AI in fintech services is originally written for Django Stars blog. Just as many other technological advancements, Artificial Intelligence came to our lives from the pages of fairy tales and fiction books (think of the Tinman from The Wizard of Oz or Maria from Metropolis). People dreamt about machines able to solve problems and release some of the fast-compounding pressure of the 21st century. Less than 70 years from the day when the very term Artificial Intelligence came into existence, it's become an integral part of the most demanding and fast-paced industries. Forward-thinking executive managers and business owners actively explore new AI use in finance and other areas to get a competitive edge on the market.
Something changed in our coexistence with artificial intelligence in 2018, and it may never be the same. Our mood of how to live in a world of hacked algorithms, stolen harvested personal data, human-sounding bots and agile humanoid robots creeped us out. Facebook stocks seem immune to the creepy feeling that has given away our data to developers who have abused that generosity, and Google is not to blame that is has bots that sounds totally human on a phone call. Of course this is in relation to Google Duplex, the augmented Google Assistant capabilities. How is the reality of crypto related to this? Nvidia Corporation recently revealed the amount of money the company generated from chip sales to the cryptocurrency market, and that the chips would be used for mining cryptocurrency.It's $289 million related to GPUs for cryptocurrency mining, according to a corporate report.
This week I am in Sibos in Sydney speaking about a number of things but the topic closest to my heart is the Future of Work and we're slicing and dicing that on stage in front of nearly 8000 bankers. I fully expect we'll be unpacking far too little with so many big topics swirling around when it comes to trying to imagine what the workplace looks like in 2050. I also expect it will be an awkward session with hard truths shy to come out and same old eager to fill in the blanks. As we were preparing this it became clear there is simply so very much to touch on. With it being one of the very few sessions regarding our biggest asset in banking – our employees, it's evident that collectively, it continues being so much more comfortable overall to speak about technology, numbers, standards and the theoretical threat of a distant AI future.
Duena is the author of "Emotional Banking: Fixing Culture, Leveraging FinTech and Transforming Retail Banks into Brands". She is an independent Digital and CX consultant, FinTech specialist, an entrepreneur and Angel Investor, a mentor for Startupbootcamp and Techstars, the founder of FinWinners – a Finovate coaching company, a blogger with cutting edge opinion style, a public speakers at industry events and the inventor of the Emotional Banking and EX concepts. Over the past few years, Duena has worked with multiple Tier 1 banks be it to assist them in their digital strategy or to help them transform. With a background in Psychology as well as Business, Duena is on a crusade to see lasting change in the industry. She is intensely passionate about getting banks to think of the concept of "Emotional Banking" or how to stop thinking feature set and start thinking customer's feelings, and is working with various organisations on deep cultural change programs that enable them to become truly Human Design led organisations and put Experience at the heart of the proposition to build strong brands that deliver Money Moments not financial products.
Television today is full of shows that raise questions about the ethics of artificial intelligence (AI): Westworld. These shows provoke dialogue over the rights and responsibilities we must take when creating AI, but the issue few are addressing is what happens to all the people displaced by AI. Every time I go to a large chain store I notice more self checkouts and less live humans working there. The transition to AI coupled with blockchain replacing human services is happening before our very eyes, but nobody is aware this is happening. It's not that masses of workers are being fired and removed from jobs, it's that new workers are not hired when existing employees quit.
In 1942, science fiction author Isaac Asimov introduced the world to his three laws of robotics. An incredibly prescient visionary, Asimov started the world thinking about the potential challenges sentient technology might present the world of humanity. In LinkedIn's Financial Services/Fintech survey of more than 1,000 professionals from the broader FI/Fintech space, it is clear that the threats and opportunities associated with A.I. have never been more present conceptually than they are today. When you look at some of the organizations making big bets on A.I. today, the online lists always include technology majors, but we don't yet see banks investing anywhere near the scale of Microsoft, Google, Apple, Alibaba, Baidu and others. Industrial players like Boeing and Tesla are making big bets on A.I., so it is reasonable to expect that we should see big investments coming through financial services also.
By redirecting focus, wealth managers can successfully respond to challenges brought on by digital disruption, demographic shifts, and tighter regulation. Wealth managers have seen their fair share of ups and downs in recent years, and while challenges remain, advisers can drive business and growth by paying attention to demographic segmentation, how investors are using technology, and changes in regulation. In this episode of the McKinsey Podcast, Simon London first speaks with PriceMetrix chief customer officer Patrick Kennedy and McKinsey partner Jill Zucker about the North American wealth-management industry; he follows that with a discussion with senior partner Joe Ngai, on the industry in China. Simon London: Welcome to the McKinsey Podcast with me, Simon London. Today, we're going to be talking about financial advice and the people who provide it: financial advisers, or as they're sometimes known, wealth managers. Wealth management is a very big business--and also a business facing a number of challenges, such as new technology, changing demographics, and tighter regulation in a lot of countries. A little later, we're going to be getting a perspective on China. But we're going to start here in North America. For the first part of the conversation, I'm joined on the line by Jill Zucker, a McKinsey partner based in New York, and Patrick Kennedy, who's based in Toronto. Pat is chief customer officer for PriceMetrix, which provides data and analytics to the wealth-management industry.