The winners of the future will not be those with the best digital technology and advanced analytics tools, but those organizations who can apply these tools for the benefit of the consumer. It is time to move from great internal reports to fantastic consumer experiences. Subscribe to The Financial Brand via email for FREE!Ever since JP Morgan declared itself a technology company that provides financial services – not the other way around – analysts and investors have been scrambling to discern which banks are doing tech well. They know the banks that harness the power of artificial intelligence, machine learning and big data, and more importantly, the applied business insights they can generate, will be the banks that will be the winners in the long run. "Long term I think this will determine the split between winners and losers," one investor told the Financial Times in a story on AI and banking earlier this year.
The advancement of robotics and artificial intelligence will make 75 million jobs obsolete by the year 2022, according to a new report. Sounds dreadful, but the same report goes on to predict the creation of 133 million new jobs over the same period. There's a lot of uncertainty right now about the future of work, and how emerging technologies will change the nature and availability of jobs in the coming years. It's tempting and wholly reasonable to believe, as so many do, that technological advances, particularly in the areas of robotics and AI, will result in massive unemployment. At the same, technological progress could also create new opportunities and completely new forms of employment.
Recently, it became known that Nasdaq is going to launch a new tool that is based on machine learning for its analytical hub. This tool will process the users data from the social networks, providing institutional investors with a new market analysis tool. However, Nasdaq specialists didn't give any direct answer for Bitnewstoday.com Apparently, this can only mean that Nasdaq AI is being tested now. Earlier in March this year, Thomson Reuters media company launched the updated MarketPsych Indices service, which makes the market forecasts by tracking for more than 2000 news sources and 800 social networks.
From virtual assistants like Siri and Alexa, to chatbots created by Facebook and Drift, AI is having a significant impact on the lives of consumers. A study from Statista showed that the number of consumers using virtual assistants worldwide is expected to exceed one billion in 2018. Additionally, a 2018 survey by Accenture projected that 37 percent of U.S. consumers will own a digital voice assistant (DVA) device by the end of 2018. It is readily apparent how AI-powered technology is making inroads into everyday life through DVAs and other consumer products, but AI is also having a transformative effect on an industry that impacts virtually all consumers and businesses: banking. Here are five ways that AI is already transforming the banking industry.
Any system where humans interact with technology involves a tradeoff: security versus accessibility. The more secure the system, the more difficult it is to access. This poses a dilemma for any organization facing pressure to embrace anytime, anywhere accessibility, the mobile workplace and real-time interaction with customers and employees--and that describes almost every organization today. Advances in artificial intelligence (AI)--and the millions of data points created by the Internet of Things--are starting to change the nature of this tradeoff, particularly where trust is part of the product or service. As AI systems learn more, they can be trained to suggest next best actions, automate some repetitive tasks and minimize the greatest risk: human error.
Most studies about the impact of artificial intelligence (AI) on jobs and the economy have focused on developed countries such as the United States and Britain. Through my work as a scientist, technology executive and venture capitalist in the US and China, I have come to believe that the gravest threat AI poses is to emerging economies. In recent decades, China and India have presented the world with two different models on how countries can climb the development ladder. In the China model, the nation leveraged its large population and low costs to build a base of blue-collar manufacturing. The country then steadily worked its way up the value chain by producing better and more technology-intensive goods.
SHANGHAI (Reuters) - U.S. technology giants, facing tighter content rules in China and the threat of a trade war, are targeting an easier way into the world's second largest economy - artificial intelligence. Google (GOOGL.O), Microsoft Inc (MSFT.O) and Amazon Inc (AMZN.O) showcased their AI wares at a state-backed forum held in Shanghai this week against the backdrop of Beijing's plans to build a $400 billion AI industry by 2025. China's government and companies may compete against U.S. rivals in the global AI race, but they are aware that gaining ground won't be easy without a certain amount of collaboration. "Hey Google, let's make humanity great again," Tang Xiao'ou, CEO of Chinese AI and facial recognition unicorn Sensetime, said in a speech on Monday. Amazon and Microsoft announced plans on Monday to build new AI research labs in Shanghai.
Member-owned financial services provider CUA is currently piloting a chatbot for its health insurance business that Head of Digital Innovation Melissa Wetheriff said helps customers move through the process of purchasing insurance. Speaking at D61 LIVE in Brisbane on Tuesday, Wetheriff said that CUA is pushing itself into emerging technologies such as AI, and is doing so with the help of partners, in particular fintechs. "Because we're a small organisation, or relatively small, we need to innovate through partnerships, whether that's with universities, corporates, or the fintech ecosystem," she explained. "In this situation, we're partnering with fintechs to be able to bring AI into the experience that we offer for our members." Specifically, CUA is working with AI-focused Flamingo and the Sydney-based firm's virtual sales assistant Rosie.
The algorithm used by a credit agency might be developed using data from pre-existing credit ratings or based on a particular group's loan repayment records. Alternatively, it might use data that is widely available on the internet - for example, someone's social media behaviour or generalized characteristics about the neighborhood in which they live. If even a few of our data sources were biased, if they contained information on sex, race, colour or ethnicity, or we collected data that didn't equally represent all the stakeholders, we could unwittingly build bias into our AI.