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Banking & Finance

Data and AI Will Drive Autonomous Future in Banking


The priorities of every financial institution have been impacted by the pandemic, with some firms believing that a greater investment needs to be made in technology, others focusing on new products and services, and still others wanting to improve components of trust and security. The foundation of each of these priorities is a combination of a need to improve customer experiences while managing operating costs in an uncertain economic environment. The reassessment of corporate priorities is being done with the backdrop of consumer standards for engagement that have moved away from one-size-fits-all transactional experiences to contextualized experiences that are personalized across multiple touchpoints and channels. At the same time, as consumers widen their scope of understanding of what can be achieved with digital engagement, more of them will be willing to pay more for services that enhance their financial lifestyle through real-time insights, proactive recommendations and simplified engagement. According to Salesforce's Trends in Financial Services report, there is an urgent need for the industry to transform data and insights into actionable outcomes that are consumer-centric.

Banks need to strike the right balance for digital transformation

MIT Technology Review

Every financial institution is looking to digital transformation to meet rising customer expectations for speed and convenience, lower its operating cost, and fend off competition, including from tech companies moving into financial services. Some are spending over 10% of yearly revenue on technology investments, according to Bloomberg. "This is a huge investment and most financial institutions cannot support this for the long term," says Michael Fei, SME banking CEO at OneConnect Financial Technology, an associate of Ping An Insurance. The covid-19 pandemic has revealed how even financial institutions that considered themselves digitally advanced are, in reality, still wedded to analog processes along the chain of processing. "For many financial institutions, this has been a wake-up call," says Fei. "In the past, many had thought that if they have an online portal and a mobile application then that's enough. But now they've realized it's not. Some banks have online portals and mobile apps where you can apply for loans, but they still need to send items to the customer and carry out on-site inspection before they can process the loans, which hasn't been possible during covid. Banks have had to reshape and redesign the whole process of their lending products."

Why It's Time to Embrace AI and Prepare for the Feeling Economy - Real Leaders


The first wave of artificial intelligence (AI) has already replaced humans for repetitive physical tasks like inspecting equipment, manufacturing goods, repairing things, and crunching numbers. That shift started way back with the Industrial Revolution. This gave rise to our current Thinking Economy, where employment and wages are more tied to workers' abilities to process, analyze and interpret information to make decisions and solve problems … Just like the industrial revolution automated physical tasks by decreasing the value of human strength and increasing the value of human cognition, AI is now reshaping the landscape and ushering in a Feeling Economy. What characterizes this emerging economy? Consider, for example, the role of a financial analyst, which seems pretty quantitative and thinking-oriented.

'Augmented creativity': How AI can accelerate human invention


In 2012, economist Robert Gordon published a controversial paper in which he argued that economic growth was largely over, due in no small part to our failure to maintain the engines of innovation in recent decades. A study from the Stanford Institute for Economic Policy Research supported his general thesis and argued that while we're spending even more money on creativity and innovation, our returns are flatlining. And this investment is not only in dollars, as the research revealed roughly 20 times as many people work in R&D today as did in 1930. Why has creating things become so difficult? Researchers from Northwestern University attempt to answer this in a paper that shows a growing percentage of today's creation is what's known as recombination.

Science's Demons, from Descartes to Darwin and Beyond

The New Yorker

It is difficult to count demons. In the Gospel of Mark, when Jesus meets a man on the far side of the Sea of Galilee who is possessed, he asks the demon to identify itself. It replies: "My name is Legion, for we are many." The thirteenth-century German abbot Richalmus suspected the number of demons was incalculable, as numerous as grains of sand in the sea. Three centuries later, when the Dutch physician Johann Weyer composed his demonology, he identified some sixty-nine demons by name, who commanded millions of others: at least eleven hundred and eleven distinct legions, each with six thousand six hundred and sixty-six demons.

Why Artificial Intelligence Will Outsmart us, Beat us and Replace us


Wisdom is not algorithmic…You can't have an if this than that algorithm that actually equals wisdom. And if you can, than we are just an intermediate boot loader for the A.I's that are better creatures than us -- Daniel Smachtenberger Is first and foremost a marketplace. Now give this market self-learning A.I-driven tools, ever-increasing capacity for the aim of profit-making, and voila, here is where we are. Tech companies have become more powerful than nation-states. We are faced with a market dynamic that is unprecedented in human history.

Top 10 Computer Vision Funding and Investments of 2020


Computer vision is an artificially intelligent technology that is rapidly growing in popularity. As this tech deals with how computers can reap high-level understanding from digital images or videos, it is becoming a part of people's everyday life. Besides having a significant impact on business transformation and consumers' lives, computer vision is starting to disrupt the global industry. The explosion in visual data, enhanced neural networks, and low-cost chips are some of the growth factors of computer vision. As a fast-evolving technology space, computer vision has attracted a lot of exposure and a great amount of investment.

The Year Of The SPAC And What It Means For Hardware


CBS MarketWatch declared 2020: The Year of the SPAC (Special Purpose Acquisition Corporation). A record 219 companies went public through this fundraising vehicle that uses a reverse merger with an existing private business to create a publicly-listed entity. This accounted for more than $73 billion dollars of investment, providing private equity startups a new outlet to raise capital and provide shareholder liquidity. According to Goldman Sachs, the current trends represents a "year-over-year jump of 462% and outpacing traditional IPOs by $6 billion." In response to the interest in SPACs, the Securities and Exchange Commission agreed last week to allow private companies to raise capital through direct listings, providing even more access to the public markets outside of Wall Street's traditional institutional gatekeepers.

What the hell is an AI factory?


If you follow the news on artificial intelligence, you'll find two diverging threads. The media and cinema often portray AI with human-like capabilities, mass unemployment, and a possible robot apocalypse. Scientific conferences, on the other hand, discuss progress toward artificial general intelligence while acknowledging that current AI is weak and incapable of many of the basic functions of the human mind. But regardless of where they stand in comparison to human intelligence, today's AI algorithms have already become a defining component for many sectors, including health care, finance, manufacturing, transportation, and many more. And very soon "no field of human endeavor will remain independent of artificial intelligence," as Harvard Business School professors Marco Iansiti and Karim Lakhani explain in their book Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World.

Intro to Fintech: Artificial Intelligence


Even though the two terms are often used interchangeably, AI and Machine Learning are two different things, and though very similar have slightly different ways of operating. Artificial Intelligence is actually the umbrella that Machine learning comes under, making ML just one type of AI. To put it as simply as possible, ML refers to any analytics that "learn" patterns in data without being guided by a human analyst. So, for example, you need your machine to be able to tell the difference between pictures of dogs and cats. Initially, you would present the bot with a set of pictures and tell it that one is a cat and the other is a dog.