Lifeboat Foundation

A study in which machine-learning models were trained to assess over 1 million companies has shown that artificial intelligence (AI) can accurately determine whether a startup firm will fail or become successful. The outcome is a tool, Venhound, that has the potential to help investors identify the next unicorn.

It is well known that around 90% of startups are unsuccessful: Between 10% and 22% fail within their first year, and this presents a significant risk to venture capitalists and other investors in early-stage companies. In a bid to identify which companies are more likely to succeed, researchers have developed machine-learning models trained on the historical performance of over 1 million companies. Their results, published in KeAi’s The Journal of Finance and Data Science, show that these models can predict the outcome of a company with up to 90% accuracy. This means that potentially 9 out of 10 companies are correctly assessed.

“This research shows how ensembles of non-linear machine-learning models applied to big data have huge potential to map large feature sets to business outcomes, something that is unachievable with traditional linear regression models,” explains co-author Sanjiv Das, Professor of Finance and Data Science at Santa Clara University’s Leavey School of Business in the US.

It’s not just salespeople, traders, compliance professionals and people formatting pitchbooks who risk losing their banking jobs to technology. It turns out that private equity professionals do too. A new study by a professor at one of France’s top finance universities explains how.

Professor Thomas Åstebro at Paris-based HEC says private equity firms are using artificial intelligence (AI) to push the limits of human cognition and to support decision-making. Åstebro says t he sorts of people employed by private equity funds is changing as a result.

Åstebro looked at the use of AI systems across various private equity and venture capital firms. He found that funds that have embraced AI are using decision support systems (DSS) across the investment decision-making process, including to source potential targets for investments before rivals.

Sri Lanka has declared a state of emergency as the food crisis worsened after private banks ran out of foreign exchange to finance imports.

And threatening to put traditional banks out of business. What would a world without banks look like, and would you even miss them? https://econ.st/3s76sYS

The business of private survival shelters has grown during the pandemic. They’re not just for survivalists and doomsday preppers anymore. Bunkers buried in backyards or remote landscapes are capable of withstanding nuclear fallout and hurricanes, as well as violent conflict.

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Researchers uncover new backdoor used by FIN8 to target financial institutions.

El Salvador began installing Bitcoin ATMs, allowing its citizens to convert the cryptocurrency into U.S. dollars and withdraw it in cash, as part of the government’s plan to make the token legal tender.

The government will install 200 of the teller machines to initially accompany its digital wallet called Chivo, a local slang term for ‘cool,’ President Nayib Bukele said on Twitter. Transactions will be commission free, he said, adding that there will also be 50 financial branches across the country for withdrawing or depositing money.

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These cloned camels were created with cells from a ‘zoo’ of frozen specimens. The cell bank could one day be used to help preserve endangered species.

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Michael is also part of a group of wealthy Indonesian scions that have in the past decade dabbled in the country’s vibrant tech sector by investing in home-grown giants and start-ups, be it in the form of money, resources, know-how, or access.

Industry stakeholders say family-owned corporate venture capital firms have played an important role in growing the country’s US$44 billion digital economy.