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Monsoon CreditTech becomes part of Mastercard's Start Path program, secures new funding

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Monsoon CreditTech has become one of the seven fintech companies from across the world and the only one from India selected by Mastercard Start Path, part of Mastercard Labs, to be part of its startup engagement program. Start Path is designed to help later stage startups scale their business. This puts Monsoon in an elite club of companies and will give Monsoon access to Mastercard's global network of customers and subject matter experts, bringing Monsoon's machine learning technology to global markets outside India. Monsoon says it has also recently closed a new round of undisclosed amount in funding from strategic institutional and individual investors from across the globe ranging from geographies such as USA, UK, UAE and India. The digital shift As the volume of data available for analysis grows and computational power becomes cheaper, banks and financial institutions are beginning to realize the potentially transformational benefits of embracing Artificial Intelligence (of which machine learning is a subset).


Would you trust an algorithm to diagnose an illness?

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Leveraging blockchain to make machine learning models more accessible - Microsoft Research

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Significant advances are being made in artificial intelligence, but accessing and taking advantage of the machine learning systems making these developments possible can be challenging, especially for those with limited resources. These systems tend to be highly centralized, their predictions are often sold on a per-query basis, and the datasets required to train them are generally proprietary and expensive to create on their own. Additionally, published models run the risk of becoming outdated if new data isn't regularly provided to retrain them. We envision a slightly different paradigm, one in which people will be able to easily and cost-effectively run machine learning models with technology they already have, such as browsers and apps on their phones and other devices. Through this new framework, participants can collaboratively and continually train and maintain models, as well as build datasets, on public blockchains, where models are generally free to use for evaluating predictions.


Bankers are rushing to take Oxford University's fintech courses before robots take their jobs Markets Insider

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Bankers are rushing to take Oxford University's courses on fintech, blockchain strategy, algorithmic trading, and artificial intelligence before robots take their jobs. More than 9,000 people from upwards of 135 countries have taken the online open courses, which focus on digital transformation in business, at the university's Saïd Business School, a spokesperson told Markets Insider. The fintech course, the first of five to be launched, has run 12 times and attracted nearly 4,300 students in less than two years. The average age of participants across the courses is 39, and two-thirds of them came from the financial services sector, suggesting experienced professionals are returning to school to understand how their industry is being disrupted and learn the skills needed to weather the changes. Bankers' fears of being replaced by robots are well founded.


Analysis Why Machine Learning Hasn't Made Investors Smarter

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Hedge funds have been in the doldrums and face mounting pressure to justify their fees. Will artificial intelligence come to the rescue? A growing number of hedge funds are putting money behind the idea that a branch of AI called machine learning could provide a way to get back on top. A software program that searches for regularly occurring patterns in more data than even the most sleep-deprived junior analyst could examine, and then tests its hypotheses against even more data. What can satellite shots of mall parking lots tell you when combined with in-store sales data?


AI Exponential Trend to Super Machine Intelligence Future Singularity

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Whilst most readership interest is in my regular stock market in-depth analysis that tend to conclude in detailed trend forecast usually covering at least the next 2-3 months and where possible much longer. However, whilst it is useful to know the probable short-term direction of the stock market for trading, accumulation (investing) and distribution (banking profits) purposes, but frankly, I think most people get overly carried away if not obsessed with seeking out short-term market direction. For instance if you have followed my articles for the past decade or so, then you should see a pattern in that trends PERSIST, i.e. stocks have been in a bull market since March 2009 and ever since then EVERY article I have written and video I have produced has concluded that as a consequence of the exponential inflation mega-trend that humanity has been on that this bull market could run for far longer and higher than anyone, including I can imagine. So what does one do when faced with a market correction, flash crash, even technical bear markets (20%) drops? I can understand that many reading this will be skeptical, despite my market analysis track record which speaks for itself.


mtes Neural Networks And DTCO Announce Their Partnership On CitiOS Project

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Japan's mtes Neural Networks and DTCO announced their partnership to promote the "CitiOS Project", combining structural health monitoring (SHM) and blockchain technology to monitor structural changes in infrastructures such as buildings, stations, railways, etc. CitiOS can significantly improve public safety for the areas that have suffered from earthquakes. Earthquakes has always been one of the biggest security issues facing Taiwan and Japan. The damage to infrastructures generated by earthquakes has often caused unacceptable casualties and an irreparable lost in property value. CitiOS will predict whether infrastructures changes in time and take necessary measures to overcome various defects. Moreover, with the aging of population in Japan, they can no longer rely entirely on manpower to manage urban infrastructures.


Blockchain for KYC: As a FinTech Problem Solver - Cygnet

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The most significant fears for financial institutions and banks are regulatory compliances. In the past, regulation was seen as a barrier to enter into Financial Services. Compliances were complex, difficult to comply with, and impossibly intricate for new organizations to adopt. It is a mandate for financial institutions to clearly identify and create a risk profile for each of their customers. Let's think of a situation, where a financial organization's KYC (Know-your-customer), which is a critical part of client onboarding, fails to show up a suspicious transaction done by another financial institution due to insufficient validation of the primary documents.


Increasing Demand for Cognitive Computing Market to Push Global Market Revenue Growth During 2016 – 2024 – Amazing Newspaper

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In the ever changing world of information technology, business organizations are left with humongous amount of data with them. This data includes very critical information for business use, but business organizations are only able to utilize 20% of whole data available with them with the use of traditional data analytics technology. To process and interpret the reaming 80% of the data that is in the form of videos, images, and human voice (also called as dark data), there is a need of cognitive computing systems. Cognitive computing systems are typical combination of hardware and software that constitute natural language processing (NLP) and machine language, and have capability to collect, process, and interpret the dark data available with business organizations. Cognitive computing systems works exactly the phenomena of how a human brain works.


Artificial Intelligence is Primed to Disrupt the Health Care Industry

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Artificial intelligence (AI) is one of the prime technologies leading the wave of disruption that is going on within the health care sector. Recent studies have shown that AI technology can outperform doctors when it comes to cancer screenings and disease diagnoses. In particular, this could mean specialists such as radiologists and pathologists could be replaced by AI technology. Per an article by the Association of American Medical Colleges, "a New England Journal of Medicine article predicted that'machine learning will displace much of the work of radiologists and anatomical pathologists,' adding that'it will soon exceed human accuracy.' That same year, Geoffrey Hinton, PhD, a professor emeritus at the University of Toronto who also designs machine learning algorithms for Google (and who received the Association for Computing Machinery's A.M. Turing Award, often called the Nobel Prize of computing, in 2019), declared, 'We should stop training radiologists now.'"