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banking & finance

Practical Machine Learning Projects In Finance Industry


Machine learning in finance is now considered a key aspect of several financial services and applications, including managing assets, evaluating levels of risk, calculating credit scores, and even approving loans. Machine learning is a subset of data science that provides the ability to learn and improve from experience without being programmed. As an application of artificial intelligence, machine learning focuses on developing systems that can access pools of data, and the system automatically adjusts its parameters to improve experiences. Computer systems run operations in the background and produce outcomes automatically according to how it is trained. Machine learning tends to be more accurate in drawing insights and making predictions when large volumes of data are fed into the system.

The LATAM Hub for Artificial Intelligence


Note: First 100 subscribers receive a free lifetime subscription. In May of 2018, a "center of excellence" for artificial intelligence opened in Medellín, Colombia. According to an article by Jared Wade, the center comes from a partnership between US-based Institute for Robotic Process Automation and Artificial Intelligence (IRPA AI) and Medellín-based startup incubator, Ruta-N. The launch was facilitated by the Agency for Cooperation and Investment in Medellín (ACI) with the goal of fostering specialized skills in the local labor force, and is part of a larger plan to promote research, development, entrepreneurship, and innovation. This is good news, but I'm biased.

Spring Oaks Capital Continues its Rapid Expansion with the Addition of Paul Hurlocker as Chief Technology Officer


Spring Oaks Capital, LLC has hired Paul Hurlocker as Chief Technology Officer. Paul will be based in Richmond, Virginia, and report to President & CEO Tim Stapleford. Paul joins from Capital One where he served as the Vice President of the Center for Machine Learning, an in-house consultancy and center of excellence for machine learning product delivery, innovation, education, research and development, and partnership across the business. Paul joined Capital One through the acquisition of Notch, a machine learning consulting firm that Paul founded in 2014. Prior to founding Notch and serving as its Chief Executive Officer until its 2018 acquisition by Capital One, Paul served in senior software development roles at Red Hat, Affinion, Plan- G, and other leading technology firms.

Knowledge Graph Conference, join the leading researchers online, May 3-6 - KDnuggets


KGC is Community Driven and built to create space for interaction and networking. KGC crafts dedicated time slots enabling access to conference speakers into the program. The program includes multiple special events, such as the second KGC Startup Investor pitch, a joint industry survey results on Knowledge Graphs and wellness events such as meditation and yoga!

Robotics ETFs hit by 'massive' outflows in March


Visit our ETF Hub for investor news and education, market updates and analysis and easy-to-use tools to help you select the right ETFs. Robotics-focused exchange traded funds have seen "massive" outflows in recent weeks as one of the hottest trends of the past six months threatens to implode. The sharp reversal is starkest in Europe, where robotics and automation-themed ETFs chalked up inflows of $753m between September 2020 and February, according to data from Global X, a New York-based ETF manager. However, a record $506m of this money was pulled out of the market in March alone, cutting assets 8.5 per cent to $5.4bn. The US robotics segment also witnessed "significant" outflows of $363m, pulling sector-wide ETF assets down 6.1 per cent to $8.9bn, according to Global X.

World's most advanced AI system installed


New Zealand's most powerful supercomputer for artificial intelligence applications has been installed at the University of Waikato as part of its commitment positioning New Zealand as a world leader in AI research and development. The NVIDIA DGX A100 is the first computer of its kind in New Zealand and is the world's most advanced system for powering universal AI workloads. The machine has been referred to as the Ferrari of computing because of how fast it can rapidly and efficiently process massive amounts of data, allowing students and researchers at the University to process at lightning-fast speeds, enabling machine learning and artificial intelligence that can solve problems from addressing climate change to managing our biodiversity. Machine learning uses algorithms to explore huge data sets and create models that provide answers or outcomes mirroring human decision making. Models can be trained to recognise things like patterns, facial expressions, and spoken words – or they can find anomalies like credit card fraud.

Advancing Machine Learning With DevOps


Allowing failure is one of the most basic prerequisites for innovation. If you are not prepared to fail, you will not be able to create anything new. As the German CTO of a Japanese IT service provider with a strong culture focused on innovation, I myself am deeply convinced of this. However, if only one of ten machine learning projects ever go live, something is definitely wrong. After all, machine learning is one of the central applications of artificial intelligence (AI) and the basis of numerous future technologies such as autonomous driving, smart cities, and the Industrial Internet of Things (IIoT).

China's Meituan Seeks $10 Billion War Chest for Drones and Driverless Cars WSJD - Technology

The Hong Kong-listed company is selling as much as $7 billion of stock and $3 billion of convertible bonds, according to a term sheet Monday that was seen by The Wall Street Journal. The huge capital-raising is considerably bigger than the $4.2 billion Meituan raised in its 2018 initial public offering and suggests there is still a healthy appetite among investors for stock in Chinese technology companies, even though shares in Meituan and many peers have pulled back recently. Earlier this month, Prosus NV raised $14.6 billion by selling down a small part of its stake in Tencent Holdings Ltd., the internet and videogaming giant. Meituan plans to use some of the net proceeds on projects such as researching and developing autonomous delivery vehicles, drone deliveries and other cutting-edge technology, the term sheet said. In a separate statement Monday, the company unveiled a new generation of self-driving delivery cars that it said were smarter and safer than previous versions, with a longer battery life and capable of carrying heavier loads.

Modular Machine Learning - Best Of Both Worlds?


A Webinar By Joseph Simonian Abstract: After reviewing some differences between traditional statistics & data science, we present a modular machine learning framework for model validation which blends the two paradigms. Model validation is set up as a sequence of procedures, in which the output from one procedure serves as the input to another procedure within a single validation framework. An econometric model is used in the first module to classify data in an economically intuitive way. Proceeding modules apply data science techniques to evaluate the predictive characteristics of the model components. We apply the framework to the fundamental law of active management, a well-known formal characterization of portfolio managers alpha generation process.

Where is debt collection heading in India? Towards less muscle and more AI


You can test this hypothesis in a most unlikely place to roll out a new technology: the Indian countryside. The setting is perhaps not as odd as it seems, with about 5% to 10% of the country's farmers not repaying their tractor loans on time. The explanations for tardiness range from failed crops to medical emergencies and strategic defaults in anticipation of state-mandated debt waivers, a regular feature of the political economy. But delinquency often stems from more mundane reasons: Borrowers forget their due dates, or fail to withdraw cash to pay the nonbank financiers who provide the bulk of loans for farm equipment purchases. Like in most emerging markets, these last-mile hurdles pose a frustratingly complex challenge to India's creditors.