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[2014 Shanghai Forum] Ju Jiandong "RMB Exchange Rate and Capital Flow"
| May 20, 2015
NCB Capital was launched in 2007 as the investment banking arm of The National Commercial Bank, the largest bank in Saudi Arabia, to provide investment banking services to individual, institutional and corporate clients in the Kingdom...
Article | April 20, 2020
Here are ten steps to defining a data strategy based on a data capability maturity assessment, for a Financial Institution, Identify and Simplify Maturity models, and customize the yardstick as well as benchmarks based on local study and future organization strategy. Conduct workshop with leaders and grassroots to sensitize the assessment and questionnaires.
From stock market swings and billions wiped off of the airlines, hotels, transportation revenues to drug, soap or iPhone replacement shortages – the coronavirus outbreak is taking its toll on many business aspects of life. Euler Hermes calls this a "quarantined trade". The company's analysts estimated that Covid-19 costs $320bn of trade losses every quarter. But what about fintech? It’s not immune to the virus either. As the side effects of Covid-19 will be unfolding in the weeks to come, we’ll see some fintech or finance companies taking hits. But other companies or solutions will be gaining traction.
Sales cycles for smaller teams had long been changing, even before a global pandemic transformed everything about the way that businesses and customers interact. In response to an increasingly digital customer base, teams have adjusted not only how they communicate, but where they advertise and how they manage leads. And many of these changes have actually left them better prepared to deal with the impacts of COVID-19, even as they face layoffs, fewer conversions, and increased customer churn.
Machine learning has had fruitful applications in finance well before the advent of mobile banking apps, proficient chatbots, or search engines. Given the high volume, accurate historical records, and quantitative nature of the finance world, few industries are better suited for artificial intelligence. There are more uses cases of machine learning in finance than ever before, a trend perpetuated by more accessible computing power and more accessible machine learning tools (such as Google’s Tensorflow).
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