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Machine Learning and Portfolio Risk Management

#artificialintelligence

By harnessing troves of historical data, asset and wealth management firms are now exploring AI solutions to improve their investment decisions. Since the market crash in the late 2000s, business regulators and consumers have been more wary about risks seeing as some are still trying to recover from it. Machine learning seeks to provide a paradigm shift in investment management for financial institutions so that they do not find themselves in such a situation again. Over the years, technology has helped companies make sense of the massive amounts of data they possess by analyzing them before reaching final decisions. For example, blockchain allows companies to check the validity of transactions before they are even completed.


Top 7 Data Science Use Cases in Finance

@machinelearnbot

In recent years, the ability of data science and machine learning to cope with a number of principal financial tasks has become an especially important point at issue. Companies want to know more what improvements the technologies bring and how they can reshape their business strategies. To help you answer these questions, we have prepared a list of data science use cases that have the highest impact on the finance sector. They cover very diverse business aspects from data management to trading strategies, but the common thing for them is the huge prospects to enhance financial solutions. Risk management is an enormously important area for financial institutions, responsible for company's security, trustworthiness, and strategic decisions.


Top 7 Data Science Use Cases in Finance

@machinelearnbot

In recent years, the ability of data science and machine learning to cope with a number of principal financial tasks has become an especially important point at issue. Companies want to know more what improvements the technologies bring and how they can reshape their business strategies. To help you answer these questions, we have prepared a list of data science use cases that have the highest impact on the finance sector. They cover very diverse business aspects from data management to trading strategies, but the common thing for them is the huge prospects to enhance financial solutions. Risk management is an enormously important area for financial institutions, responsible for company's security, trustworthiness, and strategic decisions.


Top 7 Data Science Use Cases in Finance – ActiveWizards: machine learning company – Medium

#artificialintelligence

In recent years, the ability of data science and machine learning to cope with a number of principal financial tasks has become an especially important point at issue. Companies want to know more what improvements the technologies bring and how they can reshape their business strategies. To help you answer these questions, we have prepared a list of data science use cases that have the highest impact on the finance sector. They cover very diverse business aspects from data management to trading strategies, but the common thing for them is the huge prospects to enhance financial solutions. Risk management is an enormously important area for financial institutions, responsible for company's security, trustworthiness, and strategic decisions.


Preparing For AI Ethics And Explainability In 2020

#artificialintelligence

How do we balance the potential benefits of deep learning with the need for explainability? People distrust artificial intelligence and in some ways this makes sense. With the desire to create the best performing AI models, many organizations have prioritized complexity over the concepts of explainability and trust. As the world becomes more dependent on algorithms for making a wide range of decisions, technologies and business leaders will be tasked with explaining how a model selected its outcome. Transparency is an essential requirement for generating trust and AI adoption.