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Applications of Machine Learning and AI in Banking and Finance in 2023

Analytics Vidhya

Introduction Could the American recession of 2008-10 have been avoided if machine learning and artificial intelligence had been used to anticipate the stock market, identify hazards, or uncover fraud? The recent advancements in the banking and finance sector suggest an affirmative response to this question.

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Predictive Analytics Improves Trading Decisions as Euro Rebounds

Smart Data Collective

Predictive analytics technology has become essential for traders looking to find the best investing opportunities. Predictive analytics tools can be particularly valuable during periods of economic uncertainty. Predictive Analytics Helps Traders Deal with Market Uncertainty. Analytics Vidhya, Neptune.AI

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5 Ways Data Analytics Helps Us Understand the Student Lending Crisis

Smart Data Collective

Sarah Riley, a research economist with the University of North Carolina wrote an paper in 2020 titled Predictive Analytics for Reducing Student Loan Default. As the title suggests, it is geared towards using data analytics to anticipate the risk of a borrower defaulting on their student loans.

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The New Normal for FP&A: Scenario Planning

Jedox

We had the Financial Crisis/Recession of 2008, where hopefully the comment “Well that will never happen” has been struck from our lexicon and is now considered a punishable capital offense. The 2008 economic crisis was a watershed event for FP&A teams and scenario planning.

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Smarten Augmented Analytics Receives CERT-IN Certification for Its Products and Services!

Smarten

It was initiated in 2004 by the Department of Information Technology for implementing the provisions of the 2008 Information Technology Amendment Act.

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Make Every Sprint Count with DevOps Analytics

Sisense

DevOps first came about in 2007-2008 to fix problems in the software industry and bring with it continuous improvement and greater efficiencies. Once you’ve started to measure DevOps KPIs, the next step will be to start implementing changes in the process by becoming predictive with your analytics. But is that really true?

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Data Mining – useful or not?

Jen Stirrup

Historical analytics can help to support the marketing process, which can also be augmented by predictive analytics, alternatively known as data mining, which can help to identify patterns in customer behavior. The customer behavior patterns found can be used to make more informed, quicker decisions about targeting customers.