Subject archive for "finance"

Data Science

Financial Services and Insurance: Driving Tomorrow’s Data Science Trends

Last week Domino celebrated data science innovators driving breakthroughs in health and life sciences. This week we announce a new slate of innovators in the Financial Services and Insurance edition of the Data Science Innovator’s Playbook, available now as a free download. As before, each of its top data science innovation leaders in the financial services and insurance industries share insights on their work, careers, and the data science profession. The playbook includes seven profiles, the first being of Dr. Tiffany Perkins-Munn.

By Domino Data Lab5 min read

financial services icons in a data science environment
Data Science

Deep Learning & Machine Learning Applications in Financial Services

In the last few years, machine learning and deep learning have become a core part of fields like healthcare, retail, banking, and insurance. This list can go on indefinitely—there's almost no field where machine learning (ML) is not applied to improve the overall efficiency and accuracy of systems. As the world's economy has rapidly grown, so has the need to do things automatically.

By Gourav Singh Bais39 min read

Perspective

4 Ways to Better Manage and Govern Financial Services and Insurance Models

The financial services industries are starting to realize the full import of the fact that, like household chores like dishwashing and garden work, ML models are never really done. Rather, AI and ML models need to be monitored for validity, and often, they also need to be re-explained and re-documented for regulators. So the spotlight is on model risk management (MRM) and governance (MRG), two related critical processes for financial services and insurance companies, and the importance of these two disciplines is only expected to grow.

By Nathan Greenhut9 min read

Data Science

Succeeding with Alternative Data and Machine Learning

Perhaps the biggest insight in feature engineering in the last decade was the realization that you could predict a person's behavior by understanding the behavior of their social network. This use of non-traditional social data has driven a significant amount of economic growth as it revolutionized the accuracy and applicability of models.

By Grigoriy50 min read

Data Science

Data Science in Banking: Past, Present, and Future

This was one of many fascinating sessions at the Data Science Pop-up in Austin, Texas. Don't miss the next opportunity to learn from the world's leading data scientists at the Data Science Pop-up Los Angeles on September 14, 2016. See the speaker lineup and get your tickets today.

By Grigoriy1 min read

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