Remove Events Remove Forecasting Remove Risk Management
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9 Great Reasons to Join the DataRobot AI Experience Virtual Event Jun 7-8

DataRobot Blog

Join DataRobot and leading organizations June 7 and 8 at DataRobot AI Experience 2022 (AIX) , a unique virtual event that will help you rapidly unlock the power of AI for your most strategic business initiatives. Join the virtual event sessions in your local time across Asia-Pacific, EMEA, and the Americas. Join DataRobot AIX June 7–8.

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The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

Errors in analysis and forecasting may arise from any of the following modeling issues: using an inappropriate functional form, inputting inaccurate parameters, or failing to adapt to structural changes in the market. In other words, extreme events occur far more frequently than predicted by the normal distribution.

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Manage the Demand of Stress Testing in Financial Services

Cloudera

Risk management is a highly dynamic discipline these days. Simudyne, a Cloudera partner, provides software that makes it easy for institutions to create the models and run the simulations and scenarios they need to better predict and anticipate events including economic and market events.

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How to Manage Risk with Modern Data Architectures

Cloudera

Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs. Financial institutions can use ML and AI to: Support liquidity monitoring and forecasting in real time.

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Mitigating the impact of climate change in insurance and other financial services  

IBM Big Data Hub

As the effects of climate change intensify, extreme weather events are becoming increasingly frequent and severe. The US experienced 25 extreme weather events in 2023, each causing losses of over USD 1 billion, with a total cost of USD 73.8 These climate events have a huge potential impact on financial institutions.

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How generative AI will revolutionize supply chain 

IBM Big Data Hub

From demand forecasting to route optimization, inventory management and risk mitigation, the applications of generative AI are limitless. Generative AI, with its ability to autonomously generate solutions to complex problems, will revolutionize every aspect of the supply chain landscape.

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What is Data Lineage? Top 5 Benefits of Data Lineage

erwin

For example, the marketing department uses demographics and customer behavior to forecast sales. In the event of a change in data expectations, data lineage provides a way to determine which downstream applications and processes are affected by the change and helps in planning for application updates.