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In this solution, we offer a novel approach to sustainable finance by combining NLP techniques and news analytics to extract key strategic ESG initiatives and learn companies' commitments to corporate responsibility
Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Data Intelligence Platform.
Use Databricks to improve the Claims Management process for faster claims settlement, lower claims processing costs and quicker identification of possible fraud
Preempt fraud with rule-based patterns and select ML algorithms for reliable fraud detection. Use anomaly detection and fraud prediction to respond to bad actors rapidly.
Ingest sample retail data, build visualizations to explore past purchase behavior and use machine learning to predict the likelihood of future purchases
Shows how banks can modernize their risk management practices by back-testing, aggregating and scaling simulations by using a unified approach to data analytics with the Lakehouse.
Translating text attributes (like name, address, phone number) into quantifiable numerical representations Training ML models to determine if these numerical labels form a match Scoring the confidence of each match
In this series of notebooks centered around geospatial analytics, we demonstrate how Lakehouse enables organizations to better understand customers behaviours, no longer based on who they are, but how they bank, no longer using a one-size-fits-all rule but a truly personalized AI
This series of notebooks shows how the Lakehouse for Financial Services enables banks, open banking aggregators and payment processors to address the challenge of merchant classification
Nasdaq Data Link Digital Assets is a part of Nasdaq's Investment Intelligence suite of products, designed to provide significant value to customers in making informed decisions. As the creator of the world's first electronic stock market, Nasdaq technology powers more than 70 marketplaces in 50 countries, and one in ten of the world's securities tr
Example scripts for the Python scripting API of the SimVascular FSI simulation tool wrote during Summer 2019 and Summer 2020 internships @ Stanford CBCL.
We demonstrate how FSI can leverage geospatial and graph analytics to anonymize card transaction data and monetize their assets to potential clients securely via delta sharing capability
In this solution accelerator, we demonstrate how generative AI, retrieval augmented generation (RAG) and multi stage reasoning can be used to better navigate through the complexities of regulatory filings, bringing more transparency for companies to disclose their societal and environmental impacts.
Backend service for loading financial data from multiple sources, including Yahoo Finance, FRED, Binance (crypto assets), Reddit (social media posts), and CoinGecko (stablecoin market caps), plus financial news processing.