Unifying Data Pipelines, Business Analytics and Machine Learning with Apache Spark™

Financial intermediation is a risky business. The core function of an FSI is to protect the value of assets, identify emerging risks and mitigate losses. Risk management practices are heavily scrutinized by regulators and the cost of failure is significant. Risk management today is quickly evolving from a cost of doing business to a driver of innovation. Data standardization, automation, and analytics enable superior risk management and unlocks innovative new business models such as superior underwriting performance. Databricks helps customers unify datasets into a single source of truth, streamline data ingestion and enable AI-driven risk-management techniques.

Join this on demand financial services virtual session to learn how unified data analytics can bring data science, business analytics and engineering together to accelerate your data and ML efforts. This virtual workshop will give you the opportunity to learn about:

• Using Delta Lake for a curated 360 degree view of your risk portfolio
• Tracking experiments and registering risk models through MLflow capabilities
• Leveraging the power of Apache Spark™ for massively distributed Monte Carlo simulations
• Slicing and dicing through your risk exposure using collaborative notebooks and SQL
• Detecting emerging threats using alternative data to have a more agile approach to risk management

AGENDA AT A GLANCE:

• Opening Remarks - Unifying Data Science and Data Engineering
• Real life challenges doing risk analytics at scale
• Demo: Value-At-Risk (VAR) calculations at scale - ETL
  
• Demo: Monte Carlo simulations, risk aggregation, and backtesting
  
• Wrap Up | Q&A