Get the latest information on how financial markets are using advanced in-database analytics for real-time risk aggregation. Advanced in-database analytics allows the bank to run custom XVA algorithms at scale with the GPUs massive parallelization. This approach allows banks to move counterparty risk analysis from batchundefinedovernight to a streamingundefinedreal-time system for flexible real-time monitoring by traders, auditors, and management. Real-world examples and insights will be provided, including how a multinational bank is using Kinetica as a real-time risk modeling engine running on public cloud-based, Microsoft Azure GPU instances. The bank can now handle time-sensitive, compute-intensive risk computations to project years into the future across hundreds of variables.