Banks have widely built data lakes – which often lack a semantic “understanding” of data points and their interconnections. Analytics and reporting require manual model definitions by data scientists – largely limiting capabilities and speed of analytics.
Establish a semantic core graph and scale it up with ontologies, coveringbusiness structures and models as well as external graphs, all engineered decentralized.
(e.g., market segments, products, financial market data)
Add market-moving, up-to-date topics, market actors, and relationships based on market intelligence and news monitoring.
(e.g., autonomous driving, political change)
Apply real-time graph and event analytics to derive actionable insights and recommendations.
(e.g., trending topics, trigger events, sentiment)
Apply Artificial Intelligence to the core graphand create a truly comprehensive, agile Bank Knowledge Base ready to power analytics, business applications, and advisory processes with reliable but dynamic models and up-to-date information.