Operational risk losses cost financial institutions tens of billions of dollars every year. Common issues include manual processes and data inconsistency across internal systems that produce misaligned results all throughout the trade operations process.
Linedata Analytics Service addresses these challenges with data driven intelligence for portfolio operations. It cuts through the noise to help you prevent losses today and adapt for safer, more cost-effective operations in the future. The Service helps your team benefit from new data insights from across all your systems using AI for capital markets combined with data visualization and backed by Linedata’s two decades of experience.
Linedata Analytics Service delivers easy-to-use, actionable insights, enabled by advanced machine learning models, data sourcing and integration, and secure cloud hosting. Current use cases include:
Linedata Analytics Service derives data driven intelligence for portfolio operations from past issues, business decisions, and relevant industry data and events to help you predict and prevent future problems – saving you time and money.
Linedata provides a fully featured cloud solution, so you can scale up quickly as your business grows.
Our consumption-based pricing model means you only pay for the services you need.
Our experts are transparent and collaborative across your internal teams. Data analytics as a Service includes model creation and maintenance, user interface (UI) support, along with data delivery and integration, so you only have one relationship to manage.
Real-time alerts help you find and address daily issues to prevent losses. Detailed analytics and insights enable your team to make fundamental changes to improve your operations and support your business.
We provide solutions for hundreds of financial clients, including many of the industry’s biggest players, and have been doing so for more than 22 years. We’re more than data scientists with great technology – we’re partners who truly get how you operate your business.
Linedata Analytics Service continually evolves to reflect the latest data science. Our models learn your business to deliver data driven intelligence for portfolio operations through easy-to-understand alerts, statistics, and reporting.
In a world where time truly is money, we help you cut through the noise and act with confidence. Advanced data visualization creates easy-to-understand, actionable M/L operational insights and helps you collaborate across teams and brief the C-Suite when important actions are to be taken.
Linedata Analytics Service is securely hosted in the cloud with interactions using a web-based interface. We manage integration of your historical data and augment it as needed with data from leading providers. We host and protect your data using the latest cyber defense and data security protocols.
We provide solutions for hundreds of financial clients, including many of the industry’s biggest players, and have been doing so for more than 22 years. We’re more than data scientists with great technology – we’re partners who truly get how you operate your business.
Linedata Analytics Service continually evolves to reflect the latest data science. Our models learn your business to deliver data driven intelligence for portfolio operations through easy-to-understand alerts, statistics, and reporting.
In a world where time truly is money, we help you cut through the noise and act with confidence. Advanced data visualization creates easy-to-understand, actionable M/L operational insights and helps you collaborate across teams and brief the C-Suite when important actions are to be taken.
Linedata Analytics Service is securely hosted in the cloud with interactions using a web-based interface. We manage integration of your historical data and augment it as needed with data from leading providers. We host and protect your data using the latest cyber defense and data security protocols.
Use from an existing list of models or bring your own use case.
We can pull data from Linedata systems and/ or provide your own extracts.
Training and regression of AI models.
Review model results and assess proof of concept performance.
Scale up the proof of concept environment for implementation.
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