Flexible ML Serving and Management for Financial Services

Automate and scale machine learning across your enterprise with confidence and transform the future states with agility. Lower operational costs, whilst increasing productivity, collaboration and transparency across the ML lifecycle.

Learn why organisations are relying on Seldon, with over 1.7 million models deployed

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Seldon enhances time-to-value so models can get to work up to 85% faster. Eliminate silos and minimise risk through interpretable results and transparent model performance.

of organisations are using machine learning for critical business problems.

faster business growth when powered with AI.

higher average profit margins.

Whatever AI means to you, Seldon makes it possible

In order for FSI organisations to remain competitive and deliver sustainable value, vast amounts of unstructured data to inform customer strategies, risk and pricing has become critical. Whatever maturity you’re on in your journey, Seldon’s flexibility enables your future state.

Automate loan and policy underwriting decisions
Optimise operational costs in line with customer demand SLAs
Ensemble model chains across customer journeys to create hyper-personalisation
Predict customer churn
Detect, predict and mitigate fraud (KYC & AML)
Real-time targeting and in-context promotion

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Turn R&D into ROI with Models in Production

Eliminate silos and enable teams to work together in a flexible, secure, single platform that integrates seamlessly with your digital environment and applications.

Self-serve ML through one-click deployments
Platform-agnostic and language agnostic means you can build and deploy ML models your way.
Test new models against historical data, feature distribution and patterns before running in production.
Automate complex deployments leveraging industry-leading techniques such as A/B tests, canaries and multi-arm bandits.

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Optimise your ML Models in Line with Governance and Compliance

Predicting model outputs and accuracy is key to top and bottom lines as well as brand reputation. Build confidence scaling Human Centre AI through explainability, and avoid regulatory fines through successful model governance.

Proactively mitigate model risk through advanced monitoring techniques to identify drift and outlier detection.
Explain pricing outputs inline with regulation.
Real-time dashboards and metrics creating transparency across the ML lifecycle.
Model management, monitoring and alerting triggers a faster feedback loop to improve future iterations.
Ensure full auditability, accountability and traceability across all models.

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