https://store-images.s-microsoft.com/image/apps.64257.99d641be-71c5-4173-9c69-2cb02552acfc.99735f1c-d183-49d2-99ef-be7a151f05ba.ea798abc-d661-45aa-9b54-519ab2c899f4

Sibli

by Sibli

The intelligent capital allocation platform for institutional investors

Sibli is the only platform that securely unifies Excel-based financial models, internal investment views, and external research into a connected system tailored to the needs of institutional asset managers. It transforms manual and fragmented forecasting and trade recommendation workflows into scalable processes that repeatedly generate unique insights which are aligned with your team’s unique investment philosophy and views.

Solve Critical Challenges

Institutional investors face mounting complexity in managing synthesizing research and forecasts into unique views. Siloed Excel models are at the heart of bottom-up fundamental investment analysis and contain valuable insights on what forms analyst views as well as contains data on their historical performance. Yet, there is a lack of auditability, no programmatic access to historical assumptions, and no means of unifying data across models. This leads to both operational risks and missed alpha opportunities. Research workflows are equally strained by information overload, time-consuming monitoring, all in search of identifying trends and events which impact key driving assumptions in the financial forecasts.

Sibli addresses these challenges by connecting your existing models and research into a unified data asset. By auditing and extracting all key data from Excel forecasts as well as mimicking the decision-making of the top Portfolio Managers and analysts, Sibli enables investment teams to make faster and better-informed decisions.

Core Capabilities:

  • Financial Model Management: Automate ingestion, versioning, and auditing of complex Excel models across the enterprise.
  • Advanced Analytics
  • Evaluate trade performance, forecast trends, and assess forecast quality through anomaly detection and benchmarks.
  • Scenario Analysis: Answer complex what-if questions by modifying common driving assumptions across any number of forecasts in a sector, portfolio, or across the fund.
  • Automated Screening: Quickly screen and score securities and datasets for alignment with your investment philosophy to accelerate security onboarding and expand your investment coverage.
  • Secondary Research: Save time and reduce cognitive load with event-driven alerts and causal impact analysis mapped to your forecasts and aligned with your views.

Enterprise-Grade Benefits:

  • Security: Enterprise-grade encryption, access controls, and audit trails ensure compliance and control.
  • Accuracy: Ensure consistent assumptions, verifiable forecasts, and audit-ready workflows.
  • Integration: Connect seamlessly with proprietary systems and external data providers.
  • Efficiency: Eliminate manual model checks, accelerate research review, and free up analyst time for higher-value work.
  • Scalability: Support enterprise-wide use cases like risk management, performance attribution, and compliance monitoring.

Trusted by Leading Investors: Sibli is trusted by some of the largest institutional investors by AUM in Canada and the UK. Our clients rely on Sibli to improve decision quality, reduce operational risk, and scale their research and portfolio management processes globally.

https://www.wetransact.io/

At a glance

https://store-images.s-microsoft.com/image/apps.31972.99d641be-71c5-4173-9c69-2cb02552acfc.fc7b7f99-96ad-4540-94b9-308acabbb38c.683b08c2-1f4f-49f9-82f8-77f393b0d600
https://store-images.s-microsoft.com/image/apps.61668.99d641be-71c5-4173-9c69-2cb02552acfc.fc7b7f99-96ad-4540-94b9-308acabbb38c.50915481-2f95-432c-b5b2-06ed514c40d5
https://store-images.s-microsoft.com/image/apps.33244.99d641be-71c5-4173-9c69-2cb02552acfc.99735f1c-d183-49d2-99ef-be7a151f05ba.57f65b8d-eeee-4f8f-9cfd-45410cb1498c
https://store-images.s-microsoft.com/image/apps.45042.99d641be-71c5-4173-9c69-2cb02552acfc.fc7b7f99-96ad-4540-94b9-308acabbb38c.1df78a10-0556-4a79-9574-6ae8423329ef