Explore Crisil, a company of S&P Global

Formerly known as Global Research & Risk Solutions

Data and Analytics

 

 

Assisting clients in their journey from data to insights

We collaborate with financial institutions to develop advanced data management platforms.

We start by formulating a comprehensive data management strategy, working closely with clients to establish integrated data architectures and enterprise-wide data management solutions.

This includes designing sophisticated risk-data warehouses and repositories, as well as innovative data analytics tools that deliver valuable insights.

We possess extensive experience in data onboarding, ETL processes, and analytics on data warehouses and Hadoop data lakes.

Our capabilities extend to fostering data-driven organisations by leveraging data mesh and data fabric architectures on hybrid cloud platforms, including the implementation of AI/ML functionalities such as AutoML and MLOps.

We also utilise RPA, IPA and NLP technologies within this domain.

By prioritising data quality, governance, sourcing and validation, we help clients eliminate inefficiencies and build confidence in their data, enabling them to integrate data analytics into their core operations and make informed decisions on critical business, operational and investment matters.

 

 

 

 

Why choose us

 

 

 

Expertise in end-to-end data transformation and automation best practices and industry-leading standards.

Extensive experience across industry domains (banking, wealth management, asset management, risk, finance and compliance).

Data governance and quality operating model frameworks for improved regulatory compliance.

 

 

 

2

Over two decades of experience in research and analytics

800

More than 800 research analysts across the globe

12

Presence in 12 countries, with delivery centres in India, Argentina, China, Colombia and Poland

 

 

 

 

Our solution components

 

 

Data strategy

  • Align business and technology stakeholderst
  • Conduct readiness assessments
  • Identify and prioritise use cases
  • Design an innovative data blueprint
  • Implement robust data governance
  • Mobilise the organisation and inspire data literacy

Data architecture and integration

  • Value proposition and team development
  • Conduct rationalisation assessments
  • Define data architecture and integration roadmap
  • Define foundational architecture
  • Develop transformational architecture
  • Roll out and optimise enterprise architecture

Data governance and management

  • Design target state data governance policies and master data management framework (including ingestion process)
  • Define business and technical requirements for enterprise-wide certification tool, and create relevant reporting capability
  • Develop the methodology, certification criteria and scoring methods for assessing and certifying authorised data sources and data controls
  • Identify all missing classifications and map them to their correct classifications using set rules
  • Validate and cleanse data to feed into a downstream engine that runs reports to identify issues before being automatically validated
  • Create a single source of truth and centralised repository

BI and MI reporting

  • Define BI/MI requirements
  • Collect and analyse data
  • Establish data architecture
  • Develop interactive dashboards
  • Automate process
  • Design queries and reports

Advanced analytics

  • Requirements gathering
  • Investigative phase
  • Model design
  • Metrics assessment
  • Model output
  • Iterative improvement

 

 

 

 

 

Who we serve

Corporate and investment banks



Traditional asset managers

Hedge funds





 

 

 

 

achieve-success

Discover why the world's most prestigious
global and regional financial institutions
chose us as their strategic partner