Automation Tools

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

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

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

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

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

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

The problems we solve

Research

We help to transform complex data into clear business insights

Case Studies

Led the data strategy and execution of an enterprise transformation programme for a global bank, which included cloud adoption, data estate rationalisation, and data platform modernisation related to various bank activities and functions

Data strategy

Data architecture and integration

Data governance and management

BI and MI reporting

Advanced analytics

Discover why the world's most prestigiousglobal and regional financial institutionschose us as their strategic partner

Businesses

Businesses

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Our Organisation

Investor Relations

Newsroom

More from Crisil

Our Organisation

Investor Relations

Newsroom

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