Explore Crisil, a company of S&P Global

Formerly known as Global Research & Risk Solutions

Traded Risk and Finance Platforms

 

 

Achieving real-time risk and pricing capabilities

Banks are grappling with operational inefficiencies rooted in inefficient legacy processes, fragmented data sources and infrastructure, exacerbated by exponential growth in data volumes and stringent regulatory requirements.

The burden of legacy data and inadequate data management systems is weighing heavily on banks, hindering their ability to make timely and informed decisions to manage their risk profiles better.

With decades of experience collaborating with top global financial institutions, we guide banks through complex risk transformation initiatives, helping them navigate technology transformation and empowering them to achieve real-time risk and pricing capabilities.

Our bespoke solutions are crafted to support banks at various stages of maturity in their pursuit of real-time risk management, helping them overcome their unique challenges and achieve operational excellence.

 

 

 

Our services

 

 

  • Develop ultra-low latency trade execution infrastructure solutions
  • Build, re-architect and scale real-time risk and pricing platforms
  • Conduct real-time pre-trade and post-trade analytics
  • Develop customisable user interfaces to visualise risk metrics and P&L data, supported by development of intra-day risk reporting tools
  • Perform analysis to evaluate build vs buy options (third-party tools such as Murex, Calypso, Numerix, and S&P FRA tool) to meet risk management solution needs

  • Standardise calculations for FO and EoD risk and P&L to generate one view of data
  • Perform front-to back integration and standardisation of EoD data, processes and risk engines

  • Design and implement strategic risk engines for risk generation and aggregation, and build pricing analytics/ libraries
  • Integrate and migrate from legacy systems to next-generation systems, utilising proprietary or third-party utilities, tools and frameworks such as subledger standardisation and GL cloud migration
  • Address complex regulatory requirements such as FRTB, Basel III/IV and IFRS, while integrating compliance into BAU processes
  • Develop and enhance analytics strategies; develop and deliver across the analytics spectrum, utilising AI/ML, RPA, NLG, NLP, blockchain and ML

  • Create a single, consistent source of truth for finance, risk and trading functions and regulatory reporting
  • Build seamless connections between trading, risk and finance platforms to enhance operational consistency and transparency

  • Process data feeds for market/ trade/ reference data
  • Integrate ML models
  • Carry out trading strategy and transaction cost modelling in algorithm engine
  • Implement and optimise EMS and OMS solutions
  • Design and implement hybrid cloud data and microservices platforms
  • Perform pre- and post-trade analytics, including TCA benchmarking, execution surveillance and limit order execution

 

 

 

 

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