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Risk Management Solution

The solution to centralise and control your exposure

Centralize and manage your
clearing risks !

The SLIB Risk Management Solution (RMS) is designed to allow efficient management of clearing and counterparty risk exposure, for cleared and OTC activities.

You are an individual (ICM) or general (GCM) clearing member, you monitor the daily margin call amounts of clearing houses (CCP) that you are a member of. This is carried out via contradictory calculation by replicating daily margin requirement algorithms.

To hedge exposure induced by your clients’ activities, in turn you call for margin. To do so, you can use your own algorithms or those of the clearing houses’.

SLIB RMS offers you a software to help along the complete process, to further improve your risk management requirements. Monitoring exposure in real time, our solution offers you and your clients the possibility to anticipate cash requirements related to calls and to efficiently raise alerts.

With SLIB RMS, you are able to centralise and monitor exposure as well as risk in real time.

Offre RMS pour optimiser la gestion des risques

RMS

A centralised hub

Margin calls

  • Consolidating market and OTC activity of your clients, irrespective of their origin.
  • Enabling connections to clearing houses to cover Europe and Asia.
  • Integrating exposures calculated by external contributors (clearing house) or internal ones (your own systems).
  • The margin call module integrates collateral, consolidates exposure calculated by RMS software or by your own algorithms. Your clients are kept informed thanks to a fluid and secured process.
  • You can customise all types of documents, notifications and related accounting transactions.
  • You reduce manual operations and related operational risks and costs.

Algorithms manager

A decision-making cockpit

  • Reproducing the main daily margin requirement calculation methods published by European CCPs (SPAN, ERA and TIMS, etc.).
  • The algorithm SLIB CMMA (Common Multi Market Algorithm) based on V@R (Value at Risk) allows permanent and consolidated measure of your clients’ exposure. Tested and approved, it adapts easily and efficiently to your market needs.
  • Operational management solution which offers added value.
  • User-friendly graphic design functions based on Datalake technology enabling you to analyse on-the-fly exposure or statistical trends using historical data.

Key benefits

Responsiveness

  • Monitor your exposure in real time, set up your limits and receive alerts immediately.

Flexibility

  • Build your portfolios and consolidation levels easily.
  • Integrate your own algorithms.

Scalability

  • Successfully monitor increasing volume activity with peace of mind.
  • Benefit from our SaaS infrastructure technology.

Transparency

  • Share information with your clients in real-time.
  • Browse through a client’s exposure detail.
  • Feed your credit analysis statistics.

Reliability

  • Control your operational risk: ensure compliance, security, availability and performance.

Integration

  • Connectivity: the SLIB architecture manages multi-format, clearing house standard format and/or markets standard formats (TCR FIX…) connections. It can also be customised to your own private formats.

Consult the RMS documentation

News

White Paper

Central counterparts margin models, procyclicality and clearing members

As a likely result of this worldwide effort to improve market resiliency against unavoidable crisis, CCPs, in particular European ones, remained resilient trough the COVID-19 crisis, due to effective Business Continuity Plans and robust margin models.
Still, too conservative margin calls, instead of safeguarding the financial market stability, can cause harmful liquidity stress for market participants.
In other words, the medicine would be worse than the disease.

White Paper

RMS White Paper V@R and new Margin Frameworks

Central Counterparts, as part of their Daily Margin Process with their clearing members, are enhancing their Initial Margin computation methodology. Historically based on a SPAN model or equivalent Risk aggregation models,

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