About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Quantifi Stresses Data Management Requirement for Basel III Credit Risk

Subscribe to our newsletter

Quantifi has built out its counterparty credit risk platform to meet the capital requirements of Basel III. But the company warns that data aggregation and management coupled to a centralised approach to the regulation are essential to full compliance and managing the cost of capital.

Basel III regulation was finalised in June 2011 and will be implemented into law in the European Union by the Capital Requirements Directive IV. Despite a postponement in bringing the regulation into force from January 2013 to January 2019, Quantifi says banks subject to the regulation should be looking now at how they will achieve compliance.

Dmitry Pugachevsky, director of research at Quantifi, says that whether they are building or buying Basel III solutions, banks should be bringing together all the data needed to calculate counterparty credit risk capital charges, including credit valuation adjustment (CVA) risk capital charges, centrally to achieve the best capital results. He also encourages use of the same data and models for both regulatory and trading systems to ensure consistency and ease compliance.

The company works predominantly with tier two banks and has been using used its counterparty credit risk engine to run CVA capital charges calculations across retail, commercial and investment bank portfolios. The aim is to identify which calculation methods, perhaps the internal model method or advanced method, deliver the best outcomes in terms of lower capital charges.

The work suggests the best performing methods are the internal model method for Basel II risk weighted assets and the advanced method for Basel III CVA risk capital charges. Quantifi states: “This result confirms that implementing sophisticated Monte Carlo models and getting regulatory approvals can save significant amounts of capital.” The company also refutes market opinion suggesting that Basel II counterparty credit risk capital charges are much lower than those required by Basel III, noting that charges can be similar depending on the methods used in calculation.

Quantifi’s Basel III solution uses the same software as its Basel II offering, albeit with slightly different data, managing both credit and market risk on the platform and taking into account issues such as collateral management and cross-product netting agreements. Calculations are made in real time and an integrated reporting system allows users to drill down into the data to discover the effects of particular counterparties or trades on capital charges.

Pugachevsky acknowledges market competitors such as Murex and Calypso, but suggests Quantifi provides an enterprise risk system with a more user friendly front-office element that not only delivers real-time data, but also a relatively easy to use solution for sensitivities and scenario creation. However, even with a risk system in place, he repeats that the opportunity to reduce capital requirements remains a function of the collection of high quality, aggregated data from across trading systems.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: How to organise, integrate and structure data for successful AI

Artificial intelligence (AI) is increasingly being rolled out across financial institutions, being put to work in applications that are transforming everything from back-office data management to front-office trading platforms. The potential for AI to bring further cost-savings and operational gains are limited only by the imaginations of individual organisations. What they all require to achieve...

BLOG

Validating GenAI Models in Finance: A Q&A with Chandrakant Maheshwari on Risk, Governance, and the Rise of Agentic AI

At a recent RegTech Insight Advisory Board session, a discussion with Chandrakant on generative AI (GenAI) and model risk management underscored the need to cut through the hype and myths around GenAI and emerging agentic AI in regulated markets. This Q&A is the result. It examines why traditional model validation techniques—ROC curves and confusion matrices—can’t...

EVENT

Eagle Alpha Alternative Data Conference, London, hosted by A-Team Group

Now in its 8th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...