Securitisation Swaps: An Introduction

Thursday, May 16, 2019

Securitisation swaps are a critical, yet often neglected area of finance markets. This handbook provides an introduction to the basics, through to a detailed discussion of all the key risks and how a transaction is put together from start to finish. In Chapter 7, the authors offer some numerical examples to provide ballpark CFVA costs. These example use sophisticated Monte Carlo analytics developed by Quantifi. Quantifi has an established reputation as the market leader in analytics and is built on the latest technology and incorporating advanced numerical methods. Read More

Risk Training: FRTB Course

Friday, January 19, 2018
As the FRTB implementation date looms ever closer, banks and regulators are still debating the rules and iterations of the regulations.'s training course returns to New York to help provide delegates with practical knowledge to better... read more

Applying Vectorisation to CVA Aggregation

Thursday, November 2, 2017
Join Quantifi and Intel for this complimentary webinar on vectorisation. New challenges in the financial markets driven by changes in market structure, regulations and accounting rules like Basel III, EMIR, Dodd Frank, MiFID II, Solvency II, IFRS... read more

Risk Training: Fundamental Review of the Trading Book

Friday, July 14, 2017
The Fundamental Review of the Trading Book (FRTB) has been a difficult topic for both banks and regulators over the past few years. With implementation set for 2019, many companies are still establishing what their FRTB strategy will be, as well as... read more

Vectorization, Part 3: Applying Vectorization to CVA Aggregation

Monday, July 10, 2017

As noted, the Finance domain provides many good candidates for vectorization. A particularly good example is the aggregation of Credit Value Adjustment (CVA) and other measures of counterparty risk. The most common general purpose approach to calculation of CVA is based on a Monte-Carlo simulation of the distribution of forward values for all derivative trades with a counterparty. The evolution of market prices over a series of forward dates is simulated, then the value of each derivative trade is calculated at that forward date using the simulated market prices. Read More

Explaining the Two Key FRTB Frameworks

Wednesday, June 28, 2017

FRTB is intended to address the undercapitalisation of trading book exposures witnessed during the financial crisis. While the basic goals and ideas of FRTB are simple, it differs materially from the existing Market Risk regulations. FRTB is likely to have a substantial influence in the way firms are organised, and their approach to measuring and reporting risk. There will also be an overall business and operational impact.  Banks need to decide whether the costs associated with operational and IT change is justified.  Read More

Risk Training: XVA, Credit, Funding and Capital Valuation Adjustments

Thursday, June 15, 2017
XVAs provide the financial industry with a lot of opportunities, particularly as new valuation adjustments develop and as valuation adjustments like CVA and FVA continue to add value. But with these opportunities come complexities because of the... read more

Helaba Enhances Enterprise-Wide Derivatives Counterparty Risk Management

Friday, March 31, 2017

Given current market practices around counterparty risk regulation, xVA management, funding and accounting, Helaba, one of the leading German banks, decided it needed to enhance its counterparty risk infrastructure for their OTC derivatives business. To support this initiative the bank wanted to pair their existing risk and core trading infrastructure with a modern, enterprise-wide XVA solution. The ability for senior management to get a comprehensive view of the bank's counterparty risk was one of the key priorities.

AFD Leverages Quantifi’s Single Solution for Trading, Risk & Regulatory Compliance

Friday, March 31, 2017

To remain ahead of market developments and regulatory requirements including EMIR and IFRS13 (CVA), AFD looked to complement their existing infrastructure with a single front-to-risk solution that combined high-performance technology with best-of-breed functionality.  Limited by their incumbent systems, AFD required a core trading and portfolio management solution (PMS) that could provide a single view of risk, consistent analytics, and calculations to support central clearing.