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THE 8TH XVA CONFERENCE13TH - 15TH MARCH 2019

CCT VENUES-DOCKLANDS, CANARY WHARF, LONDON

SPEAKERSSarah B Tremel: Global Head of Analytics – Product Control, HSBC

Michael Pykhtin: Manager, Quantitative Risk, U.S. Federal Reserve Board

Andrew Green: Managing Director, XVA Lead Quant, Scotiabank

Assad Bouayoun: Senior XVA Quantitative Consultant, HSBC Global Banking and Markets

Jon Gregory: Independent xVA Expert

Lucia Cipolina Kun: VP, Morgan Stanley

Youssef Elouerkhaoui: Managing Director, Head of Credit Derivatives, Citigroup

Nnamdi Okaeme: Director – Risk and Capital, ISDA

Satinder (Sid) Jandu: Risk Management Consultant, Morgan Stanley

Osamu Tsuchiya: Principal, Simplex Inc

Hannah Townsend: xVA Trader, Lloyds Banking Group

Ignacio Ruiz: Founder & CEO, MoCaX Intelligence

Stéphane Crépey: Professor of Mathematics, University Of Evry

Jos Gheerardyn: Co-Founder and CEO, Yields.io

Giovanni Cesari: Head of XVA – Market and Traded Credit Risk, Standard Chartered

Gordon Lee: XVA and Capital Quantitative Analyst, UBS

Chris Kenyon: Director, Head of XVA Quant Modelling, MUFG Securities EMEA Plc

Mats Kjaer: Head of Quant XVA Analytics, Bloomberg LP

Alexandre Antonov, Director, Standard Chartered Bank

Colin Turfus: Quantitative Analyst, Deutsche Bank

Andrey Chirikhin: Founder, Quantitative Recipes

Christian Pötz, Postgraduate Researcher, Queen Mary University of London

SPONSORS

CONFERENCE OVERVIEW

LOCATION:CCT Venues-Docklands, Canary WharfThames Quay193 Marsh WallLondonE14 9SG

Tel: +44 (0)20 7537 6545 | Website: www.cctvenues.co.uk/venues/docklands

WEDNESDAY 13TH MARCH: PRE-CONFERENCE WORKSHOP DAYMachine Learning Applications in the XVA Spaceby Andrew Green: XVA Lead Quant, Scotiabank

THURSDAY 14TH MARCH: MAIN CONFERENCE, DAY ONE• XVA & Initial Margin Stream• Machine Learning Applications in XVA Stream

FRIDAY 15TH MARCH: MAIN CONFERENCE, DAY TWO• MVA & Initial Margin Stream• XVA Techniques Stream

CONFERENCE BOOKINGS: DISCOUNT STRUCTURE:• Super Early Bird Discount: 25% until 8th February• Early Bird Discount: 10% until 1st March• Main Conference + Workshop (£150 Discount)• SPECIAL OFFER: When 2 colleagues attend the 3rd goes free!• 70% Academic Discount (FULL-TIME Students Only)

CPD CERTIFICATION

You will be able to receive up to 19 CPD points (18 hours and 30 minutes of structured CPD) for attending this event

The CPD Certification Service was established in 1996 as the independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies. The CPD Certification Service provides recognised independent CPD accreditation compatible with global CPD principles.

www.cpduk.co.uk

IMPORTANT NOTES:

Conference presentation files on USB memory sticks will be provided on arrival. The conference files will also be made available for download via a password protected website before the event. Please print out each presentation if you wish to have hard copies before the conference and bring them with you.

Also, Wi-Fi access will be available at the venue to view presentations on laptops and mobile devices.

PRE-CONFERENCE WORKSHOP DAY – WEDNESDAY 13TH MARCH

MACHINE LEARNING APPLICATIONS IN THE XVA SPACE BY ANDREW GREEN: XVA LEAD QUANT, SCOTIABANK

DAY SCHEDULE: 09:00 – 17:30BREAK: 10:30 – 11:00 / LUNCH: 12:30 – 13:30 / BREAK: 15:15 – 15:30

Tutor BiographyAndrew Green: Managing Director and XVA Lead Quant, Scotiabank

Andrew Green is a Managing Director and lead XVA Quant at Scotiabank in London. Prior to joining Scotiabank, Andrew held roles as a quantitative analysis in several different banks in London. He is the author of XVA: Credit, Funding and

Capital Valuation Adjustments, published by Wiley.

Foundations: CVA, DVA & FVA

• CVA & DVA by Replication• Credit Mitigants• FVA by Replication• FVA & DVA (overlaps)• FVA in pricing and accounting• A brief tour of the XVA Monte Carlo engine

MVA

• Initial Margin and XVA• MVA by Replication• MVA for VaR-type IM (CCPs)• MVA for SIMM-IM

KVA

• What is Capital?• KVA by Replication• KVA vs Hurdle Rates• Which measure?• The Cost of Capital

Introducing Machine Learning

• Types of machine learning problem:• Motivation I: Multivariate Linear Regression

• Supervised learning• Regression problems• Classifier problems• Unsupervised learning

• Motivation II: Logistic Regression• Bias and Variance• Regularization

• Neural Networks• Activation functions• Geometry• Forward and backpropagation• Initialization

• Deep Learning

Credit Curve Mapping as a Machine Learning Problem

• Dealing with Illiquid counterparties in XVA• Key Requirements of the Map

• Trading Requirements• Regulatory Requirements: Basel III & FRTB-CVA

• Classical Methods• Classifier Approach• Regression Approach

A Tour of XVA ML Applications

• Optimising MVA• Dimension Reduction: PCA & Autoencoders

MAIN CONFERENCE DAY ONE – THURSDAY 14TH MARCH

XVA & INITIAL MARGIN STREAM MACHINE LEARNING APPLICATIONS IN XVA STREAM

08:00 REGISTRATION AND MORNING WELCOME COFFEE

09:00 – 09:45 KEYNOTE SPEECH: HOW MACHINE LEARNING CAN HELP BETTER MANAGE XVA

by Sarah B Tremel: Global Head of Analytics – Product Control, HSBC

• P&L explain• Sensitivities• Forecasting

09:45 – 10:30 MVA MARKET DEVELOPMENTS

• MVA Overview• Pricing and Optimisation• MVA Reserves• IM Phase 4 and 5

Presenter: Hannah Townsend: xVA Trader, Lloyds Banking Group

10:30 – 11:00 MORNING BREAK AND NETWORKING OPPORTUNITIES

11:00 – 11:45 DEEPLY LEARNING DERIVATIVES

Abstract

This paper uses deep learning to value derivatives. The approach is broadly applicable, and we use a call option on a basket of stocks as an example. We show that the deep learning model is accurate and very fast, capable of producing valuations a million times faster than traditional models. We develop a methodology to randomly generate appropriate training data and explore the impact of several parameters including layer width and depth, training data quality and quantity on model speed and accuracy.

Presenter: Andrew Green: Managing Director and XVA Lead Quant, Scotiabank

11:45 – 12:30 XVA WITH SIMM USING MACHINE LEARNING TECHNIQUES

• Motivation – SIMM, FRTB and ANN• Master Pricing Equation with Credit, Funding and IM• Mathematical Introduction to Neural Networks• The Universal Representation Theorem• Pre and Post Default Forward Exposures with SIMM• Numerical Implementation• Applications

Presenter: Youssef Elouerkhaoui, Managing Director, Head of Credit Derivatives, CITI

12:30 – 13:30 LUNCH

11:00 – 12:30 EXTENDED TALK: SYMMETRIC OR ASYMMETRIC FVA?

• Basic FVA and discounting• Funding strategies• NSFR• Evidence from Totem• A move to asymmetric FVA?• Link to initial margin and MVA

Presenter: Jon Gregory: Independent xVA Expert

12:30 – 13:30 LUNCH

MAIN CONFERENCE DAY ONE – THURSDAY 14TH MARCH

XVA & INITIAL MARGIN STREAM MACHINE LEARNING APPLICATIONS IN XVA STREAM

13:30 – 14:15 THE PRICING OF XVA AND STOCHASTIC CORPORATE LIABILITIES

• A structural model allows to construct a self-consistent and paradox-free theory of XVA.

• Derivatives are treated as stochastic liabilities of issuers.

• XVA on new business is always a corporate finance problem, as marginal debt (stochastic or not) must be priced. In practice it is approximated by various CCDSs, assuming marginal debt is small.

• DVA is credit haircut on a theoretical value of a (stochastic) liability. It is created together with the liability, it cannot be hedged and it must be borne by the original investor that then can later sell it physically or synthetically (CDS).

• CVA is the counterparty’s DVA from the investor’s point of view. Treatment of reciprocal investments is possible but requires settlement theory.

• FVA is syntactic sugar for marginal DVA; valuing FVA requires explicit assumptions about marginal assets.

• Cost of capital (KVA) must be borne by the party that decides on the asset/liability structure, i.e. by “effective shareholder”. It cannot be transferred to pure bond investors (as DVA).

• Collateralization turns deals into swaps with no initial exchange and shifts funding of PNL to third parties. Such funding will attract its own DVA.

Presenter: Andrey Chirikhin: Founder, Quantitative Recipes

14:15 – 15:00 FAST CALCULATION OF CREDIT EXPOSURES

• New method for the calculation of credit exposures of Bermudan, barrier and European options based on Chebyshev interpolation.

• Closed form approximation of the option prices along the paths together with the options’ delta and gamma.

• Polynomial structure of the approximation allows a highly efficient evaluation of the credit exposures, even for a large number of simulated paths.

• The presented approach is flexible in the model choice, payoff profiles and asset classes.

• Investigation of exposure profiles and discussion of practical implications.

(Joint work with Kathrin Glau and Ricardo Pachon)

Presenter: Christian Pötz, Postgraduate Researcher, Queen Mary University of London

13:30 – 14:15 REINFORCEMENT LEARNING FOR MARGINAL KVA PRICING

• Capital creation and consumption• Models for lifetime costs and benefits of capital in

trading• Contract design vs KVA model• Solution framing and methods: F-K/FBSDE:

Stochastic programming; reinforcement learning• Numerical results

Presenter: Chris Kenyon: Director: Head of XVA Quant Modelling, MUFG Securities EMEA Plc

14:15 – 15:00 QUANTUM ANNEALING FOR MULTI-PERIOD XVA REVERSE STRESS TESTING

• Modelling• XVA reverse stress testing formula• XVA reverse stress testing as a QUBO problem (

Quadratic Unconstrained Binary Optimisation)• Generalisation to multi-period case

• Optimisation using annealing• Quantum annealing• Simulated annealing

• Applications• Simple portfolio of swaps• Firm level management

Presenter: Assad Bouayoun: Senior XVA Quantitative Consultant, HSBC Global Banking and Markets

MAIN CONFERENCE DAY ONE – THURSDAY 14TH MARCH

XVA & INITIAL MARGIN STREAM MACHINE LEARNING APPLICATIONS IN XVA STREAM

15:00 – 15:30 AFTERNOON BREAK AND NETWORKING OPPORTUNITIES

15:30 – 16:15 INTRADAY LIQUIDITY AND THE SETTLEMENT DILEMMA

Presenter: Gordon Lee: XVA and Capital Quantitative Analyst, UBS

15:00 – 15:30 AFTERNOON BREAK AND NETWORKING OPPORTUNITIES

15:30 – 16:15 QUANTUM ANNEALING FOR MULTI-PERIOD XVA REVERSE STRESS TESTING

Abstract:

One to one relations among banks are often the limit of risk models. Counterparty dynamics beyond a one to one relation has started to appear in network risk metrics, but these network models often rely on Pareto distributed random networks to integrate out the known structural constraints and interactions that dictate the flow of risk modelled by xVA. Interdependencies are integral to credit risk modelling, but the default xVA assumption is counterparty independence. This independence assumption results in an unrealistic picture of credit risk. In light of the rich dynamics available through network models and xVA, we present an interconnected Agent-based xVA model of this complex interconnected system of banks as agents interacting according to their behavioural dynamics. This new Agent-based xVA model results in a higher-order impact assessment of emergent counterparty risk.

Presenter: Krishnen Vytelingum: Agent-based Modelling Specialist, Simudyne

MAIN CONFERENCE DAY ONE – THURSDAY 14TH MARCH

XVA & INITIAL MARGIN STREAM MACHINE LEARNING APPLICATIONS IN XVA STREAM

16:15 – 17:00XVA, FRTB & MACHINE LEARNING PANEL

MODERATOR:

• Gordon Lee: XVA and Capital Quantitative Analyst, UBS

PANELLISTS:

• Ignacio Ruiz: Founder & CEO, MoCaX Intelligence• Andrew Green: Managing Director and XVA Lead Quant, Scotiabank• Satinder (Sid) Jandu: Risk Management Consultant, Morgan Stanley• Giovanni Cesari: Head of XVA – Market and Traded Credit Risk, Standard Chartered

TOPICS:

XVA & INITIAL MARGIN:• Initial Margin, a push for more model standardization? Good or bad?• How do you interpret the regulatory requirements to validate and monitor SIMM, and how would a firm best go about

meeting those requirements?• SIMM relies on counterparts calculating their own sensitivities. Do the panelists foresee that causing any problems

meeting requirements or additional costs?• Discuss Implementing SIMM for Non Cleared Initial Margin Rules• Discuss the role of technology to increase the knowledge base from XVA calculations

MACHINE LEARNING• Discuss the existing applications of machine learning in XVA• Discuss the potential new applications of machine learning in XVA going forward• How important is machine learning in calculation of XVAs?• Best practices to incorporate machine learning across XVAs• Is machine learning necessary for XVA?

DISCUSS THE IMPACT OF FRTB ON XVA’S:• How will the latest proposed regulations impact CVA calculations• Review what are the most important factors to take into account when calculating the new CVA• Calculating & Implementing FRTB CVA. How will it affect banks’ internal modelling for counterparty risk and risk

management?

MAIN CONFERENCE DAY ONE – THURSDAY 14TH MARCH

XVA & INITIAL MARGIN STREAM MACHINE LEARNING APPLICATIONS IN XVA STREAM

MAIN CONFERENCE DAY TWO – FRIDAY 15TH MARCH

MVA & INITIAL MARGIN STREAM XVA TECHNIQUES STREAM

08:30 MORNING WELCOME COFFEE

09:00 – 09:45 EFFICIENT CALCULATION TECHNIQUES FOR CREDIT EXPOSURE IN THE PRESENCE OF INITIAL MARGIN

by Michael Pykhtin: Manager, Quantitative Risk, U.S. Federal Reserve Board

• Modeling collateralized exposure• Producing exposure on a daily simulation time grid without daily revaluations or daily IM calculations• Reducing simulation noise in the presence of IM• Alternatives to calculating IM along simulation paths

09:45 – 10:30 VITAMIN B, CHEBYSHEV POLYNOMIALS, HOMOCYSTEINE AND… DYNAMIC INITIAL MARGIN

• The power of Chebyshev Polynomials. Exponential convergence of Chebyshev methods: why is it so fast?• Theoretical basis• Live demo of how they work• Application to simulation of Initial Margin inside Monte Carlo simulations• Examples: swaps, swaptions and beyond• Comparison to regression and AD methods• Numerical results• Chebyshev is to Dynamic Initial Margin what Vitamin B is to Homocysteine• Options for free software available for inhouse testing and implementation

Presenter: Ignacio Ruiz: Founder & CEO, MoCaX Intelligence

10:30 – 11:00 MORNING BREAK AND NETWORKING OPPORTUNITIES

11:00 – 11:45 AN ENHANCED INITIAL MARGIN METHODOLOGY TO MANAGE WAREHOUSED CREDIT RISK

• The CVA profile after collateralization: an array of zeros

• The problem of lliquid CDS’s and warehoused credit risk

• A methodology to improve Initial Margin for warehoused Credit Risk

• Consistency of the methodology with the current CVA framework

• Examples of practical implementation

(Joint work with Ignacio Ruiz and Mariano Zeron)

Presenter: Lucia Cipolina Kun: VP, Morgan Stanley

11:00 – 11:45 USING MACHINE LEARNING TO MANAGE MODEL RISK IN XVA

• Leveraging ML in model risk management• Data quality analysis with deep neural networks• Building benchmark models using reinforcement

learning• Measuring cross-sectional performance• Surrogate models for ongoing monitoring

Presenter: Jos Gheerardyn: Co-Founder and CEO, Yields.io

11:45 – 12:30 CORRELATION IN MVA CALCULATION

• General Issues about XVA• The importance of interest rate correlations in MVA

calculation• LSM (Least Square Monte Carlo) in XVA calculation• Analysis of MVA calculation of the Non Callable

Interest Rate Derivatives• Numerical Examples• Discussion about applying to Callable Exotics

Presenter: Osamu Tsuchiya: Principal, Simplex Inc

12:30 – 13:30 LUNCH

13:30 – 14:15 ADVANCED TECHNIQUES FOR SIMM-MVA CALCULATIONS

• Initial margin (IM) and its projection to the future; MVA as a future IM interest

• Complexity of the MVA: one needs(exotic) portfolio sensitivities calculation for each scenario and observation data

• Particular difficulties with structured products: brute force MVA calculation time is unacceptably long

• An efficient method for the exact MVA calculation based on the future differentiation and its comparison with known approximations

• Numerical experiments for a Bermudan Swaption MVA: massive acceleration using the new method with respect to the brute force

Presenter: Alexandre Antonov, Director, Standard Chartered Bank

11:45 – 12:30 XVA FROM THE BEGINNING

Abstract

We use a single period structural model of a dealer balance sheet to study the impact of regulatory capital requirements on the marginal fair value and shareholder indifference price of a new derivative. As expected the former does not change. The latter is reduced by a capital valuation adjustment, which depends on the financing method used by the dealer. Finally we show that if the dealer hedges the derivative, then the indifference price is related to the cost of setting up the hedge.

Presenter: Mats Kjaer: Head of Quant XVA Analytics, Bloomberg LP

12:30 – 13:30 LUNCH

13:30 – 14:15 EVIDENCE-BASED APPROACH TO SIMM GOVERNANCE AND EVOLUTION

• Focus on our approach to governance• It’s importance for the SIMM evolution

Presenter: Nnamdi Okaeme: Director – Risk and Capital, ISDA

MAIN CONFERENCE DAY TWO – FRIDAY 15TH MARCH

MVA & INITIAL MARGIN STREAM XVA TECHNIQUES STREAM

14:15 – 15:00 XVA METRICS FOR CCP OPTIMISATION (JOINT WORK WITH YANNICK ARMENTI)

• Based on an XVA analysis of centrally cleared derivative trading, we consider two capital and funding issues pertaining to the efficiency of the design of central counterparties (CCPs).

• Regarding capital, we challenge pure market risk specifications of the sizing (such as Cover 2) and allocation of the default fund, by economic capital specifications based on expected shortfalls of a one year ahead trading loss of the CCP. Our default fund contributions would be pure “survivor pay” capital at risk, remunerated as such at a cost-of-capital hurdle rate.

• Regarding funding, we compare the MVAs resulting from two different IM raising strategies: a standard approach, where the IM is funded by unsecured borrowing by the clearing member, and an alternative strategy where a clearing member delegates the posting of its IM to a specialist lender with low funding costs.

• We find that, unless efficient (such as specialist lender) IM raising strategies are implemented, the IM funding expenses are in fact the main contributor to an economical capital based default fund of a CCP. This is an illustration of the transfer of counterparty risk into liquidity risk triggered by extensive collateralization

Presenter: Stéphane Crépey: Professor of Mathematics, University Of Evry

14:15 – 15:00 ANALYTIC CALCULATION OF WRONG-WAY RISK ON INTEREST RATE SWAPS

• Analytic rates-credit pricing kernel• Analytic pricing of CVA on a portfolio of IR swaps• Adjustment for collateral update schedule• Extension to multi-currency case• Impact of FX rate jump at default

Presenter: Colin Turfus: Quantitative Analyst, Deutsche Bank

MAIN CONFERENCE DAY TWO – FRIDAY 15TH MARCH

MVA & INITIAL MARGIN STREAM XVA TECHNIQUES STREAM

15:00 – 15:10 QUICK AFTERNOON BREAK

15:10 – 15:50 CLOSING TALK: THE CURRENT FRTB REGULATIONS ON XVA’S

Presenter: Satinder (Sid) Jandu: Risk Management Consultant, Morgan Stanley

END OF CONFERENCE

CONFERENCE SPONSORS

MoCaX Intelligence is a new-to-the-market algorithm that accelerates existing Risk Engines without the need for complex systems development or expensive hardware upgrades. MoCaX removes the pricing step bottle-neck that often uses over 90% of computational effort in existing engines and increases capabilities by several orders of magnitude with no loss of accuracy.

MoCaX builds on the new Algorithmic Pricer Acceleration (APA) and Algorithmic Greeks Acceleration (AGA) methods. APA synthesises your existing pricers and creates an accelerated version of them. Even your very slowest and complex pricer, passed through MoCaX, will return the same results (down to 10-15 precision) ultra-fast (up to a few nanoseconds). For example, this enables highly accurate Monte Carlo within Monte Carlo in an instant.

AGA is a further enhancement, creating also an ultra-accurate, ultra-fast function of the Greeks of your pricers, even when you do not have an expression for them. This enables for example exact MVA and MVA sensitivity calculations.

APA and AGA work for any pricing function: analytical, tree or MC based; and with any asset class.

With one million accurate Price or Greek values in a few milliseconds, MoCaX delivers:

• massive acceleration of your current simulations• previously-impossible simulations, e.g. accurate and ultra-fast MVA via real Dynamic

SIMM• potential for trades that had been too slow to simulate, e.g. non-linear products,

barriers, bermudans• enhanced regulatory approval, because MoCaX delivers perfect pricing and widens IMM

product scope

MoCaX Intelligence: the next step forward.

Please ask for a free version of MoCaX so you can test it for yourself.

mocaxintelligence.com | i.ruiz@iruiztechnologies.com

The Thalesians are a think tank of dedicated professionals with an interest in quantitative finance, economics, mathematics, physics and computer science, not necessarily in that order.

www.thalesians.com/finance/index.php/Main_Page

QWAFAFEW is an informal organization of quantitatively oriented professionals in various aspects of financial services, primarily investment management.

The members span the gamut from owners and senior executives of investment related organizations to recent entrants to the industry. Most attendees have some technical training beyond the M.B.A. level, and many have Ph.D.s. All share a common interest in quantitative solutions to understanding investment markets.

Please visit www.qwafafew.org for more information.

CONFERENCE SPONSORS

Yields.io is the first FinTech platform that uses AI for real-time model risk management on an enterprise-wide scale.

Our clients use our solution to speed up model validation tasks, to generate regulatory compliant documentation and to industrialize model monitoring. The platform works with all models that are used within the financial sector such as credit risk models, valuation algorithms, market risk, AML, AI and behavioural models.

Yields.io was founded by Jos Gheerardyn and Sébastien Viguié. The company is expanding quickly and has offices in Brussels and London. Yields.io has an international portfolio of clients with both investment banks as well as regional financial institutions.

yields.io

Welcome to The Machine Learning Institute Certificate in Finance (MLI)

• Start Date: Tuesday 23rd April 2019• Super Early Bird: 25% Discount until 22nd February 2019

Quantitative finance is moving into a new era. Traditional quant skills are no longer adequate to deal with the latest challenges in finance. The Machine Learning Institute Certificate offers candidates the chance to upgrade their skill set by combining academic rigour with practical industry insight.

The Machine Learning Institute Certificate in Finance (MLI) is a comprehensive six-month part-time course, with weekly live lectures in London or globally online. The MLI is comprised of 2 levels, 6 modules, 24 lecture weeks, lab assignments, a practical final project and a final sit down examination using our global network of examination centres.

This course has been designed to empower individuals who work in or are seeking a career in machine learning in finance. Throughout our unique MLI programme, candidates work with hands-on assignments designed to illustrate the algorithms studied and to experience first-hand the practical challenges involved in the design and successful implementation of machine learning models. The MLI is a career-enhancing professional qualification, that can be taken worldwide.

mlinstitute.org

The Numerical Algorithms Group (NAG) are experts in numerical algorithms, software engineering and high-performance computing. They have served the finance industry with numerical software and consulting services for over four decades because of their outstanding product quality and technical support. Specifically, relevant to the finance industry, NAG pioneer in the provision of the NAG Library – numerical, machine learning and statistical components ideal for building Quant Libraries, Risk Applications and the like.

NAG also provides best-in-class C++ operator-overloading AD tools for CPU and GPU called dco (derivative computation through overloading) and dco/map (dco meta adjoint programming). The NAG Library and AD tools are used by many of the largest Investment Banks where they are embedded in Quant Libraries and XVA applications. As a not-for-profit company, NAG reinvests surpluses into the research and development of its products, services, staff and its collaborations.

www.nag.com

By completing this form you are accepting the terms and conditions of

WBS Training’s cancellation and data policies.

To Register please e-mail the completed booking form to:

sales@wbstraining.com

FLIGHT DETAILS:

All delegates flying into London on the morning of the event are

reminded that they should arrive 30 minutes before the workshop

starts for registration. The venues West End location is approximately

1 hour from all 3 main London airports, Heathrow, Gatwick and City.

Returning flights should equally allow for the events finishing time.

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World Business Strategies Ltd, offer sponsorship opportunities for

all events, e-mail headers and the website. Contact sponsorship via

telephone on: +44 (0)1273 201 352

DISCLAIMER:

World Business Strategies command the rights to cancel or alter any

part of this programme.

CANCELLATION:

By completing of this form the client hereby enters into an agreement

stating that if a cancellation is made in writing within two weeks of the

event date no refund shall be given. However, in certain circumstances

a credit note may be issued for future events. Prior to the two-week

deadline, cancellations are subject to a fee of 25% of the overall course

cost.

DISCOUNT STRUCTURE:

The discount is available on any day permutation, and can be

combined across delegates within the same company (only at the time

of booking and not retrospectively).

CONTACT:www.wbstraining.com | sales@wbstraining.com

SPECIAL OFFER: When 2 colleagues attend the 3rd goes free!

70% Academic Discount / FULL-TIME Students Only

THE 8TH XVA CONFERENCECCT VENUES-DOCKLANDS, CANARY WHARF, LONDON

13TH - 15TH MARCH 2019

REGISTRATION:Tel: +44 (0)1273 201 352

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