Financial Risk Analytics

Addressing evolving risk and regulatory capital requirements with scalable and modular cloud solutions

Financial Risk Analytics provides products and solutions to financial institutions to measure and manage their counterparty credit risk, market risk, regulatory risk capital and derivative valuation adjustments. Using the latest analytics and technology such as a fully vectorized pricing library, Machine Learning and a Big Data stack for scalability, our products and solutions are used by the largest tier-one banks to smaller niche firms. Our risk analytics solutions are available deployed, in the cloud or can be run as a service so we free up your internal resources to focus on your business priorities.

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Equity Forecasting Utility Now available in the Risk Bureau app

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Financial Risk Analytics For sell-side traded markets and buy-side

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Trusted Data, Analytics and Expertise

Gain unique insights with our curated data and analytics combined with your internal or third-party data

Cloud compatible across major providers

Pay only for what you use with technology built to scale up or scale down depending on your needs

Reduce Total Cost of Ownership (TCO)

Leverage our platform’s turnkey capabilities and project acceleration track-record without sacrificing flexibility

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Traded Market Risk

Supports regulatory and market risk requirements

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XVA

A flexible, cloud-based solution delivering deal-time insights to the XVA desk

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Counterparty Credit Risk

A flexible, cloud-based solution that supports counterparty credit risk and regulatory capital requirements

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Scenario Stress Testing

Create scenarios at scale and comply with global stress testing requirements

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Risk Bureau

Access useful insights online in the cloud, on demand and via our mobile app

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Buy Side Risk

CVA, VaR and other Risk Measures for the Buy Side

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Videos


Chartis RiskTech Buyside 50	RiskTech100 2022: Winner's Interview	Financial Risk Analytics solutions	Buy Side Risk Analytics Solution	FRTB challenges for banks

Thought Leadership/Case Studies

Financial Risk Analytics FAQ

What is XVA?

X-Value Adjustment (XVA) is a collective term for “valuation adjustments” made to derivative trades to reflect various costs related to the trade. The first valuation adjustment was Credit Value Adjustment (CVA); which reflect the credit risk for a given counterparty of a trade. Since the creation of CVA, additional valuation adjustments have been created to capture the cost of funding (FVA), cost of your party defaulting (DVA), cost of collateralization (KVA) and the cost of initial margin (MVA).

What is SA-CCR?

The Standardized Approach for counterparty credit risk (SA-CCR) is the capital requirement framework under Basel III addressing counterparty risk. The SA-CCR exposure-at-default calculation drives a bank's regulatory capital calculations and is a measure of counterparty credit risk as it calculates the exposure at default (EAD) of derivative trades with counterparties. SA-CCR is calculated as if a counterparty were to default today as the current value of the trade plus an add-on which measures potential future exposure (PFE). The framework replaced both non-internal model approaches (non-IMA): the current exposure method (CEM) and the standardized method (SM).

What is FRTB?

The Fundamental Review of the Trading Book (FRTB) refers to a comprehensive restructuring of market risk regulatory capital requirements published by the Basel Committee on Banking Supervision (BCBS) between 2016 and 2019 in response to the financial crises. After a few iterations since 2016, BCBS published the final version of the framework in January 2019, and local regulators are starting to release their final translation of FRTB into local law.

With FRTB, banks will have to comply with new rules by 1 January 2023, but a lot of retro planning, implementation and model validation work as well as regulatory approval is required in order to publish official capital numbers by this date. Banks operating trading books will have to confirm to their respective supervisory authorities whether they wish to pursue a Standardized Approach (SA) calculation or obtain approval for an Internal Model Approach (IMA) for each desk in scope.

What is the difference between FRTB and previous regulations?

FRTB introduces a number of changes for market risk capital requirements including stricter boundaries between the bank’s Trading and Banking Book allocations (i.e. for active trading vs. held to maturity) and fewer possibilities to move trades between them. Instead of a top-of-the-house model approval, banks will have to seek approval at the level of each Regulatory Trading Desk as well as calculating consolidated capital requirements either under the Standardized Approach (SA) or the Internal Model Approach (IMA). Risk Factors to be included in IMA calculations will need to be evidenced as derived from sufficiently observable or liquid instruments (thereby becoming “modellable”), else banks will have to calculate a Stressed Expected Shortfall (SES) add-on for them instead.

The IMA framework also switches from the usual VaR metric to an Expected Shortfall-based risk measure based on the risk type and associated liquidity horizon. In addition, eligible desks will need to demonstrate they pass not only back testing requirements but also a P&L Attribution test designed to reduce any gaps between front-office and risk models which will often increase risk factor granularity compared to existing VaR models. Failing these criteria, desks will have to fall back to the new Standardized Approach which although still based on close-ended sensitivity-based calculations, still increases in complexity and requires implementation changes.

What is ISDA SIMM?

The International Swaps and Derivatives Association (ISDA) standard initial margin mode (SIMM) is a risk sensitivity-based approach to calculate initial margin (IM) for uncleared derivatives ISDA providing model parameters to calibrate for each product class on historical data considering a period of relevant financial stress. Over-the-counter (OTC) derivatives are categorized into one and only one of the following four Product Classes: RatesFX, Credit, Equity, and Commodity. Under ISDA SIMM, initial margin is calculated using sensitives as inputs. This includes Delta and Vega such that the initial margin would cover 99% confidence given a 10-day margin period of risk. For each product class covered ISDA specifies which sensitivities are required. For Equity, Commodities & FX spot prices are bumped 1% to calculate deltas, and volatility is shifted 1% to calculate vegas. For Interest Rates, curves are bumped at 12 points to calculate deltas.

What is Scenario Stress Testing?

A bank stress test is an analysis conducted under hypothetical unfavorable economic scenarios, such as a deep recession or financial market crisis, designed to determine whether a bank has enough capital to withstand the impact of adverse economic developments. The importance of robust and rigorous stress testing has moved to the top of the agenda of risk management priorities with many banks having to comply with multiple regulatory regimes i.e. US CCAR & DFA, UK BoE/PRA and ECB/EBA requirements.

In contexts where firms have discretion over the design of scenarios, they must make a large number of subjective decisions around scenario definition. Scenario Stress Testing (SST) allows users to specify hypothetical, historical or regulatory shocks and revalue their portfolio to understand market-market (MTM) loss and changes to counterparty credit exposure. Using Scenario Stress Testing, users can specify shocks to a subset of risk factors which are expanded to all the risk factors in their portfolio through a combination of rules and statistical methods. Banks construct scenarios thus allowing stress testing to be a pro-active process they can use for internal risk and business planning.

Leadership Team

Mark Findlay

He is the Global Head of S&P Global's (now part of S&P Global) Financial Risk Analytics business which provides award winning products and solutions to financial institutions to measure and manage their counterparty credit risk, market risk, regulatory risk capital, derivative valuation adjustments as well as custom on demand risk services. Using the latest analytics and technology such as a fully vectorized pricing library, Machine Learning and a Big Data stack for scalability, the products and solutions are also available in the cloud and are used by the largest tier-one banks to smaller niche firms.Prior to joining S&P Global, Mark worked as a Partner at TLG, a specialist risk management consultancy in London. Previously, Mark held Chief Operating Officer positions in financial markets trading and quantitative risk management roles at ABN AMRO, UBS and Bank of America Merrill Lynch. He was also the Capital Management Program Director of global markets at HSBC.Mark holds an MBA from CASS Business School, University of London, UK.

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Vinay Nayak

Vinay has over 16+ years of Software Engineering experience in various industries including Financial Services, e-Commerce, Retail and Publishing. An expert in architecting and developing big data systems on the Cloud both for batch and real-time analytics, he is passionate about technology and innovation, focussing on its application for solving business needs.Vinay holds a Bachelor's degree in Electronics & Telecommunications from University of Mumbai.

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Stuart Nield

He has worked on many aspects of risk in his career and has held senior positions in risk management, quantitative analytics and system development. Over a 15-year career, Dr. Stuart has worked for Barclays Capital, UBS Investment Bank and Detica (a data analytics consulting firm). He has a passion for developing risk software that solves business problems in a simple and elegant way.Stuart has a first class honours degree and Ph.D. in Physics from the University of Cambridge.

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Allan Cowan, Ph.D.

As global head of Financial Engineering, Dr. Cowan is responsible for the R&D initiatives for the Financial Risk Analytics team. He oversees the research and development of the quantitative libraries and methodology used in the groups counterparty credit risk and xVA solutions. With over 13 years of experience, he is an expert in the field of derivatives valuations, regulatory risk and xVA management. Dr. Cowan joined Markit, now S&P Global, through the 2011 acquisition of QuIC Financial Technology, where he held the role of senior financial engineer. He took on responsibility for the Financial Engineering team in October 2016. He attained a Ph.D. in physics from the University of British Columbia, Canada.

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Abhay Pradhan

Abhay oversees technology strategy and vision for the Financial Risk Analytics product suite. He also researches and evaluates new technology for the next generation of analytics. In a career spanning 17 years, he has designed and implemented large scale distributed systems, for pricing and risk analytics, at major financial institutions.Abhay has a Masters in Finance from London Business School and a Masters in Electrical and Computer Engineering from the University of Texas at Austin, specializing in distributed networks.

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Vikas Valand

Vikas Valand leads the implementation of Financial Risk Analytics software products, both deployed and in the cloud, through a world-wide team of project managers, quantitative analysts and technology subject matter experts. He also manages our customer support and communication functions.Vikas has previously run banking operation teams, worked in Risk Management and as a consultant in Financial Risk Management, bringing 18 years of combined industry and Big 4 consulting experience covering regulatory change, risk governance, model & methodology development, validation and assurance.

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Financial Risk Analytics

Addressing evolving risk and regulatory capital requirements with scalable and modular cloud solutions

Trusted Data, Analytics and Expertise

Cloud compatible across major providers

Reduce Total Cost of Ownership (TCO)

View our product set

Videos

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Leadership Team

Mark Findlay

Vinay Nayak

Stuart Nield

Allan Cowan, Ph.D.

Abhay Pradhan

Vikas Valand