Risk Technology Awards 2018: Moody’s Analytics

MoodysAnalytics

Credit data provider of the year
Credit stress-testing product of the year 
Wholesale credit modelling software of the year

Accounting and regulatory requirements demand transparency in credit risk metric calculations, adequate data quality and robust model development data, often spanning full credit cycles. To help financial institutions meet these challenges, Moody’s Analytics runs several consortia for data sharing and portfolio risk benchmarking under the Data Alliance banner, covering commercial and industrial assets, commercial real estate, and project, infrastructure and asset finance. In addition, the company offers high-quality, off-the-shelf data products for stress testing, International Financial Reporting Standard (IFRS) 9 and the current expected credit loss accounting standard, as well as for models for probability of default, loss given default, earnings at default, expected loss and loan origination models, with web-based tools for visualising, querying and benchmarking the data.

Steve Tulenko – Moodys Analytics
Steve Tulenko, Moody’s Analytics

Data Alliance members contribute private firm data, such as financial statements and loan and default metrics. Moody’s Analytics aggregates, anonymises and analyses the data to create industry benchmark and analytical tools, enabling members to gain insight into usually opaque private markets where internal data is thin. In addition, members can benchmark specific risk metrics such as forward-looking default probabilities generated with Moody’s Analytics products against peer and industry consensus levels.

For enterprise-wide stress testing, the Moody’s Analytics Scenario Analyzer combines relevant data, scenarios, models and reports into repeatable and auditable automated processes. It enables institutions to optimise their stress testing for a variety of management and regulatory purposes, including compliance with the US Federal Reserve’s comprehensive capital analysis and review, IFRS 9, and European Banking Authority and Hong Kong Monetary Authority rules.

Economic, risk and financial data is centralised in a single database for consistency. The Scenario Analyzer can use a broad spectrum of models, including Moody’s Analytics’ off-the-shelf models – such as Commercial Mortgage Metrics and RiskCalc – as well as internally developed models. For flexibility, the system offers configurable engines covering the deployment of most major forecasting methodologies, including linear regression models, arithmetic formula calculations and transition matrices. The Scenario Analyzer also integrates with Moody’s Analytics’ reporting application. All processes within the Scenario Analyzer are repeatable, and automated tasks can be replayed with varying data, assumptions or scenarios. Iterations are kept by the system for future analysis or comparison, with settings and results of every calculation maintained for later reference or audit.

Moody’s Analytics offers a suite of credit-scoring models and applications for the wholesale market covering everything from small business to large private and public companies to commercial real estate and project finance. The models can be applied to a range of tasks, including pre-qualification, origination, ongoing monitoring early warning, benchmarking and limit setting, pricing, reserve allocation, risk-based pricing, stress testing, capital planning and impairment calculations. Clients can use the tools as primary, benchmark or challenger models, or tailor them to meet specific needs using the company’s or their own datasets. 

MoodysAnalytics
(l–r) Damian Watson, Jamie Stark, Pierre-Etienne Chabanel, Rebecca Wagner, Marina Gromova, Chiara Barbaglio, Jelena Ivanovic

Moody’s Analytics’ RiskCalc default-and-recovery analytics and technology enables users to easily and effectively assess the credit risk of private firms, commercial banks, project finance projects and insurance companies. The application produces forward-looking default probabilities using the company’s Expected Default Frequency model, loss given default and expected loss by combining financial statement and equity market information into predictive measurements of standalone credit risk. RiskCalc, which makes use of the Data Alliance input, allows users to assess the risk of a counterparty or portfolio against a peer group by asset size and industry groups.

Stephen Tulenko, executive director, enterprise risk solutions, at Moody’s Analytics, says: “Moody’s Analytics provides financial intelligence and analytical tools supporting our clients’ growth, efficiency and risk management objectives. Our solutions help financial institutions transform – through digitisation and automation – enabling better, faster business decisions. Our solutions are built to help clients grow their business with flexible and modular architecture that facilitates innovation to meet their customers’ evolving needs. Leveraging cloud computing, we combine deep domain expertise in credit analysis, risk management, accounting standards and business information to deliver award‑winning software as a service.”

Judges’ comments

“Comprehensive and deep credit stress‑testing functionality, with impressive recent enhancements”

“More credit stress‑testing functionality, data richness and global usage than other candidates”

“Moody’s Analytics continues to extend its credit data content and associated analytics, extracting maximum benefit from its data pooling initiatives”

“Moody’s Analytics has leadership and critical mass in the wholesale credit modelling market”

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