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Credit Catalyst pulls data from Orbis, widely acknowledged as the leading entity database, into a purpose-built credit platform to help you identify risk and make better decisions quicker. It helps you onboard new counterparties and continue to monitor them for risk factors.
Combining your knowledge of your counterparties with our extensive entity data and risk metrics, Credit Catalyst gives you:
Credit Catalyst can save you time because it can automate much of your credit analysis process. It also gives you a centralized location to store and manage your credit data in structured formats. It gives you:
We deliver standardized financial reports so you can compare and benchmark companies across borders. And it’s not just financial data that’s standardized – you can look at reports in one language, use the currency of your choice, and even activity classifications such as SIC codes are harmonised, so you can segment your portfolio accurately.
The integral risk module means you can create a scorecard that automatically rates any company you view in Credit Catalyst. The module is flexible and you can adjust the weight given to various elements and set conditional parameters. You can include quantitative, qualitative data in your model and combine data from Credit Catalyst with your own knowledge of a company, to set recommended credit limits.
You can create benchmark values, compare companies’ financial health and measure your own internal ratings against them. Variables include probability of default, propensity to become bankrupt, suggested credit limit, plus other predictive indicators and risk scores. There are three key scores:
The financial score assesses the creditworthiness of a company, grading companies based on how well they can meet their financial commitments. It’s a probability of default model, based on the analysis of financial statements. It’s a through-the-cycle probability of default (TTC PD). The output is tied to the closing date of a set of accounts, it also analyses key financial ratios, which are scored independently. There are four categories:
The model also includes the probability of default which reflects the degree of certainty (in quantitative terms) that the company will go into default in the next 18 to 24 months, a confidence level, and a recommended credit limit.
Detailed financial data is simply not available for many companies so we also offer the qualitative score. This score measures the creditworthiness of a company based on non-financial information such as strength of shareholders, country specific risks, longevity of the company, legal form and sector-specific risks. The model also includes a confidence level and qualitative credit limit.
This adjusted score is created using modelling that’s been adapted to be more sensitive to the economic environment by taking specific sector and regional factors into account. It uses the financial score to reflect current creditworthiness with several quantitative variables, such as sector and macroeconomic factors, to forecast the financials of a company based on ‘impact scenarios’. These impact scenarios are reviewed regularly to offer a score that is more sensitive to market conditions.
Sourcing stories from a range of newswires and news aggregators, we then apply machine learning to create a new Sentiment Score based on negative news. This powerful application of AI is not only an efficient news filter, but also delivers valuable early warning indicators. Our research shows that credit sentiment scores increase, six to eight months before major credit events.
Use BitSight’s industry-leading cybersecurity analytics to understand the level of cybersecurity risk posed by your third parties. BitSight’s cybersecurity analytics provide insight into an organization’s cybersecurity performance, which can be used to:
Assess the cybersecurity risk associated with key clients
Enhance the client due diligence and risk management process. Strong cybersecurity risk management practices often demonstrate broader managerial effectiveness.
Our new spreading tool harnesses the power of machine learning, combined with a human expert to check the output, for super-fast and accurate financial spreads.
Simply upload the financial data in pdf format and get the output delivered seamlessly either in your own ‘private Orbis zone’ or your Catalyst portfolio.
The company’s financials are spread into the standard Orbis financial format, so you can:
This tool is powered by the award-winning QUIQspread™ from Moody’s Analytics. The tool works with Orbis, Credit Catalyst and Procurement Catalyst. It’s ideal if you have financials for a company in more detail than are available in Orbis, or a more recent version has been sent to you directly.
Credit Catalyst has a range of ‘views’, including the dashboard view and the counterparty view, so you can look at your portfolio or individual counterparties from different perspectives. The dashboards are simple to customize and are focused on helping you spot risk quickly.
As well as viewing and analyzing data within Credit Catalyst, you can easily access it through your own in-house or third-party systems. We offer contemporary API solutions, plus our own purpose-built connectors, combined with high levels of support from our customer success teams.
Corporate credit risk
Compliance and financial crime
Tax and transfer pricing
Business development and strategy
Corporate finance and M&A
Data management
Supplier risk and procurement
Corporate
Financial institutions
Professional services and the Big 4
Government and not for profit
Academic
Data
