Towards more predictive risk management with Data Science
Artificial Intelligence, Machine Learning, Predictive analysis and modelling, Deep Learning, Image processing...
Coface is leveraging advanced Data Science technologies to manage risks more effectively and predictively for the benefit of its clients.
SCORING: predicting corporate insolvencies to better manage buyer risk
Effective risk management is all about anticipating risks! When it comes to assessing companies' financial health and buyer risk (DRA - Debtor Risk Assessment), Scoring is an essential component of risk management. This is why Coface is constantly improving its internal scoring model. The aim: to anticipate ever more accurately the probability of companies defaulting. This decision-making tool that Coface provides to its clients combines the expertise of Coface's data scientists and its actuaries.
Using advanced artificial intelligence and machine learning advanced technologies, Coface automates part of the production of the DRA by massively exploiting financial data on companies from its 52 enriched information centres around the world, and from other external information providers. To optimise the score's predictivity, Coface also takes into account its payment default history.
Thanks to this improved scoring tool, Coface offers its clients the opportunity to manage their risks even more accurately and efficiently through:
- better qualified financial information;
- refined and relevant predictive analyses;
- modelling that can be customised according to the country in which their business is based;
- a better estimate of credit risk, and more powerful risk underwriting decisions;
- a reduction in claims through better prediction of corporate insolvencies.
As a unique immaterial asset, Coface's business information is enriched and its added value increases!
MACRO-ECONOMIC & FINANCIAL MODELLING: simulating and anticipating the impact of macro-economic shocks on companies
Economic, health or energy crises... How can we anticipate the impact of potential macro-economic shocks on companies' financial balance sheets?
This is the challenging issue to which Coface has tried to address by designing a solution for modelling companies' future financial statements according to different scenarios. The idea is to look one year ahead, rather than looking in the rear-view mirror!
This decision-making tool addresses a dual need for our clients:
- to collect and analyse financial information on companies as early as possible, without waiting for the financial statements to be published (6 to 9 months after the end of the financial year)
- to have access to relevant predictive analyses and reliable growth forecasts on the financial health of companies.
Working with our economists, risk underwriters and Business information teams, the Data Lab collects, aggregates and analyses various sources of data (Coface economic forecasts, IMF data, Banque de France data, government ministries, etc.) to produce predictions that anticipate the financial statements and simulate the impact of potential external macro-economic shocks.
These predictive models, which include massive simulation on balance sheet data from our credit insurance data sources, enable our clients to benefit from:
- an advanced predictive company score, taking into account anticipated financial statements and therefore more reliable growth projections on the financial health of companies;
- better-informed risk underwriting decisions for more effective predictive risk management;
- relevant analyses and a better quality of service to support them in developing their business in a complex and changing economic environment, where any external shock can have a major impact on a company's economic and financial balance sheet.
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