Data & technology: from smart data to predictive risk management solutions

Because companies now need to go beyond simple access to qualified and added value information, Coface combines the wealth of its data, its unique insights and input from its experts with Data Science and Artificial Intelligence technologies to provide its clients with predictive risk management solutions. Or how to turn commercial risk into growth opportunity!

"Previously in our Data, Technology & Risk Management series..." we looked at how Coface combines Big Data with the strategic governance of its data assets to upgrade its human risk management expertise to serve its clients. But how can this credit data and information be converted into advanced decision support solutions, enabling clients to manage their commercial risks in a predictive way? This is what we are going to explore now.

 

Exclusive data + Coface expertise = unique credit information

Our position as global leader in trade credit insurance for over 75 years (!) combined with our expertise in risk management and the wealth of our data assets enable us to generate unique data for our clients:

  • Descriptive: our scores and financial information provide a detailed, factual analysis of past events, which feeds into our clients' decisions, giving them a better overall understanding of a company's situation.
  • Predictive: our models and algorithms enable us to anticipate a company's solvency and default risk over a 12-month period.
  • Prescriptive: based on predictive data and analysis, our credit recommendations determine the best approach to take to minimise the risk of insolvency.

The in-depth analysis of our 700 risk experts enhances this exclusive data and transforms it into unique credit information. This information is then delivered to our clients and partners to help them make the right decisions and trade smarter.

 

Data Science & Artificial Intelligence: predictive risk management  

Governing is about forecasting, and effective risk management is about anticipating risks! Evaluating the probability of company bankruptcy over 1 year, spotting weak signals, modelising the impact of possible macro-economic shocks on company balance sheets, getting to know suppliers better... In the era of all-data and new technologies, companies of all sizes are now striving to benefit from exclusive economic perspectives (insights), predictive analyses and more advanced risk management solutions, enabling them to better predict possible threats (client risk, supplier risk) to their business portfolio.

At Coface, we can't predict the future. But we can help you to anticipate threats and limit business risks as much as possible! For Coface and its Data Lab teams, new technologies open the way to an (almost) infinite laboratory of possibilities. Focused on the underwriting business, the Data Lab leverages Coface's data assets and artificial intelligence technologies (Data Science, Machine Learning, Deep Learning) to design innovative risk management services and products.

Together with our economists and risk experts (risk underwriters, credit analysts, underwriters), the Data Lab teams collect, cross-reference and analyse massive volumes of data (Big Data), using artificial intelligence and advanced analytics algorithms to deliver powerful decision-making solutions easy to use for our clients:

  • Advanced analytics solutions: compare in real time the financial ratios between similar companies on more than 5 million financial statements, anticipate risks and identify at a glance  the best investment opportunities from a dynamic dashboard, based on the scores and key indicators produced by Coface's economists.
  • Scoring solutions to estimate the probability of a company defaulting in 1 year and better manage debtor risk.
  • Modelling solutions for +1 year financial statements to simulate the impact of macro-economic shocks on companies, according to different scenarios.

For our clients, these solutions help to minimise risk, while opening the way to new opportunities for growth, through:

  1. Better-qualified financial data and unique credit information
  2. Advanced analysis, models and predictive scoring
  3. A better assessment of credit risk, and a higher level of explanation of underwriting decisions
  4. Reduced claims experience and detection of early warning signals
  5. Increase the number of sales leads generated

Knowhow to transform "Big Data" into "Smart Data"!

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