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The need to leverage non-traditional data to improve decision making and credit risk management

July 24, 2020 | grandstands

Experian is partner of France FinTech and is involved in the fintech ecosystem. Ozgur Ererdem, presents the Web Data Insights solution through this platform. 

Assessing the credit risk of companies, in particular SMEs, represents a major challenge for financial organizations.

Indeed, the lack of available data or the absence of a credit history often prevents financial organizations from making an informed decision. This can be particularly problematic, especially for newly created companies, therefore without a history. Even in situations where strong databases are available, the need to constantly improve risk models poses real challenges for financial institutions.

In this context, Experian has developed an innovative new methodology that uses artificial intelligence and machine learning to collect, classify and analyze multiple data sources from the web. This allows the creation of new models of predictive credit risk management that go well beyond the “traditional” method of scoring based on internal and external data sets.

How does this Web Data Insights solution work?

Experian's Web Data Insights solution unites cutting-edge technology and advanced analytical capabilities into a single, easy-to-deploy API that can transform SMB decision-making throughout their journey. It automatically selects, collects and analyzes relevant public web data to provide more detailed indications on SME activity, such as the presence of the company in business directories, in online media and social networks, its membership trade or industry associations or professional bodies, or its links with academic institutions and government agencies. All this unstructured information is then converted into actionable insights using sophisticated text mining and sentiment analysis algorithms to create temporary “clusters” then into scores and finally into index each representing different degrees of risk. credit.
These results can be used independently or in combination, that is to say that the existing results and models are crossed to optimize their precision.

Scores are generated and combined in just a few seconds and are made available via standard API interfaces that can be queried by our customers' decision-making system, in real time.

What are the concrete benefits of Web Data Insights?

Our web data analytics technology took over five years to develop. WDI enables financial organizations to transform their processes for accepting requests from SMEs by being more precise and faster, allowing faster approval of requests from the best clients, reducing manual processes and providing proactive warning indicators on the customer's propensity to buy, to turn to competition, or to default.

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