<ul><li>Credit risk modelling using Merton's Model has long been the go-to framework for assessing default probability in loans or bonds.</li><li>However, in today's volatile financial markets, static assumptions and unstructured data make Merton's Model less reliable.</li><li>To overcome these limitations, integrating generative AI and hybrid models can provide a fresh approach to credit risk modelling.</li><li>These techniques involve processing unstructured data, generating realistic stress scenarios, and combining structural models with data-driven methods.</li></ul>

Revolutionizing Credit Risk Modeling: Beyond Merton in a Volatile World

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