When Big data and Data Science Meet Credit Decisioning

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In particular with logistic regression using application, behavioural and bureau data, has become an industry standard accepted as an accurate credit risk assessment tool. Recently, however, financial companies have begun considering how Big Data and advanced Data Science techniques (such as neural networks and GBM) could improve their credit decisioning models. The obstacles that must be overcome before Data Science can be used in this way are both significant and varied (including technological, cultural and legal obstacles).

In this talk Roberta will explain how Data Science can work with financial companies to overcome these obstacles and transform their credit decisioning models.

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