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The Long-Term Effect of Digital Innovation on Bank Performance: An Empirical Study of SWIFT Adoption in Financial Services
John Van Reenen / Markos Zachariadis / Susan Scott
banking / panel dataResource overview

The Long-Term Effect of Digital Innovation on Bank Performance: An Empirical Study of SWIFT Adoption in Financial Services

Paper2010

by John Van Reenen, Markos Zachariadis, Susan Scott

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bankingpanel data

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Suggested foundations for credit and counterparty risk and risk measurement and stress. Specialist prerequisites vary by paper.

Before you read

  1. Credit Instruments, PD/LGD/EAD, and Rating Migration

    Separate default probability, loss severity and exposure.

  2. Conditional Expectation

    Read conditional default and exposure quantities.

  3. Random Variables and Distributions

    Represent losses as a distribution rather than one forecast.

  4. Expected Shortfall and Other Tail Risk Measures

    Distinguish a loss quantile from the average loss in the tail.

Go further

  1. Threshold Models and the Gaussian Copula for Portfolio Default

    Study dependence between defaults.

  2. CVA and DVA

    Connect exposure and counterparty losses to valuation adjustments.

  3. VaR Estimation in Practice: Variance-Covariance, Historical Simulation, Monte Carlo

    Compare risk estimators and their assumptions.

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