How degradation of scoring models might impact banks and how to use payment data in forecasting: new issue of Russian Journal of Money and Finance
The second issue of the scholarly quarterly Russian Journal of Money and Finance of 2021 has been published.
In periods of instability, events move fast, and there is an increasing need to use high-frequency indicators making it possible to assess the economic situation very fast – on a weekly or even daily basis. At the outbreak of the pandemic, the Bank of Russia developed a tool based on payment system data enabling virtually real-time monitoring of the situation across industries: this is done on a daily basis, and the findings of monitoring of sectoral financial flows are published on the Bank of Russia website at the end of each month. In her article, Natalia Turdyeva and her colleagues from the Bank of Russia present a methodology for building this high-frequency indicator, analyse the impact of the pandemic on groups of industries and the economy in general based on obtained data, and discuss possibilities for using financial payment data to forecast economic activity trends.
When making decisions on issuing loans to particular clients, banks rely on their credit scoring models. However, even good models might be wrong. Moreover, when economic conditions alter, the percentage of incorrect decisions might increase. To get prepared for such a scenario and mitigate their potential losses, banks should assess in advance how a possible degradation of a scoring model might affect their financial performance. A tool for such assessment based on scenario forecasts of changes in the quality of models has been proposed by Roman Tikhonov and his colleagues from Sberbank.
Variations in price growth rates across regions of a country might complicate the implementation of monetary policy as, despite a single nominal interest rate, regions might have varying real interest rates and, consequently, monetary policy measures would have different effects. Alyona Nelyubina (Bank of Russia; Lomonosov Moscow State University) describes a regional projection model to analyse how the situation in one region might impact other regions, how regions react to common economic changes, and what monetary policy response would be appropriate.
Since the 1980s, many emerging market economies have been experiencing elevated demand for foreign currency assets from households. The implications of this phenomenon for the economy are still not fully understood. In the review of a joint seminar of the Bank of Russia and the New Economic School, Konstantin Egorov (NES) and Alexey Ponomarenko (Bank of Russia) present the findings of research on financial dollarisation, including the reasons for this phenomenon and expenses incurred by households opting for deposits in dollars rather than national currency.
Inflation trends are significantly influenced by inflation expectations – relevant data are usually available from surveys of professional forecasters. However, data on expectations taken into account in the economic model are generally based on a part of the information and might rapidly change under the influence of news. Sergey Slobodyan (CERGE-EI) and Raf Wouters (National Bank of Belgium; Université Catholique de Louvain) show how models can comprise, among other things, the simulation of a mechanism changing inflation expectations through new data on actual inflation and thus provide a realistic representation of actual inflation expectations.
The new issue of the Russian Journal of Money and Finance (No. 2, 2021) is available on its website.