RTGS Determinant & Sub-transaction Behavior during COVID-19 in Indonesia

Authors

Bastian Muzbar Zams, Bank Indonesia, IndonesiaFollow
Akhmad Ginulur Pangersa, Bank Indonesia, IndonesiaFollow
Gemala Srihati, Bank Indonesia, IndonesiaFollow
Primitiva Febriarti, Bank Indonesia, IndonesiaFollow
Nur Annisa Hasniawati, Bank Indonesia, IndonesiaFollow

Document Type

Article

Abstract

This paper investigates external factors affecting Indonesia’s Real Time Gross Settlement (RTGS) transactions by applying machine learning regularization to identify key variables from a large dataset. A Vector AutoRegression (VAR) model analyzes dynamic links among RTGS sub-transactions, while Impulse Response Function (IRF) analysis examines system behavior during COVID-19 shocks. Using monthly data on 75 economic indicators, we show that 21 variables most accurately capture the movement of Bank Indonesia Real Time Gross Settlement System (BIRTGS) transactions. The study shows that monetary operation sub-transactions most strongly affect other BI-RTGS sub-transactions. Impulse Response Function analysis also finds that shocks in customer transfers and capital market transactions during COVID-19 can negatively impact fiscal soundness and financial stability.

Recommended Citation

Zams, Bastian Muzbar; Pangersa, Akhmad Ginulur; Srihati, Gemala; Febriarti, Primitiva; and Hasniawati, Nur Annisa (2025) "RTGS Determinant & Sub-transaction Behavior during COVID-19 in Indonesia," Bulletin of Monetary Economics and Banking: Vol. 28: No. 3, Article 7.
DOI: https://doi.org/10.59091/2460-9196.2487
Available at: https://bulletin.bmeb-bi.org/bmeb/vol28/iss3/7

First Page

465

Last Page

504

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Country

Indonesia

Affiliation

Bank Indonesia