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

Year: 2025

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.

Source: Bulletin of Monetary Economics and Banking

DOI: 10.59091/2460-9196.2487

Authors: Bastian Muzbar Zams, Akhmad Ginulur Pangersa, Gemala Srihati, Primitiva Febriarti, Nur Annisa Hasniawati

Institution: Bank Indonesia

Language: English

Topic: Banking stability, regulation, efficiency

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: diamond

OpenAlex ID: W4414991584

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