Digital technology has been raising the competition between banks and other financial service providers, and encourages banks to undergo digital transformation and introduce innovation in their products and services. However, the high investment required cannot be ignored when undergoing the digital transformation. A few research studies have examined the digital transformation effects on bank’s financial performance. This research aims to examine the digital transformation’s effect on bank profitability, specifically on banks with digital business models. Using digital banks’ profitability as the object is the novelty of this study, whereas previous research on bank profitability focused solely on traditional banks. This research utilizes the Panel of Autoregressive Distributed Lag (ARDL) and the panel data from 2016 to February 2023 of the digital business model bank population in Indonesia, which consists of seven banks. The result of the analysis indicates the U-shape relationship between digital transformation and bank profitability, as the digital transformation significantly supports the bank’s profitability in the long run, while it causes profitability deterioration in the short run due to the huge IT investment. This study recommends that banks need to consider the cost of IT investment as well as the required time and optimum strategy in undergoing the digital transformation and achieving targeted profitability.

Changes in customer behaviors after the COVID-19 pandemic have encouraged the transformation of banking systems. Neobanks have emerged as an innovation and entered the banking system to compete with traditional banks by offering new customer experiences. Neobanks transform traditional banking products and services which are delivered through physical interactions into those delivered via digital channels. This paper analyzes traditional banks that have transformed into neobanks, specifically their efficiency after digital transformation. Efficiency was measured using Stochastic Frontier Analysis (SFA), as it is highly accurate in estimating efficiency scores. This study also used a Pooled Mean Group (PMG) estimation of the Panel ARDL (Autoregressive Distributed Lag), as this approach is useful for analyzing the relationship between variables in panel data, to investigate digital transformation as a determinant of neobanks’ efficiency and examine the existence of short-term and long-term relationships between digital transformation and efficiency. We found that the efficiency of neobanks increases after digital transformation. Furthermore, it can be concluded that digital transformation is a determinant of efficiency and that there is long-term relationship between digital transformation and efficiency. In the short term, digital transformation has a significant negative correlation with efficiency, but in the long term, it has a significant positive relationship; this is because the cost of digital transformation initially decreases the profit efficiency, but afterwards, it increases the efficiency.