Continuity of the Use of AI-Based Collection Systems in Credit Collection: The Influence of Employee Perception and Risk Management in Shaping Sustainability Intentions

Abstract

The use of Artificial Intelligence (AI) in the Indonesian banking industry has driven transformation in operational processes, especially in improving customer service in the business initiation process. However, in addition to the business initiation process, AI can be used in the credit collection process, where Bank XYZ is one of the state-owned banks that is a pioneer in the use of AI-based Collection Systems for credit collection activities.

This study aims to analyze and find out how user perception, including risk perception, affects users' sustainable intentions towards the AI-based Collection System at Bank XYZ with a quantitative approach. Data was collected through a questionnaire with respondents using the Collection System (employees) in the billing division at Bank XYZ. The data that has been collected is analyzed through 3 (three) stages, namely the preparation of the questionnaire (pre-test), the main analysis using Structural Equation Modeling - Partial Least Square (SEM-PLS) with an outer model measurement model to understand the basic characteristics of the research sample, and the structural model measurement stage using an inner model to assess the relationship between research variables and hypothesis testing using bootsrapping.

The research update lies in the analysis of the use of AI in the back end process in banking (credit collection) and the identification of risk perception as a factor that also influences Continuous Intention (CI), in addition to other traditional variables in the Expectation Confirmation Model (ECM). The results show that users' perception of intelligence, human nature, and usefulness of AI technology.