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AI to Accelerate Indonesia’s Banking System

Bernard Widjayam, the Head of the Market Conduct Department at the Financial Services Authority (OJK), underscored the significance of incorporating technology into the oversight of financial service businesses. In his statement, he highlighted the limitations of manual analysis when it comes to efficiently and effectively analysing data on behaviour within the industry.

Manually analysing vast amounts of data related to financial service business behaviour can be a time-consuming task. Furthermore, relying solely on manual analysis can introduce the risk of inefficiencies, inaccuracies, and inconsistencies in the data analysis process. It may lead to a lack of coherence and potentially misleading information.

By leveraging technology in the supervision and monitoring of financial service businesses, the aim is to enhance data analysis’s efficiency, accuracy, and reliability. Automation and advanced algorithms can streamline the process, enabling faster and more comprehensive analysis of behaviour-related information. In turn, facilitates timely and informed decision-making for regulatory authorities and promotes a more transparent and compliant financial services sector.

Implementing technology-driven solutions allows for data collection, processing, and analysis automation. By harnessing advanced analytical tools and techniques, regulatory bodies can uncover patterns, trends, and anomalies in behaviour data that may otherwise be overlooked in manual analysis. This comprehensive and data-driven approach enables a deeper understanding of the industry, identifies potential risks or misconduct, and supports proactive regulatory interventions.

Moreover, using technology to supervise financial service businesses helps establish a consistent and standardised framework for data analysis. It ensures that the analysis is conducted systematically and unbiasedly, reducing the potential for human errors and subjective interpretations. It promotes transparency, fairness, and accountability in assessing behaviour within the financial services industry.

Bernard Widjayam also highlighted the potential use of AI and machine learning technologies in monitoring the offerings of financial products and services through various media channels. By harnessing the power of AI and machine learning, regulatory authorities can enhance their ability to detect and assess potentially misleading or non-compliant advertisements and promotions in the financial services sector.

AI and machine learning algorithms can analyse enormous amounts of data from different sources, such as websites, social media platforms, and online advertisements, to identify patterns and anomalies in the marketing practices of financial service providers. It enables authorities to swiftly identify misleading claims, hidden fees, or unfair marketing tactics that misguide consumers or violate regulatory standards.

Using AI and machine learning technologies can significantly augment the effectiveness and efficiency of regulatory oversight in the digital age. These technologies can automate the monitoring process, flagging suspicious advertisements or promotions for further investigation and reducing the burden of manual monitoring on regulatory authorities.

To promote the digitalisation of activities in BPR/BPRS as outlined in pillar 2 of the Indonesian Banking Development Roadmap, CBI, as the Credit Insurance Management Institution (LPIP), has implemented Artificial Intelligence (AI) and utilised credit scoring for credit application analysis.

Implementing AI in credit application analysis is expected to provide higher efficiency and accuracy. By leveraging AI technology, CBI can process customer data quickly and accurately, identify credit risks, and make more precise credit decisions. Moreover, CBI can evaluate the credit profiles of prospective borrowers based on factors such as credit history, income, and assets. It enables CBI to make objective and fair credit decisions.

With the implementation of AI and the utilisation of credit scoring, CBI can accelerate the credit application process, reduce undesirable credit risks, and improve the overall operational efficiency of BPR/BPRS. This step aligns with the vision of the Indonesian Banking Development Roadmap, which emphasises the importance of digitalisation in enhancing the competitiveness of the banking sector.


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