Analysis of Operational Risk Mitigation in Customer Identification Files (CIF) Management at PT. Bank SUMUT

Abstract

Penelitian ini mengkaji mitigasi risiko operasional pada proses Customer Identification File (CIF) di PT Bank Sumut dengan menerapkan metode Failure Mode and Effect Analysis (FMEA) dan Fault Tree Analysis (FTA). Tujuan utama penelitian adalah mengidentifikasi kondisi kritis yang memicu kegagalan proses CIF serta merancang rekomendasi mitigasi yang tepat. Metode FMEA diaplikasikan untuk menentukan Severity (S), Occurrence (O), dan Detection (D) pada beberapa failure mode, menghasilkan Risk Priority Number (RPN) tertinggi pada kegagalan pemindaian identitas nasabah (RPN=50) dan pengisian data ambigu (RPN=48). Selanjutnya, FTA memetakan akar penyebab kegagalan tersebut ke dalam dua kategori utama: human error (kurangnya pemahaman SOP dan pelatihan staf) serta system failure (sinkronisasi batch-based antara CBS dan ARS, dan antarmuka modul yang kurang intuitif). Hasil analisis menunjukkan bahwa kelemahan paling mendasar terletak pada pemahaman karyawan terhadap prosedur serta minimnya validasi otomatis dalam sistem, sedangkan deteksi dini masih lemah (D=4–5) sehingga sering kali kegagalan hanya terungkap saat audit. Berdasarkan temuan ini, penelitian merekomendasikan perbaikan SOP, pelatihan berkala, implementasi real-time synchronization, dan mekanisme validasi otomatis untuk menurunkan RPN, memperkuat kepatuhan regulasi, dan meningkatkan kualitas data nasabah

This study examines the mitigation of operational risks in the Customer Identification File (CIF) process at PT Bank Sumut by applying the Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) methods. The objective of the research is to identify critical conditions that trigger failures in the CIF process and to design appropriate mitigation recommendations. The FMEA method was applied to determine Severity (S), Occurrence (O), and Detection (D) on several failure modes, resulting in the highest Risk Priority Number (RPN) for the failure of customer identity scanning (RPN=50) and ambiguous data entry (RPN=48). Next, FTA mapped the root causes of these failures into two main categories: human error (lack of understanding of SOP and staff training) and system failure (batch-based synchronization between CBS and ARS, and a less intuitive module interface). The analysis results indicate that the most fundamental weaknesses lie in employees' understanding of procedures and the lack of automated validation in the system, while early detection remains weak (D=4–5), often resulting in failures being revealed only during audits. Based on these findings, the research recommends improving SOPs, conducting periodic training, implementing real-time synchronization, and establishing automatic validation mechanisms to reduce RPN, strengthen regulatory compliance, and enhance the quality of customer data