Perancangan Early Warning Indicators Dashboard Pengawasan Bank di Otoritas Jasa Keuangan

Surya Baruna Semenguk, Sumiyana, Dr., M.Si., Ak., CA.

2024 | Tesis | S2 MANAJEMEN (MM) JAKARTA

Secara historis industri perbankan termasuk industri yang berisiko tinggi dengan dampak kerugian yang tinggi. Selain itu, inovasi, teknologi dan globalisasi turut andil untuk memajukan bisnis perbankan lebih kompleks dan berpotensi lebih berisiko. Atas dasar hal tersebut regulator harus mempersiapkan cara atau strategi untuk mendeteksi krisis dan menanganinya secara cepat dan terukur serta didukung dengan tata kelola (governance) yang baik. Salah satu strateginya adalah menggunakan pendekatan berbasis Supervisory Technology (Suptech) yang memanfaatkan data analytics dan business intelligence sehingga mampu mewujudkan kualitas pengawasan efektif dan efisien dan mampu secara cepat mengidentifikasi bank-bank yang berpotensi mengalami permasalahan dan pada akhirnya solusi bisa diberikan lebih awal sebelum masalah menjadi besar.

Tujuan utama penulisan tesis ini adalah untuk merancang suatu tools berupa early warning indicator dashboard pengawasan bank yang bersifat diagnostik dan prediktif sehingga memudahkan otoritas mengidentifikasi posisi bank-bank di antara peers-nya. Pembentukan dashboard dilakukan berdasarkan studi literatur dengan penggabungan indikator kinerja keuangan konvensional (Capital Adequacy Ratio, Return on Asset, Non-Performing Loan, Loan to Deposit Ratio, Posisi Devisa Neto) yang bersifat diagnostik dan indikator pengukuran keuangan modern (Earning Power, Capacity, Investment Scalability, Growth Opportunities, Discounted Cost) yang bersifat prediktif. Selanjutnya untuk mempermudah pengambilan keputusan dibangun visualiasi berbentuk Matriks (GE/Mckinsey nine cell matrix) sehingga dapat diketahui bank mana yang masuk dalam kategori watchlist yaitu bank yang posisinya berada di ruang dengan kinerja terendah baik dari sisi indikator kinerja keuangan konvensional maupun sisi indikator pengukuran keuangan modern.

Berdasarkan hasil dashboard menggunakan data periode keuangan terakhir teridentifikasi 52 bank umum masuk kategori watchlist untuk dilakukan penanganan lebih intensif. Selanjutnya Otoritas Jasa Keuangan dapat menjadikan EWI Dashboard pengawasan Bank ini menjadi salah satu rangkaian proses yang mendukung quality assurance sehingga OJK dapat mencapai internally dynamic flexibility yaitu organisasi yang tetap relevan, inovatif, dan responsif terhadap perubahan internal yang terjadi.

Historically the banking industry has been an industry with high risks and high impact of losses. Apart from that, innovation, technology and globalization have also contributed to advancing the banking business which is more complex and potentially riskier. Therefore, regulators must prepare methods to detect crises and handle these crises quickly and measurably. One strategy is to use a Supervisory Technology (Suptech) based approach which utilizes data analysis and business intelligence so that it is able to create quality supervision more effective and efficient and is able to quickly identify banks that have the potential to experience problems and, in the end, solutions can be provided early before problems arise and become bigger.

The main purpose of this thesis is to be able to design a tool of early warning indicator bank surveillance dashboard that is diagnostic and predictive so that it is easier for the authorities to identify the position of the banks among their peers. The creation of the dashboard was carried out through a literature study with a combination of conventional financial performance indicators (Capital Adequacy Ratio, Return on Asset, Non-Performing Loan, Loan to Deposit Ratio and Neto Currency Position) which are diagnostic and predictive indicators of modern financial measurement (Earning Power, Capacity, Investment Scalability, Growth Opportunities and Discounted Cost). Furthermore, to facilitate decision-making, a GE/Mckinsey nine cell matrix visualization has been built so that it can be seen which banks are in the watchlist category, namely the banks whose position is in the space with the lowest performance both on the side of conventional financial performance indicators and on the sides of modern financial measurement indicators.

Based on the results of the dashboard using the data of the last financial period identified 52 public banks into the watchlist category for more intensive handling. Furthermore, the Financial Services Authority can make the EWI Bank supervision Dashboard into one of a series of processes that support quality assurance so that OJK can achieve dynamic internal flexibility that allows the organization to remain relevant, innovative and responsive to internal changes that occur.

Kata Kunci : Diagnostik, Prediktif, Deteksi Dini, Indikator Bank, Dashboard, Diagnostic, Predictive, Early Warning, Bank Indicator