GCRI · Manajemen Risiko Sistemik
Metode kuantitatif dan kualitatif
penilaian risiko uses numbers where data support them and structured judgement where they do not. Probabilistic models, loss distributions, Elisitasi pakar, bow-tie diagrams and risk matrices each answer different questions and fail in different ways. This page sets out how the main methods work, when each is fit for purpose, and how combining them keeps an assessment honest about what is known and what is assumed.
Quantitative and qualitative methods on the record.
Quantitative and qualitative methods: how the risk develops.
Probability, uncertainty and judgement. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Models need data that fit
Frequency and severity models work where events are numerous and recorded consistently. For rare, novel or changing risks the data are thin, and a precise-looking number can carry more assumption than evidence.
Judgement carries biases
Experts anchor on recent events, overestimate their own precision and converge in groups. Structured elicitation reduces these effects by separating estimates, asking for ranges and scoring calibration.
Matrices compress information
Likelihood and consequence matrices are quick to use, but they rank risks coarsely, can reverse orderings and hide correlated losses. They suit screening, and need other methods before a major decision.
Methods combine through structure
Fault trees, event trees and bow-tie diagrams link causes, controls and consequences. They provide a frame into which quantitative estimates and expert judgement can be placed and checked.
Cascade and stress lab.
Layar yang akan digunakan sebuah tim untuk mengikuti subjek ini: ukuran, status, dan keputusannya. Nama adalah contoh dan nilai bersifat ilustratif.
Cascade and stress lab
Quantitative and qualitative methods · National system · Scenario SC-40
Interdependency graph
red: failed in scenario
Cascade sequence
- T+0HAZHeatwave and drought
- T+6hENGThermal plant derated, cooling water
- T+9hICTData centre on backup power
- T+14hWATPumping reduced, pressure loss
- T+20hHLTHospital water supply at risk
Service loss by system
Methods must be fit for risks that cross domains.
- AirKeterkaitanHydrological risk is mostly quantified with simulation and extreme value statistics.What to watchUncertainty ranges reported with return periods
- KesehatanKeterkaitanEpidemic risk combines transmission models with expert judgement early in outbreaks.What to watchStructured elicitation records
- Keanekaragaman hayatiKeterkaitanEcosystem risks often have qualitative evidence only, which matrices flatten.What to watchQualitative evidence kept as such
Method comparisons are designed for the seri Metode dan Teknis. Cox showed in 2008 that risk matrices can rank risks inconsistently; the page sets out when quantitative, semi-quantitative and qualitative methods each fit.
- Comparisons of assessment techniques applied to the same risk.
- Cases where a Matriks risiko misled a decision.
How quantitative and qualitative methods is modelled, measured and tested.
Model, asumsi, data, dan ketidakpastiannya, dalam bentuk yang akan diperiksa ilmuwan atau insinyur. Strukturnya mengikuti metode yang dipublikasikan. Nilai yang digambar bersifat ilustratif, bukan temuan.
Model, persamaan, dan asumsi
The model structure used for quantitative and qualitative methods, the assumptions it makes and how each is tested.
Ri = f(Hi, Ei, Vi, Ci)bahaya, keterpaparan, kerentanan, dan kapasitas penanggulanganEAL = ∑k pk · Lkatas peristiwa k dengan probabilitas tahunan pkxt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error| Asumsi | Mengapa ini dibuat | Bagaimana ini diuji |
|---|---|---|
| Bahaya dan eksposur bersifat independen dalam satu peristiwa | Menjaga integral kerugian tetap dapat dihitung | Bandingkan dengan pencocokan kopula pada catatan gabungan |
| Keterkaitan bersifat linear di dekat titik operasi | Membiarkan guncangan merambat melalui A | Uji di luar rentang linear lalu bandingkan |
| Kurva kerentanan dapat dipindahkan antartempat | Kurva lokal jarang tersedia | Validasi terhadap kerugian teramati jika tersedia |
- Masukan
- dataset berversi dengan asal-usul yang tercatat
- Keluaran
- distribusi, bukan angka tunggal
- Kode
- dirilis bersama kartu model dan pengujiannya
- Reproduksi
- data, kode, lingkungan, dan seed yang sama
Apa yang diukur, dan seberapa baik.
Setiap indikator membawa satuan, frekuensi, jenis sumber di baliknya, dan label bukti yang akan dibawa suatu nilai. Tidak ada nilai yang ditampilkan: sebuah program menyediakannya berdasarkan wewenangnya sendiri.
| Indikator | Unit | Kadensi | Jenis sumber | Label |
|---|---|---|---|---|
| Risks assessed with quantitative estimates | percent of principal risks | tahunan | Assessment records | DILAPORKAN |
| Calibration of expert estimates | calibration score on seed questions | per elicitation | Structured expert judgement records | TERAMATI |
| Loss event records | count of events with cause and amount recorded | berkelanjutan | Internal loss databases | TERAMATI |
| Assessment uncertainty range | ratio of upper to lower bound | per penilaian | Assessment outputs | ESTIMASI |
| Controls with tested effectiveness | percent of key controls | tahunan | Control testing records | DILAPORKAN |
| Method documentation completeness | percent of assessments with method, data and assumptions recorded | tahunan | Assessment files | DILAPORKAN |
Asal bukti.
Set data publik bernama dan catatan kelembagaan, masing-masing dengan kelas lisensinya. Sumber berdasarkan perjanjian hanya digunakan sesuai ketentuannya dan tidak pernah diterbitkan ulang.
| Sumber | Apa yang diberikannya | Kelas lisensi |
|---|---|---|
| IEC 31010 Teknik penilaian risiko techniques | Descriptions, strengths and limits of more than forty techniques | Licensed standard, purchase required |
| Basis data bencana internasional EM-DAT (CRED, UCLouvain) | Disaster events with human and economic impacts | Free for non-commercial use with registration |
| Kerangka Kerja Sendai untuk Pengurangan Risiko Bencana 2015-2030 Monitor and national disaster loss databases | Published reporting of disaster losses against Sendai targets | Publik, ketentuan penggunaan PBB |
| TU Delft expert judgement database | Past structured expert judgement studies with calibration data | Licence to check |
| Published operational loss data consortia summaries | Aggregate operational loss patterns in financial services | Members only; public summaries (to check) |
Siapa yang memutuskan, dan apa yang dilayani bukti.
Risiko Sistemik Management prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Siapa yang memutuskan | Pertanyaannya | Bukti yang dilayani halaman ini |
|---|---|---|
| Risk functions and analysts | Which method fits a given risk and decision | Method selection guides; documentation standards |
| Boards and executives | How much confidence to place in an assessment before acting on it | Uncertainty ranges; method documentation; calibration records |
| Regulator dan pengawas | Whether an institution’s risk models are fit for the use made of them | Model documentation; validation and back-testing evidence |
Keluaran yang dihasilkan topik ini
- Method selection guides keyed to the question and the evidence available
- Structured Elisitasi pakar protocols with calibration
- Bow-tie and fault-tree templates linked to registers
- Assessment files that record data, assumptions and ranges
What methods experts ask.
- Is there enough relevant data to estimate probabilities, or would numbers convey a false sense of precision?
- What kind of uncertainty dominates: randomness, lack of knowledge, or disagreement about how the system works?
- How sensitive is the decision to the parts of the analysis that are least certain?
- How can expert judgement be elicited so that it is transparent and less prone to bias?
Kinds of uncertainty.
Randomness
Natural variability that persists even with perfect knowledge, such as weather from year to year. Probability handles it well.
Lack of knowledge
Uncertainty that more data or research could reduce. It should be shown, not hidden in a single number.
Disputed structure
Where experts disagree on models, probabilities or values. Scenarios and robust decision methods suit it better.
A toolkit, matched to the problem.
- 01
Statistical and probabilistic models
Frequency analysis, extreme value methods and Bayesian inference from probabilitas dan statistika. Limits: rare events are poorly sampled, and past data may not reflect a changing system.
- 02
Kuantifikasi ketidakpastian
Kuantifikasi ketidakpastian dan validasi model propagates input uncertainty through models and tests them against data. Limits: it cannot capture what the model leaves out.
- 03
Penilaian pakar terstruktur
Formal elicitation protocols that calibrate and combine expert views. Limits: time-consuming, and experts share blind spots.
- 04
Qualitative assessment
Scales, matrices and narrative analysis. Useful for communication and screening, but risk matrices can rank risks inconsistently and should not be the only tool.
Cara hal ini dikaji, dan apa yang tidak dapat dinyatakan metodenya.
- 01Probabilitas dan statistikaPemodelan frekuensi dan keparahan · Ketergantungan antarrisiko · Menggabungkan data dan penilaianDiterapkan di sini
- 02Kuantifikasi ketidakpastian dan validasi modelPerambatan ketidakpastian masukan · Pemisahan jenis-jenis ketidakpastian · Pembingkaian ketidakpastian mendalamDiterapkan di sini
- 03Analisis keputusan dalam ketidakpastianPemilihan penanganan multikriteria · Pohon keputusan untuk rencana kontingensiDiterapkan di sini
- 04Perancangan skenario dan uji tekananDesain skenario lintas sektor · Uji tekanan terbalik · Dampak putaran keduaDiterapkan di sini
Where this page’s references lead.
Badan dan dokumen yang menjadi acuan halaman ini. Status dan edisi berubah; setiap tautan menuju badan penerbitnya.
Tanya jawab.
Are risk matrices reliable?
What is structured expert judgement?
When should risk be quantified?
Are quantitative methods always better?
What is wrong with risk matrices?
How should uncertainty be communicated?
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Bawa metode, dataset, atau pertanyaan.
Informasi dan pertanyaan sudah terbuka hari ini. Sebuah pertanyaan menerima nomor referensi dan menyebutkan langkah berikutnya; lamaran, pembayaran, alokasi komputasi, dan pendaftaran hanya dibuka ketika tim, ketentuan, dan kapasitas tinjauannya tersedia.
Dokumen hukum.
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