RETACH Documentation
Methodology, model assumptions, terms of use, and engagement templates for the S.I.N.S. Framework™ for Digital Resilience.
CRQ Methodology
The RETACH Cyber Risk Quantification Engine applies a frequency-severity actuarial model to produce financial loss estimates for organisations assessed under the S.I.N.S. Framework™. This document describes the full methodology — the model steps, the assumptions behind every constant, and the sources used to calibrate them.
Every number the CRQ Engine produces traces back to a calculation described on this page. We use the same core mathematics as insurance actuaries — Expected Loss = Frequency × Severity — applied to your specific sector, size, and control posture. We then model the distribution of possible outcomes using lognormal statistics to show you not just the average year, but a bad year and a very bad year.
How the model works — five steps
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01Count how often attacks happen (Frequency)Base attack probabilities for six scenario types — phishing, ransomware, financial fraud, data breach, business continuity failure, and insider threat — are drawn from published East Africa sector incident data. A sector multiplier adjusts for the relative attack frequency of the assessed organisation's industry: a Fintech faces attacks 2.4× more often than baseline; a SACCO 1.8×. A risk modifier derived from the organisation's control posture (MFA adoption, backup posture, ODPC status, S.I.N.S. score) adjusts the final likelihood downward where controls are in place.
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02Estimate how much each event costs (Severity)Severity is modelled as a percentage of annual revenue, because an organisation's revenue is the most reliable proxy for the scale of data held, transactions processed, and operational complexity. Ransomware typically costs 18% of annual revenue when it hits. A data breach costs 12%. These percentages are calibrated to East Africa incident cost data and validated against IBM Cost of a Data Breach 2023 and Zurich Insurance emerging markets loss data.
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03Multiply: Expected Loss = Frequency × SeverityThis is the same formula an insurance actuary uses to price a premium. If ransomware has a 30% annual probability and costs KES 9M when it hits, the expected annual loss from ransomware is KES 2.7M. The Engine calculates this for six attack types and sums them. That total is your Expected Annual Loss.
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04Model the distribution (Poisson-Lognormal)The EAL is the mean of a loss distribution, not a guarantee. Real losses follow a lognormal distribution — most years are cheaper than average, but occasionally an event is catastrophic. We use a Poisson-Lognormal model with sector-specific dispersion constants (σ) calibrated from Serianu and Zurich emerging markets data. This gives you the 50th percentile (Expected), 75th percentile (Adverse), and 95th percentile (Severe/Worst-Case) loss figures.
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05Add regulatory fine exposureFor each sector, applicable Kenyan regulatory frameworks are assessed separately. The Kenya Data Protection Act 2019 (max KES 5M, ODPC) applies universally. Sector-specific regulators — CBK, SASRA, CA Kenya, ICT Authority, NC4 — add additional exposure. For Critical Infrastructure sectors, CMCA 2018/2024 s.18 adds up to KES 25M, creating a combined ceiling of KES 30M. These figures are modelled independently from the EAL and added to produce Total Risk Exposure.
Total Risk Exposure = EAL + Regulatory Fine Exposure + Reputational Cost (downtime × revenue/day)
Assumptions & limits
Every modelling assumption is listed here. Where a figure is an estimate rather than an empirical measurement, that is noted explicitly.
| Assumption | What it means | Honest limit |
|---|---|---|
| Frequency from published data | Base attack probabilities from Serianu 2023, CBK, and CA Kenya sector reports | Historical frequency does not guarantee future attack rates. Threat actors evolve. |
| Severity as % of revenue | Impact calibrated as a share of annual revenue — larger organisations face larger absolute losses | Actual severity depends on systems held, data volume, and attacker sophistication — not size alone. |
| Sector multipliers | Fintechs face 2.4× the baseline frequency; SACCOs 1.8×; Critical Infrastructure 2.5–2.9× — from sector incident data | Calibrated from published sector reports. Refined as RETACH engagement data accumulates. |
| Control efficacy | Full MFA reduces risk by 38%; tested backup by 30% — from NIST 800-53 benchmarks | Actual reduction depends on implementation quality, not just whether a control exists. |
| Loss distribution shape (σ) | Lognormal distribution; sector dispersion (σ) calibrated to Serianu and Zurich emerging markets data. CI sectors use σ = 1.10 — the highest constant, reflecting nation-state threat exposure and OT/IT risk. | Not derived from RETACH's own claims dataset yet. Improves as the RETACH Risk Ledger™ grows. |
| Single-organisation scope | Models your organisation's direct loss exposure | Does not model supply chain contagion or systemic sector-wide events. |
| Point-in-time snapshot | Reflects your posture at the time of assessment | Risk changes as threats evolve and controls are added or removed. Reassess annually. |
| FX rate | USD conversion at KES 130 | Exchange rate movements are not modelled. KES figures are primary. |
RETACH CRQ outputs are financial planning estimates based on the modelling methodology described above. They are not actuarial certifications, legal opinions, or insurance advice. Figures should be used for internal risk management, board reporting, and informed conversations with insurers and legal counsel — not as binding loss projections. RETACH Digital Ltd is not a licensed insurer, broker, or legal firm.
Calibration sources
The following published sources are used to calibrate sector multipliers, severity percentages, and control efficacy constants in the CRQ Engine.
Run the CRQ Engine for your organisation
See your Expected Annual Loss, 75th and 95th percentile loss bands, and regulatory fine exposure — calibrated to your sector and size.
CRQ Terms & EULA
By using the RETACH CRQ Engine, you agree to the following terms. These terms govern the use of all quantification outputs, reports, and models produced by RETACH Digital Ltd tools.
All figures produced by the RETACH CRQ Engine are financial planning estimates based on the frequency-severity model described in this document. They are not actuarial certifications, insurance valuations, regulatory assessments, or legal opinions. No output constitutes a guarantee of accuracy, completeness, or fitness for any particular purpose.
CRQ outputs must not be used as the sole basis for insurance purchasing decisions, legal compliance determinations, or regulatory submissions. Regulatory fine exposure figures are indicative estimates based on publicly available enforcement data, not legal advice. Engage qualified legal counsel and licensed insurance brokers for binding decisions.
CRQ outputs may be used for: internal risk registers, board and executive risk reporting, cyber insurance gap analysis conversations, investment prioritisation for security controls, and general organisational awareness. They may not be reproduced in marketing materials, public filings, or third-party reports without written permission from RETACH Digital Ltd.
RETACH Digital Ltd is not liable for any direct, indirect, incidental, or consequential loss arising from reliance on CRQ outputs. The user accepts full responsibility for decisions made based on CRQ figures. RETACH's total liability under any engagement is limited to the fees paid for that engagement.
The S.I.N.S. Framework™, RETACH CRQ Engine, and all associated methodology, scoring models, and outputs are the intellectual property of RETACH Digital Ltd. Reverse engineering, reproduction, or commercial use of the methodology without written licence is prohibited.
Active assessment tools — including the AD Audit module and Pentest Kit — must only be used under written engagement authorisation. Unauthorised use of these tools against systems you do not own or have explicit permission to assess may violate the Kenya Computer Misuse and Cybercrimes Act 2018 and equivalent legislation in your jurisdiction.
Engagement Templates
Standardised deliverable templates used across RETACH engagements. Download and use as the basis for client reporting.
S.I.N.S. Framework™
The S.I.N.S. Framework™ for Digital Resilience is a four-pillar methodology for building organisational resilience against digital risk. It is an implementation alignment layer that translates global standards (ISO 27001, NIST CSF, CIS Controls) into executable programmes for organisations without dedicated security teams.
The pillars are sequenced intentionally — each layer depends on the one before it. You cannot meaningfully govern security risks (Security) without knowing what infrastructure you have (Infrastructure). You cannot segment a network (Network) without managing what connects to it (Systems).
Critical Infrastructure Protection
The RETACH CRQ Engine models organisations in sectors designated as critical infrastructure under applicable law separately from general commercial sectors — with higher frequency multipliers, tighter RTO assumptions, and combined regulatory fine exposure reflecting both data protection and sector-specific cyber legislation.
RETACH's practice includes direct operational security experience inside critical national infrastructure — including enterprise network security, identity management, IRP, and BCP delivery in a mission-critical, geographically distributed environment. That practitioner background informs how the framework is calibrated for CI sectors.
Combined fine = DPA 2019 max KES 5M (ODPC) + CMCA 2018/2024 s.18 max KES 25M (NC4/DCI). Both penalties can be imposed simultaneously for the same security failure. CMCA s.18 also carries a custodial sentence of up to 20 years imprisonment. This does not constitute legal advice — validate with qualified Kenyan counsel.
Book a Critical Infrastructure Security Review
Delivered by a practitioner with direct CI operational experience. Scope covers CMCA compliance obligations, OT/IT separation, BCP for essential services, and NC4 incident reporting readiness.