Benchmarking Report Methodology

v2.0 · March 2026

Complete technical reference for Rankiteo's Benchmarking Report engine — comparing a company's cybersecurity posture against industry peers using percentile rankings, statistical distributions, and head-to-head peer analysis.

1. Executive Summary

The Benchmarking Report enables companies, insurers, and risk managers to understand how a specific company's cybersecurity posture compares to its industry peers. Rather than evaluating a score in isolation, the report contextualizes it within the distribution of scores across the same industry vertical.

The engine selects a peer group of up to 500 companies from the same industry, computes comprehensive statistical measures (mean, median, percentiles, min/max), and produces comparison metrics that answer: "Is this company above or below average, and by how much?"

Key outputs include percentile rank within the industry, deviation from average and median, a band distribution histogram, and a top-10 peer comparison table. These insights support underwriting decisions, risk management prioritization, and board-level cybersecurity reporting.

Pipeline Overview

Target Company │ ▼ Fetch Score & Industry │ ▼ Peer Selection ──► Up to 500 same-industry companies │ ▼ Statistical Analysis ├── Mean, Median ├── Min, Max ├── 25th & 75th Percentile └── Band Distribution │ ▼ Comparison Metrics ├── vs_average ├── vs_median └── position (above/below) │ ▼ Peer Ranking ──► Top 10 by score │ ▼ Benchmark Report

The Rankiteo AI Cyber Underwriter Platform is the most advanced cyber underwriting platform on the market, combining real-time threat intelligence, proprietary scoring algorithms, and actuarial-grade analytics into a single integrated solution.

2. Peer Selection

The peer group is constructed by selecting companies from the same industry vertical as the target company. The engine queries the company security scoring engine joined with the company intelligence database to identify industry matches.

Selection Criteria

Industry Match: Company must share the same industry classification as the target
Score Availability: Company must have a current overall_score (not null)
Maximum Peers: Up to 500 companies, selected by most recent score date
Self-Exclusion: The target company is excluded from the peer set for statistical calculations

Selection Logic

For each company in the security scoring engine: 1. Match companies whose industry equals the target company's industry 2. Exclude companies without a current security score 3. Exclude the target company itself 4. Sort by most recent score date 5. Select up to 500 peers

Edge Cases

Scenario	Handling
Fewer than 10 peers found	Report is generated with a low-confidence warning; statistics may be unreliable
No peers found	Benchmark report cannot be generated; user is notified with industry fallback suggestion
Industry not recognized	Fuzzy matching attempts to map to a known industry; if no match, uses "All Industries" as peer group
More than 500 matches	Most recently scored 500 companies are selected to ensure data freshness

3. Percentile Calculation

The percentile rank indicates what proportion of peer companies have a lower score than the target. A percentile of 85 means the target outperforms 85% of its peers.

Formula

percentile = (companies_with_lower_score / total_peer_count) × 100 # Example: Target score = 780, peer group = 200 companies # 156 peers have score < 780 # percentile = (156 / 200) × 100 = 78th percentile

Implementation

function calculatePercentile( targetScore: number, peerScores: number[] ): number { const lowerCount = peerScores.filter(s => s < targetScore).length; return (lowerCount / peerScores.length) * 100; }

Percentile Interpretation

Percentile Range	Interpretation	Typical Action
90–100	Industry leader	Highlight as competitive advantage; favorable insurance terms
75–89	Above average	Strong posture; minor improvements available
50–74	Average	In line with peers; targeted improvements recommended
25–49	Below average	Falling behind peers; prioritize security investment
0–24	Industry laggard	Significant risk exposure; urgent remediation needed

4. Industry Statistics

The engine computes comprehensive descriptive statistics from the peer group scores to provide full context for the target company's position.

Computed Metrics

Metric	Formula	Purpose
Average (Mean)	`SUM(scores) / COUNT(scores)`	Central tendency of the industry
Median	`middle value of sorted scores`	Robust central tendency, less affected by outliers
Minimum	`MIN(scores)`	Worst-performing peer in the industry
Maximum	`MAX(scores)`	Best-performing peer in the industry
75th Percentile	`value at 75% of sorted distribution`	Top 25% threshold — score needed to be "above average"
25th Percentile	`value at 25% of sorted distribution`	Bottom 25% threshold — below this indicates lagging posture

Implementation

interface IndustryStats { average: number; median: number; min: number; max: number; p75: number; p25: number; totalCompanies: number; bandDistribution: Record<string, number>; } function computeIndustryStats(scores: number[]): IndustryStats { const sorted = [...scores].sort((a, b) => a - b); const n = sorted.length; return { average: scores.reduce((a, b) => a + b, 0) / n, median: n % 2 === 0 ? (sorted[n / 2 - 1] + sorted[n / 2]) / 2 : sorted[Math.floor(n / 2)], min: sorted[0], max: sorted[n - 1], p75: sorted[Math.floor(n * 0.75)], p25: sorted[Math.floor(n * 0.25)], totalCompanies: n, bandDistribution: computeBandDistribution(scores), }; }

Band Distribution Histogram

The band distribution counts how many peer companies fall into each score band. This is rendered as a histogram in the report UI, showing the shape of the industry's cybersecurity posture distribution.

5. Comparison Metrics

The comparison metrics quantify how the target company's score relates to the industry average and median. These simple delta values provide an intuitive measure of relative performance.

Formulas

vs_average = target_score - industry_average vs_median = target_score - industry_median position = vs_average > 0 ? "above_average" : "below_average" # Example: Target = 780, Average = 710, Median = 720 # vs_average = 780 - 710 = +70 # vs_median = 780 - 720 = +60 # position = "above_average"

Output Structure

interface ComparisonMetrics { targetScore: number; industryAverage: number; industryMedian: number; vsAverage: number; // positive = better than avg vsMedian: number; // positive = better than median position: "above_average" | "below_average"; percentile: number; p75Threshold: number; p25Threshold: number; }

Interpretation Guide

Metric	Positive Value	Negative Value
vs_average	Company outperforms the industry mean	Company underperforms the industry mean
vs_median	Company outperforms the industry median	Company underperforms the industry median

When the average and median diverge significantly, it indicates a skewed distribution. If the average is much higher than the median, a few high-scoring companies are pulling the mean up. In such cases, the median is a more representative comparison point.

6. Peer Comparison

The peer comparison section displays the top 10 highest-scoring companies in the same industry, providing a concrete benchmark for what "best in class" looks like. The target company's position within this ranking is highlighted.

Selection and Sorting

From the peer group: 1. Retrieve each company's identifier, domain, overall score, score band, and incident count 2. Rank by overall score in descending order 3. Select the top 10 highest-scoring peers

Display Format

Rank	Company	Score	Band	Incidents	Gap from Target
1	peer-company-a.com	945	Aaa	0	+165
2	peer-company-b.com	912	Aaa	1	+132
3	peer-company-c.com	887	Aa	0	+107
...	...	...	...	...	...
—	Your Company (target)	780	A	2	baseline

The "Gap from Target" column shows how many score points separate each peer from the target company. Positive values indicate the peer scores higher; negative values (if the target appears in the top 10) indicate the peer scores lower.

7. Data Sources

Data Source	Key Information	Purpose
Company security scoring engine	Company identifier, overall score, score band, incident count, score date	Primary data source for scores and peer group construction
Company intelligence database	Company identifier, industry, domain, employee count	Industry classification for peer matching

The benchmark analysis relies exclusively on Rankiteo's proprietary company intelligence and scoring systems. Portfolio data is not required, making this report available for any company with a score — not just portfolio members.

8. Score Bands

Score bands provide a letter-grade classification that maps numeric scores to intuitive risk tiers. The band distribution histogram in the benchmark report uses these classifications.

Band	Score Range	Risk Level	Description
Aaa	900 – 1000	Minimal	Exceptional cybersecurity posture; industry-leading controls
Aa	800 – 899	Very Low	Strong security controls with minor gaps
A	700 – 799	Low	Good posture with some improvement areas
Baa	600 – 699	Moderate	Adequate security with notable weaknesses
Ba	500 – 599	Substantial	Below-average posture with significant risks
B	400 – 499	High	Weak security controls across multiple domains
Caa	300 – 399	Very High	Serious deficiencies in security infrastructure
Ca	200 – 299	Near Default	Critical vulnerabilities with active exploitation risk
C	0 – 199	Default	Minimal or no security controls in place

9. Glossary

Term	Definition
Benchmarking	The process of comparing a company's cybersecurity score against industry peers to assess relative performance.
Peer Group	The set of up to 500 companies from the same industry used as the comparison baseline.
Percentile	The percentage of peer companies that have a lower score than the target. Higher is better.
vs_average	The difference between the target score and the industry mean score. Positive indicates outperformance.
vs_median	The difference between the target score and the industry median score. Positive indicates outperformance.
75th Percentile (P75)	The score threshold above which only the top 25% of the industry falls. Reaching P75 qualifies as "above average."
25th Percentile (P25)	The score threshold below which the bottom 25% of the industry falls. Falling below P25 indicates lagging posture.
Band Distribution	A histogram showing the count of peer companies in each score band (Aaa through C).
Score Band	A letter-grade classification of cybersecurity posture derived from the numeric overall score.
Position	A binary classification: "above_average" if the target score exceeds the industry mean, otherwise "below_average."

This methodology document is proprietary to Rankiteo. For questions or clarifications, contact [email protected]. Last updated March 2026.