Curated Measure
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The Global Corporate Cyber Risk Exposure Index

Monitor corporate cyber risk exposure globally—derived from earnings calls and decomposed into management disclosure vs analyst attention.

Last data refresh Mar 25, 2026 • 5 series in this Curated Measure

At a glance:

Cyber Risk Exposure Index

Coverage

Public firms, 80+ countries, 2003-present.

Methodology and data

Granularity

Earnings-call level (firm-panel export: one row per call).

Source

LSEG earnings-call transcripts (English).

Update schedule
Last data refresh Mar 25, 2026. Update frequency:

Quarterly
Export shape

Time-series aggregates; firm-panel call-level rows.

Access

Free preview; exports depend on plan.

Access details • Pricing

Overview

The Cyber Risk Exposure Index measures how much of a firm's earnings call is devoted to cyber topics. It is computed as the number of sentences in an earnings call that contain at least one cybersecurity keyword (247-term dictionary).

Designed for:

  • tracking cyber risk exposure over time (firm, sector, global),
  • cross-sectional research across firms/industries/countries,
  • separating structured disclosure (presentation, executives) from attention and questioning (Q&A, external participants).

Why it matters

Cyber risk is economically meaningful, but direct measurement is hard: incident databases are incomplete and reporting is uneven across jurisdictions and time. Earnings calls provide a scalable, timely signal of what firms and markets choose to discuss in a recurring, forward-looking setting.

Evidence in the underlying research shows the measure is:

  • validated via human auditing and LLM auditing,
  • linked to stock returns, profits, and options-implied risk,
  • able to predict reported cyberattacks,
  • informative about spillovers and firm-to-sector propagation.

What this captures (important): discussion-based exposure/attention to cyber issues.
What this does not capture: a direct count of incidents, breach probability, or a technical vulnerability score.

Common use cases:

  • early warning signals around regulation, major vulnerability cycles, or large-scale incidents,
  • benchmarking by sector/region and studying spillovers,
  • separating "voluntary disclosure" vs "analyst-driven attention" using Presentation/Q&A and Executive/External splits.

Explore the data

Curated chart

CyberRisk: Global (All sections, all speakers) over time

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Mean number of sentences per earnings call containing a query keyword. Smoothed with a 4-period moving average.

How to read this chart

This chart shows the mean number of sentences per earnings call that contain at least one cybersecurity keyword (247-term dictionary). Smoothed with a 4-period moving average. Restricted to US-based companies.

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Methodology and data

Methodology

Based on The Anatomy of Cyber Risk (Jamilov, Rey, Tahoun, December 2025).

  1. Cyber keyword dictionary (247 terms): constructed from institutional lexicons (FSB, NCSC, CISA) plus keyword discovery using word embeddings; de-duplicated and pruned.

  2. Sentence-level scoring: split transcript into sentences; mark a sentence cyber-related if it contains at least one keyword. The exposure score is the number of cyber-related sentences. Note that our data contains both the number of matched and total sentences.

  3. Decompositions: repeat the same scoring within Presentation vs Q&A and Executives vs External participants to separate disclosure vs attention channels.

Data & coverage

  • ~400k English-language earnings-call transcripts, ~14,00 firms, over 80 countries.
  • Sample in paper: 2003Q1–2025Q3 (we extend the series forward as new transcripts arrive).
  • Source: LSEG / StreetEvents.

References

Jamilov, R. & Rey, H & Tahoun, A., "The Anatomy of Cyber Risk," Working paper (R&R at Journal of Finance) (2025)

NL Analytics. (2026). The Global Corporate Cyber Risk Exposure Index [Data set]. NL Analytics. https://apps.nlanalytics.tech/curated-measures/cyber-risk/

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