Draft:Relational Risk
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Relational Risk is a risk assessment methodology that analyzes a company's executive networks, funding structures, and governance changes as leading indicators to detect investment risks before they manifest in financial statements.[1]
| Submission declined on 7 March 2026 by ChrysGalley (talk). This draft reads like an advertisement. Wikipedia is an encyclopedia, not a platform for promotion or marketing. Drafts that are exclusively promotional may be deleted without notice.
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Comment: And it seems to be AI assisted too. This does not meet notability via sourcing. ChrysGalley (talk) 21:34, 7 March 2026 (UTC)
- Comment: This topic describes a specific risk assessment methodology that appears to originate from a single company or research effort, with limited independent verification from reliable, third-party sources. It does not yet have sufficient established recognition or corroboration to qualify as a verifiable encyclopedia entry. References published in well-regarded academic journals would be helpful. Mirtip (talk) 05:48, 6 March 2026 (UTC)
Unlike traditional financial analysis, which focuses on lagging indicators such as financial statements, Relational Risk captures early warning signals from human networks and capital flows that typically precede corporate distress by several months.[2]
Background
Traditional corporate risk assessment relies primarily on financial statement analysis, examining metrics such as debt-to-equity ratios, earnings quality, and cash flow patterns. However, financial statements are backward-looking documents that record events after they occur. Corporate crises typically begin in human networks and capital flows months before they appear in accounting figures.
Relational Risk was developed as part of the RaymondsRisk platform by KonnectAI to address this gap by focusing on network-based leading indicators.
Three Core Components
Human Risk
Human Risk analyzes changes in a company's executive network, including:
- Frequency and patterns of executive turnover
- Influx of executives with prior involvement in delisted companies
- Interlocking directorate structures, where specific individuals simultaneously control boards of multiple companies
Funding Risk
Funding Risk examines corporate financing patterns, particularly:
- Private placement convertible bond (CB) issuance patterns
- Refixing clauses that automatically lower conversion prices when stock prices decline, diluting existing shareholders
- Circular investment structures (A→B→C→A) that may indicate coordinated market manipulation
A typical risk pattern involves: CB issuance → executive replacement → stock price manipulation → conversion and sale → stock price collapse.
Governance Risk
Governance Risk evaluates corporate governance integrity, including:
- Rapid dilution of major shareholder stakes
- Frequent extraordinary general meetings
- Compromise of outside director independence
Scoring System
The Relational Risk scoring system, designed by Jaejoon Park, combines the Worsening Probability (WP) score—a measure of financial deterioration risk derived from machine learning—with the Relational Risk Score (RRS):
- Combined Risk = WP (40%) × RRS (60%)
Companies are classified into four investment grades:
- LOW: Monitor and maintain
- MEDIUM: Caution advised
- HIGH: Elevated alert
- CRITICAL: Investment avoidance recommended
The system is built on Neo4j graph database and PostgreSQL, utilizing DART API data, with a model trained on 75,059 executive position records.
Empirical Evidence
A study examining 2,793 KOSPI and KOSDAQ-listed companies found the following results:[2]
- 5-fold cross-validation AUC: 0.8830 (95% CI [0.8674, 0.8986])
- 56.17% of CRITICAL-rated companies experienced TYPE_A trading suspensions
- Odds Ratio of CRITICAL vs. LOW group: 113.72
- Kolmogorov–Smirnov statistic D: 0.9065
- Common Language Effect Size (CLES): 99.1%
- Recall at WP ≥ 0.50: 82.6%; Negative Predictive Value: 97.9%
- Out-of-Time validation AUC: 0.8280 (24-month), 0.9291 (12-month)
These results, based on six in-time and nine out-of-time statistical tests, confirm Worsening Probability as a statistically significant predictor of TYPE_A trading suspensions.
Relationship to Corporate Financial Distress Research
Relational Risk contributes to the broader field of corporate financial distress prediction, which includes models such as Altman's Z-score and Ohlson's O-score. While traditional models rely on accounting variables, Relational Risk introduces a novel feature domain based on network relationships and governance patterns.
Academic research in related areas includes studies on:
- Reliable sources include: reputable newspapers, magazines, academic journals, and books from respected publishers.
- Unacceptable sources include: personal blogs, social media, predatory publishers, most tabloids, and websites where anyone can contribute.
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