Executive Summary

This prototype is a scoring and flagging framework for institutional and geopolitical risk across ten Asian markets. It is designed for long-duration investors with exposure to infrastructure, credit, real estate, natural resources, and private equity.

The framework supports three decisions: initial market screening, trigger-based escalation for enhanced diligence, and portfolio-level scenario review. Country scores provide the baseline screen, while scenario overlays capture tail risks that standard indicators underweight.

China combines selective liberalization with tighter control in strategic sectors and high external strategic exposure. Vietnam remains investable but carries meaningful institutional and compliance risk; Indonesia’s main risk is resource nationalism; Taiwan scores strongly on domestic institutions but remains tail-sensitive because of cross-strait risk.

This framework is intended to support screening and escalation, not to replace deal-level diligence or produce definitive country rankings.

How This Framework Supports Investment Decisions

Layer 1: Screening

The composite risk score and tier assignment provide an initial screen for country-level exposure decisions.

Tier Score Range Screening Action
GREEN (LOW) 0–29 Standard diligence; no geopolitical escalation required
AMBER (MODERATE / MODERATE-HIGH) 30–64 Enhanced diligence required; geopolitical brief to investment committee before commitment
RED (HIGH) 65–100 Investment committee approval with dedicated geopolitical risk memo; structuring constraints apply

Layer 2: Diligence Escalation

Specific conditions trigger deeper legal, regulatory, compliance, sanctions, or reputational review beyond the standard scoring framework.

Escalation Trigger Review Required Typical Asset Classes Affected
Country on FATF grey/black list AML/CFT compliance review; counterparty screening Credit, Private Equity
Active sanctions regime affecting sector of investment Sanctions counsel opinion; OFAC/EU/UK screening All — especially Infrastructure, Natural Resources
Sovereign security review applies to transaction type Regulatory pathway assessment; timeline and approval uncertainty modelling Infrastructure, Real Estate, Natural Resources
Country scores ≥80 on External Strategic Exposure pillar Scenario stress test required (see Taiwan analysis); supply chain mapping All — portfolio-level cascade
Press freedom score in bottom decile (RSF) LP reputational screen; ESG reporting implications Private Equity, Real Estate

Layer 3: Portfolio Construction Implications

Geopolitical risk affects five dimensions of portfolio construction:

Decision Dimension How Geopolitical Risk Enters
Entry decision Tier assignment informs whether a market requires enhanced committee review for a given asset class
Structuring High-risk markets require enhanced contractual protections, arbitration clauses, minority JV structures
Sizing Country risk caps limit concentration; higher-risk markets receive smaller allocations
Required return Geopolitical risk premium added to hurdle rate; explicit in deal-level underwriting
Scenario stress testing Tail-risk scenarios (blockade, sanctions escalation, regime change) run at portfolio level

Data & Methodology

Data Sources

Data Source Provider Risk Pillar Coverage
CPI 2025 Transparency International Corruption 182 countries/territories
WGI Aggregate Percentile Ranks 2024 World Bank Governance Quality (RQ + RL) ~215 economies
WGI Aggregate Percentile Ranks 2024 World Bank Political Stability ~215 economies
ACLED 2024 Armed Conflict Location & Event Data Security Event-level, Asia-Pacific
FATF as of 2026-02-13 Financial Action Task Force Reputational Jurisdictional lists
RSF Press Freedom Index 2024 Reporters Without Borders Reputational 180 countries
Custom composite (see methodology) Multiple — see External Strategic Exposure External Strategic Exposure 10-country focus set

Methodological Notes

WGI usage: This framework uses official WGI aggregate percentile ranks as published by the World Bank, not raw underlying source data. The World Bank notes that cross-country and cross-year comparisons should account for margins of error; small score differences between similarly-ranked countries should not be over-interpreted. Tier assignments are the primary decision-relevant output.

Normalization scope: Pillar scores are normalized relative to this 10-country East and Southeast Asian peer group. Scores are peer-relative and not globally comparable absolute risk levels. Adding or removing countries will shift scores. Results are best interpreted as tier assignments.

Composite scores and scenario overlays: Composite scores capture institutional and operating risks that can be measured through standard indices. Scenario overlays address low-frequency, high-severity shocks — such as a Taiwan Strait blockade or major sanctions escalation — that standard indicators consistently underweight. Both layers are part of the framework: the composite provides the baseline screen, and scenarios cover tail risks.

Scoring Framework

Each country receives a composite risk score (0–100), where higher values indicate greater risk. Six pillars are normalized to a common 0–100 scale and aggregated using the weights below.

Pillar Source Weight Rationale
Corruption CPI 2025 (inverted) 20% Empirically associated with infrastructure cost overruns (Collier et al.); commonly weighted heavily in institutional risk frameworks
Governance Quality WGI RQ + RL 2024 (official aggregate percentile ranks, inverted) 20% Regulatory predictability critical for long-duration assets; captures rule of law and regulatory quality jointly
Political Stability WGI Political Stability & Absence of Violence 2024 (official aggregate percentile rank, inverted) 15% Political stability and absence of violence directly measure domestic disruption probability over infrastructure-relevant time horizons
Security ACLED 2024 (political violence only) 15% Physical asset protection; proximity to political violence events
Reputational RSF PFI 2024 (70%) + FATF 2026-02-13 (30%) 10% LP reputational screen; ESG compliance requirements
External Strategic Exposure Composite: sanctions, chokepoints, alliance entanglement, export controls, military escalation 20% Interstate conflict exposure, sanctions vulnerability, geoeconomic shock transmission — not captured by domestic institutional indicators

Trend Classification Rules

Trend arrows are assigned based on the rule set below. In this prototype, trends are assessed analytically by the author against these criteria; in production, they would be generated programmatically from rolling pillar updates.

Trend Symbol Rule
Worsening ▲ At least 2 of 6 pillars deteriorated beyond threshold over trailing 12 months
Stable → No material movement outside confidence band on any pillar
Improving ▼ At least 2 of 6 pillars improved materially over trailing 12 months

Thresholds: >5-point movement on the 0–100 pillar scale, or a discrete regime change (e.g., FATF list entry/exit, sanctions designation, negative list revision).

Composite Score Calculation

# ── STEP 1: Raw indicator data ───────────────────────────────────────────────
# In production: replace with read_csv() from actual downloaded datasets.
# CPI:   https://www.transparency.org/en/cpi
# WGI:   https://info.worldbank.org/governance/wgi/
# ACLED: https://acleddata.com/
# FATF:  https://www.fatf-gafi.org/en/countries.html

raw_data <- tibble(
  country      = c("China","Vietnam","Indonesia","Taiwan",
                   "India","Japan","South Korea","Thailand",
                   "Philippines","Singapore"),
  iso3         = c("CHN","VNM","IDN","TWN",
                   "IND","JPN","KOR","THA","PHL","SGP"),
  lat          = c(35.9, 14.1, -0.8,  23.7,
                   20.6, 36.2, 35.9,  15.9, 12.9,  1.4),
  lon          = c(104.2, 108.3, 113.9, 121.0,
                    78.9, 138.3, 127.8, 100.9, 121.8, 103.8),

  # ── Pillar 1: Corruption ───────────────────────────────────────────────────
  # CPI 2025 (Transparency International) — inverted: risk = 100 - CPI score
  # CPI2025_Results.xlsx:
  # CHN=43, VNM=41, IDN=34, TWN=68, IND=39, JPN=71, KOR=63, THA=33, PHL=32, SGP=84
  corruption_raw  = c(57, 59, 66, 32, 61, 29, 37, 67, 68, 16),

  # ── Pillar 2: Governance Quality ───────────────────────────────────────────
  # WGI Official Aggregate: Regulatory Quality + Rule of Law 2024
  # Average of RQ and RL percentile ranks, inverted (100 = highest risk)
  # Source: wgidataset.xlsx, official aggregate percentile ranks
  # NOTE: Uses official WGI aggregate scores, not raw underlying source data.
  # Small differences between similarly-ranked countries may fall within
  # WGI confidence intervals and should not be over-interpreted.
  governance_raw  = c(82.5, 52.0, 48.5, 15.2, 50.8, 12.5, 20.8, 51.2, 47.5, 2.5),

  # ── Pillar 3: Political Stability ──────────────────────────────────────────
  # WGI Official Aggregate: Political Stability & Absence of Violence/Terrorism
  # Percentile rank, inverted (100 = highest risk)
  # Source: wgidataset.xlsx, official aggregate percentile ranks
  # This pillar measures domestic disruption probability and policy continuity
  # risk — more directly relevant to infrastructure investment horizons than
  # Voice & Accountability, which measures democratic participation.
  stability_raw   = c(62.0, 48.5, 50.2, 18.3, 68.5, 8.2, 28.1, 55.8, 62.4, 5.0),

  # ── Pillar 4: Security ────────────────────────────────────────────────────
  # ACLED 2024 — Political violence only (excl. protests)
  # Events + fatalities per million pop, normalized 0–100
  # Source: Asia-Pacific_aggregated_data_up_to-2026-02-21.xlsx
  security_raw    = c(1.7, 0.2, 23.8, 0.0, 34.3, 0.0, 1.1, 22.7, 100.0, 0.0),

  # ── Pillar 5: Reputational ────────────────────────────────────────────────
  # 70% RSF Press Freedom Index 2024 (inverted) + 30% FATF grey/blacklist flag
  # FATF per 2026-02-13: VNM on grey list; all others not listed.
  # Source: RSF World Press Freedom Index 2024; FATF fatf-gafi.org/en/countries
  reputational_raw = c(67.9, 85.3, 32.2, 22.4, 44.8, 22.4, 25.2, 45.5, 32.9, 31.5),

  # ── Pillar 6: External Strategic Exposure ──────────────────────────────────
  # Custom composite: sanctions exposure, shipping chokepoint dependence,
  # alliance entanglement, export-control sensitivity, cross-border military
  # escalation probability. See External Strategic Exposure methodology section.
  # Scored 0–100.
  external_raw    = c(69, 24, 13, 78, 43, 48, 59, 11, 42, 31)
)

# ── STEP 2: Normalize each pillar 0–100 within peer group ────────────────────
normalize <- function(x) {
  rng <- max(x) - min(x)
  if (rng == 0) return(rep(50, length(x)))
  (x - min(x)) / rng * 100
}

scored <- raw_data %>%
  mutate(across(ends_with("_raw"), normalize, .names = "{.col}_norm")) %>%
  rename_with(~ str_replace(., "_raw_norm", "_norm"), ends_with("_raw_norm"))

# ── STEP 3: Weighted composite ───────────────────────────────────────────────
weights <- c(
  corruption_norm   = 0.20,
  governance_norm   = 0.20,
  stability_norm    = 0.15,
  security_norm     = 0.15,
  reputational_norm = 0.10,
  external_norm     = 0.20
)

scored <- scored %>%
  mutate(
    geo_risk_score = round(
      corruption_norm   * weights["corruption_norm"]   +
      governance_norm   * weights["governance_norm"]   +
      stability_norm    * weights["stability_norm"]    +
      security_norm     * weights["security_norm"]     +
      reputational_norm * weights["reputational_norm"] +
      external_norm     * weights["external_norm"],
      0  # integer — avoid false precision
    ),
    risk_tier = case_when(
      geo_risk_score >= 65 ~ "HIGH",
      geo_risk_score >= 45 ~ "MODERATE-HIGH",
      geo_risk_score >= 30 ~ "MODERATE",
      TRUE                 ~ "LOW"
    ),
    # Taiwan's composite is misleadingly moderate because strong domestic
    # institutions dilute extreme external strategic exposure. A display
    # tier flags this for summary-table readers.
    display_tier = case_when(
      iso3 == "TWN" ~ paste0(risk_tier, " (TAIL-SENSITIVE)"),
      TRUE          ~ risk_tier
    ),
    trend = case_when(
      country == "China"       ~ "Worsening ▲",
      country == "Vietnam"     ~ "Stable →",
      country == "Indonesia"   ~ "Worsening ▲",
      country == "Taiwan"      ~ "Stable →",
      country == "India"       ~ "Stable →",
      country == "Japan"       ~ "Stable →",
      country == "South Korea" ~ "Stable →",
      country == "Thailand"    ~ "Stable →",
      country == "Philippines" ~ "Stable →",
      country == "Singapore"   ~ "Stable →"
    )
  )

Risk Snapshot

Interactive Map

Country Scores

Cross-Asset Risk Matrix

The matrix below maps country-level risk drivers to specific asset classes. This is the primary output for investment teams evaluating exposure across infrastructure, real estate, natural resources, credit, and private equity.

Country / Risk Driver Infrastructure Real Estate Natural Resources Credit Private Equity Portfolio Response
China: regulatory tightening + external strategic exposure Licensing / JV constraints; national security review on data-linked and energy assets Land-use restrictions; data-center-linked assets subject to security review Strategic mineral review; SOE joint venture typically required Refinancing / covenant uncertainty; regulatory-driven credit events Exit risk (listing / data compliance); GP-LP alignment in JV structures Elevates committee review; generally disfavors direct control positions in strategic sectors; JV structuring with arbitration clauses
Vietnam: institutional risk (one-party, FATF grey list as of Feb 2026) Permitting delays; land title risk; brownfield preferred Title clarity concerns; local approval process opaque Concession enforcement uncertainty; energy transition assets more favorable Bank counterparty / AML perception risk; FATF-driven compliance cost Minority rights / governance protections; local partner dependence Enhanced AML/CFT diligence; FATF exit timeline as positive catalyst; brownfield entry preferred
Taiwan: external strategic exposure (cross-strait) Logistics disruption / port asset impairment under escalation scenarios Valuation shock under escalation; insurance market repricing Shipping / commodity routing disruption under blockade scenario Spread widening / liquidity freeze under escalation Portfolio company supply-chain shock; TSMC-dependent value chains Run cross-strait scenario stress test; cap Taiwan-dependent supply-chain concentration; review shipping-linked positions
Indonesia: resource nationalism Concession revision risk; domestic content requirements on capital equipment Less direct — urban commercial relatively insulated Royalty regime changes; export bans (nickel template extends to cobalt, bauxite) Sovereign-linked repricing; resource-sector credit correlation Local partner dependence; regulatory predictability in extractives Sovereign arbitration clauses (ICSID/UNCITRAL); model domestic content in project forecasts; resource-sector concentration limit
Philippines: security + political instability Physical security risk in conflict-affected areas; permitting bottlenecks Political instability affects commercial real estate demand Mining sector permitting; indigenous land rights disputes Sovereign credit trajectory uncertain; local bank quality variable Governance risk; exit pathway limited Physical security assessment required; enhanced counterparty screening; limited sizing
South Korea: North Korea escalation + export controls Limited direct risk; semiconductor fab supply-chain exposure Seoul metro resilient but peninsula risk premium latent Limited direct exposure Won-denominated credit resilient but sensitive to peninsula escalation Mature market but geopolitical overhang depresses multiples Monitor peninsula escalation indicators; semiconductor supply-chain mapping; standard diligence otherwise
Note:
Matrix maps country-level risk drivers to asset-class-specific investment implications. Intended as a screening tool — deal-level diligence remains required for all investments.

Risk Horizon Decomposition

Pension fund investment horizons (10–30+ years) require risk analysis at multiple time scales.

Country Horizon Risk Characterization
China
China 0–12 months Policy headline risk: negative list revisions, VIE guidance, security review decisions on pending transactions
China 1–3 years Tightening in strategic sectors (data, semiconductors, critical infrastructure); export-control reciprocity measures
China 3–10 years Structural narrowing of foreign operational space in strategic domains coexists with continued liberalization in manufacturing; state-capital coordination model consolidates
Taiwan
Taiwan 0–12 months PLA exercise cadence and signaling; AIS shipping anomaly monitoring
Taiwan 1–3 years Coercive military pressure normalization; semiconductor export-control escalation (BIS); insurance and shipping market repricing
Taiwan 3–10 years Low-probability, high-impact strategic rupture; TSMC capacity diversification timeline (Arizona, Kumamoto) partially reduces concentration but remains incomplete within this horizon
Vietnam
Vietnam 0–12 months FATF mutual evaluation progress; land law implementation decrees; FDI approval pipeline monitoring
Vietnam 1–3 years CPV leadership transition dynamics post-2026 congress; institutional reform trajectory
Vietnam 3–10 years Structural FDI beneficiary of supply-chain diversification; institutional quality convergence pace determines tier trajectory
Indonesia
Indonesia 0–12 months Prabowo first resource policy package; nickel template extension signals
Indonesia 1–3 years Downstream processing mandates expand across strategic minerals; subnational regulatory divergence persists
Indonesia 3–10 years Resource nationalism as durable structural feature; infrastructure build-out pace determines long-term investability

Risk Flagging Service: Monitoring Triggers

The trigger table below defines the between-cycle monitoring protocol. Triggers turn the scoring framework into an ongoing watchlist rather than a one-time assessment.

Trigger Threshold Frequency Action
FATF status change Grey/black list entry or exit Quarterly (FATF plenary cycle) Re-score Reputational pillar; notify Credit and PE teams
Negative list revision (China) Sector opened or closed to foreign investment On release (typically annual) Reassess entry mode and structuring for affected sectors
Security event spike Political violence events >2σ above trailing 12-month baseline (ACLED) Monthly (ACLED data refresh) Flag to Infrastructure and Real Estate teams; review physical security assumptions
Military exercise escalation 2+ consecutive high-intensity episodes or new geographic scope Event-driven Run Taiwan / regional scenario stress test; notify all asset class teams
Sanctions designation (new or expanded) Any SDN / entity list addition affecting investable sectors Event-driven (OFAC / EU / UK announcements) Immediate escalation to legal / compliance; review of new commitments pending assessment
Export-control expansion (BIS / EU) New technology category restricted or new country added Event-driven (BIS Federal Register notices) Re-score External Strategic Exposure pillar; assess portfolio company supply-chain exposure
Sovereign credit action Rating downgrade or outlook change by 2+ agencies Event-driven Review Credit portfolio concentration; reassess sovereign-linked positions
Leadership transition / constitutional change Unscheduled leadership change; constitutional amendment affecting property / contract rights Event-driven Re-score Political Stability pillar; comprehensive framework refresh
Implementation note:
Triggers are designed for quarterly framework updates supplemented by event-driven alerts. In production, triggers would feed into an automated watchlist dashboard with notification routing to relevant asset class teams.

Country Analyses

Country Profiles

Country Score Tier Trend Key Risk Driver
China 74 HIGH Worsening ▲ Selective liberalization alongside tightening in strategic domains; national security review expansion; high external strategic exposure (sanctions, export controls, SCS)
Vietnam 53 MODERATE-HIGH Stable → One-party institutional risk; FATF grey list (as of 13 Feb 2026); press freedom 174/180; moderate SCS exposure
Indonesia 47 MODERATE-HIGH Worsening ▲ Resource nationalism (nickel template); Prabowo statist orientation; subnational divergence
Taiwan 32 MODERATE (TAIL-SENSITIVE) Stable → Strong domestic institutions but extreme external strategic exposure: cross-strait military escalation, semiconductor chokepoint, alliance entanglement
Note:
Scores are peer-relative within the 10-country set. Small score differences between similarly-ranked countries may fall within WGI confidence intervals and should be interpreted as tier assignments rather than precise ordinal rankings.

Risk Radar Charts

China

Tier: HIGH | Trend: Worsening ▲

China’s risk profile is driven by regulatory and institutional risk on the domestic side and high external strategic exposure on the geopolitical side.

1. Regulatory Environment China combines selective liberalization with tighter state control in strategic, data-sensitive, and security-relevant sectors. The 2024 negative list eliminated all remaining manufacturing-sector restrictions for foreign investors, but the CSRC’s 2023 overseas listing rules introduced new ambiguity around Variable Interest Entity structures. Infrastructure-adjacent assets — logistics platforms, data centers, energy distribution — sit in grey zones subject to regulatory reinterpretation.

2. National Security Review Expansion The 2020 Measures for Security Review of Foreign Investment (effective January 2021) and the 2021 Data Security Law extended review triggers to a wider class of infrastructure assets, including those involving critical data and technology. Review outcomes are non-transparent and non-appealable, introducing material uncertainty into deal timelines.

3. Central-Provincial Enforcement Gap FDI regulatory data drawn from State Council documents (1950–2015, n ≈ 2,000) reveals a persistent structural gap between centrally-issued facilitation policies and sub-national implementation. Post-2012, this gap has narrowed through centralization — but in a direction that reduces rather than stabilizes foreign investor discretion.

4. External Strategic Exposure China is the primary target of US-led export controls (BIS Entity List expansion), escalating technology bifurcation (semiconductor equipment restrictions), and South China Sea territorial disputes. Secondary sanctions risk compounds direct exposure for portfolio companies with cross-border operations.

Vietnam

Tier: MODERATE-HIGH | Trend: Stable →

Structural FDI tailwinds from China+1 supply-chain reorganization are real, but institutional risk vectors keep Vietnam in MODERATE-HIGH territory.

WGI Political Stability data places Vietnam in the middle of the peer group, reflecting a one-party CPV system with constrained political competition and periodic anti-corruption campaigns that introduce leadership uncertainty. Vietnam remained on the FATF grey list as of 13 February 2026, signalling AML/CFT deficiencies that affect financial infrastructure and credit counterparty risk. RSF ranks Vietnam 174th of 180 on press freedom, creating LP reputational screening concerns.

External strategic exposure is moderate — South China Sea disputes are present but managed; no formal alliance entanglement triggers escalation dynamics.

Asset class note: Logistics and energy transition assets retain favorable risk-adjusted entry points. Monitor FATF exit timeline — removal would trigger meaningful tier improvement. Brownfield preferred over greenfield.

Indonesia

Tier: MODERATE-HIGH | Trend: Worsening ▲

Resource nationalism is the dominant risk vector. The Jokowi-era nickel export ban — which a WTO panel ruled inconsistent with GATT obligations in November 2022, though Indonesia’s appeal to the non-functional Appellate Body has left enforcement in limbo — has established a template that Prabowo’s administration is likely to extend to cobalt, bauxite, and copper.

Prabowo’s stated orientation toward domestic downstream processing suggests continued intervention in extractive value chains. Decentralization creates subnational regulatory divergence; local permitting is a persistent bottleneck. Presidential Regulation on Domestic Content Requirements affects imported capital equipment for infrastructure builds.

External strategic exposure is low — non-aligned posture, geographic buffer from core flashpoints, and limited export-control sensitivity provide insulation.

Asset class note: Natural resources and energy infrastructure require enhanced contractual protections and sovereign arbitration clauses (ICSID / UNCITRAL). Domestic content requirements should be modeled in project forecasts.

Taiwan

Tier: MODERATE (TAIL-SENSITIVE) | Trend: Stable →

Taiwan scores near the bottom of the peer group on domestic institutional risk but near the top on external strategic exposure — the widest gap between these two dimensions in the dataset.

Domestic indicators — rule of law, regulatory quality, corruption control — place Taiwan among the lowest-risk economies in the peer group. These scores are correct for what they measure.

The risk is external and geostrategic:

  • Cross-strait military pressure: PLA exercise frequency and scope have increased since 2022. The August 2022 exercises represented a qualitative escalation in simulated blockade operations. The May 2024 exercises extended and normalized these coercive patterns, though their overall scale was smaller than the 2022 precedent.
  • Semiconductor chokepoint: TSMC’s Taiwan-based capacity dominates global advanced-node foundry production; a disruption would ripple through global technology supply chains.
  • Alliance entanglement: US arms sales timelines, Taiwan Relations Act commitments, and regional alliance structures create escalation pathways exogenous to Taiwan’s own institutional decisions.

Taiwan Scenario Analysis

The composite score captures Taiwan’s external strategic exposure through the sixth pillar. The scenario framework below breaks this down further for portfolio-level contingency planning.

Scenario Probability Trigger Indicators Infrastructure Impact Portfolio Action
  1. Status quo / managed tension
Base case (~60%) PLA exercise frequency stable; diplomatic channels open Minimal — monitor only No action required
  1. Escalated military pressure (extended exercises)
Elevated (~25%) Large-scale PLA exercises encircling Taiwan; AIS shipping anomalies Shipping lane disruption; logistics asset repricing Review cross-strait logistics exposure; stress test shipping-linked assets
  1. Partial economic coercion (sanctions / trade restrictions)
Low-moderate (~12%) Chip export controls escalate; cross-strait financial flows restricted Supply chain reconfiguration cost; semiconductor-linked asset drawdown Accelerate diversification away from Taiwan-dependent supply chains
  1. Full blockade / kinetic conflict
Low (<3%) PLA amphibious deployment signals; insurance market seizure Catastrophic — port/logistics NAV impairment; global supply chain freeze Activate tail-risk hedges; liquidity review for illiquid infrastructure positions
Note:
Probability estimates are qualitative assessments based on PLA exercise cadence, US-Taiwan Relations Act commitments, and cross-strait economic interdependence as of Q1 2026. Not a quantitative forecast.

External Strategic Exposure: Methodology

Components

Sub-dimension Weight Operationalization
Sanctions exposure 25% Current sanctions regime + secondary sanctions vulnerability + trajectory
Shipping chokepoint dependence 20% Trade volume through contested / vulnerable maritime corridors (Malacca, Taiwan Strait, SCS)
Alliance entanglement 20% Bilateral defense commitments creating escalation pathways exogenous to country decisions
Export-control sensitivity 20% Exposure to US/EU technology export restrictions; dependence on controlled inputs
Cross-border military escalation 15% Proximity to active military flashpoints; frequency of interstate military incidents

Scoring Decomposition

The table below shows the sub-dimension scores underlying the External Strategic Exposure pillar. This provides transparency on the composition of the aggregate score and allows reviewers to challenge or adjust individual assessments.

Country Sanctions Chokepoints Alliance Export Controls Military Escalation Composite (weighted)
Taiwan 30 90 95 90 100 78
China 85 55 40 95 65 69
South Korea 25 50 80 75 80 59
Japan 15 55 75 55 45 48
India 40 30 35 50 65 43
Philippines 10 70 65 15 60 42
Singapore 15 80 20 30 5 31
Vietnam 15 40 15 20 35 24
Indonesia 10 25 10 10 10 13
Thailand 10 20 10 10 5 11
Note:
Sub-dimension scores are analyst assessments (0–100) as of Q1 2026. Composite is the weighted sum per methodology above. Scores are intended to be challenged and refined through team review and updated as conditions evolve.

Limitations

This pillar involves more qualitative judgment than the other five:

  • Scoring reflects analyst assessment as of Q1 2026 and should be updated as conditions evolve
  • Sub-dimension weights reflect infrastructure-investment-relevance rather than geopolitical salience per se
  • The pillar captures structural exposure, not the probability of specific conflict scenarios

Sensitivity Analysis

Weight robustness check: each pillar weight is perturbed ±5 percentage points while holding others proportionally constant. The analysis covers all 10 countries using the same normalized pillar data as the main composite.

set.seed(42)
n_sim <- 500

# Extract normalized pillar matrix for all 10 countries
pillar_cols <- c("corruption_norm","governance_norm","stability_norm",
                 "security_norm","reputational_norm","external_norm")

pillar_matrix <- scored %>%
  select(country, all_of(pillar_cols)) %>%
  column_to_rownames("country") %>%
  as.matrix()

base_weights <- c(0.20, 0.20, 0.15, 0.15, 0.10, 0.20)

# Simulate weight perturbations
sim_results <- map_dfr(seq_len(n_sim), function(i) {
  noise       <- runif(6, -0.05, 0.05)
  w_perturbed <- base_weights + noise
  w_perturbed <- abs(w_perturbed) / sum(abs(w_perturbed))

  sim_scores <- as.numeric(pillar_matrix %*% w_perturbed)

  tibble(
    sim     = i,
    country = rownames(pillar_matrix),
    score   = sim_scores
  )
})

# Rank stability summary
rank_stability <- sim_results %>%
  group_by(sim) %>%
  mutate(rank = rank(-score)) %>%
  ungroup() %>%
  group_by(country) %>%
  summarise(
    median_score = round(median(score), 0),
    iqr_score    = paste0("[", round(quantile(score, 0.25), 0), "–",
                          round(quantile(score, 0.75), 0), "]"),
    median_rank  = round(median(rank), 1),
    rank_range   = paste0(min(rank), "–", max(rank)),
    .groups = "drop"
  ) %>%
  arrange(desc(median_score))

# Plot
country_order <- rank_stability$country
sim_results <- sim_results %>%
  mutate(country = factor(country, levels = country_order))

ggplot(sim_results, aes(x = country, y = score, fill = country)) +
  geom_boxplot(alpha = 0.7, outlier.size = 0.5, show.legend = FALSE) +
  scale_fill_manual(values = c(
    China = "#ef4444", Vietnam = "#f97316", India = "#f97316",
    Indonesia = "#f97316", Philippines = "#eab308", Thailand = "#eab308",
    Taiwan = "#3b82f6", `South Korea` = "#eab308", Japan = "#94a3b8",
    Singapore = "#22c55e"
  )) +
  labs(
    title    = "Sensitivity Analysis — 500 Weight Perturbation Simulations (All 10 Countries)",
    subtitle = "Tier assignments stable across ±5pp weight perturbations",
    x        = NULL,
    y        = "Simulated Risk Score (peer-relative)",
    caption  = "Dirichlet-like perturbation around base weights; n = 500; all 6 pillars perturbed simultaneously"
  ) +
  theme_minimal(base_size = 11) +
  theme(
    plot.title    = element_text(face = "bold", size = 12),
    plot.subtitle = element_text(color = "grey50"),
    axis.text.x   = element_text(angle = 35, hjust = 1, face = "bold")
  )

Rank Stability

Country Median Score IQR Median Rank Rank Range
China 74 [72–76] 1 1–2
Philippines 71 [69–72] 2 1–2
India 63 [61–64] 3 3–3
Vietnam 53 [51–55] 4 4–5
Thailand 51 [49–52] 5 4–5
Indonesia 47 [46–49] 6 6–6
South Korea 33 [32–34] 7 7–8
Taiwan 32 [31–34] 8 7–8
Japan 19 [18–20] 9 9–9
Singapore 7 [7–8] 10 10–10
Interpretation:
Narrow rank ranges indicate robust placement. Pairwise reversals between adjacent countries are expected; tier-level reversals (e.g., HIGH ↔︎ MODERATE) are the relevant stability criterion.

Forward Indicators

Country Indicator Priority Watch Date
China CSRC VIE structure guidance (Q2 2026) HIGH Q2 2026
China State Council negative list revisions — sector-level evolution HIGH Q3 2026
China Foreign Investment Security Review trigger expansion HIGH Ongoing
China BIS Entity List / export-control escalation (External Strategic pillar) HIGH Ongoing
Vietnam FATF mutual evaluation and grey list exit timeline HIGH Q3 2026
Vietnam Land Law implementation decree progress MEDIUM Q2 2026
Vietnam CPV leadership transition dynamics post-2026 congress HIGH Q4 2026
Indonesia Prabowo first resource policy package (nickel template extension) HIGH Q2 2026
Indonesia ASEAN critical minerals framework ratification MEDIUM Q3 2026
Indonesia Subnational permitting reform progress LOW Ongoing
Taiwan PLA exercise frequency, geographic scope, force composition HIGH Monthly
Taiwan US arms sales timeline and technology category HIGH Q2 2026
Taiwan Semiconductor export-control escalation (BIS) HIGH Ongoing
Taiwan Cross-strait shipping lane indicators (AIS anomalies) MEDIUM Ongoing

Limitations and Appropriate Use

Three boundaries matter for anyone using this framework:

1. Peer-relative, not absolute. Scores are normalized within this 10-country peer group. They are not globally comparable. Adding or removing countries will shift all scores. The output is peer comparison and tier assignment, not cross-regional benchmarking.

2. Not a substitute for deal-level diligence. Country-level risk scoring does not replace project-specific legal, contractual, regulatory, and operational due diligence. A MODERATE-HIGH country may contain individual assets with favorable risk profiles, and vice versa.

3. Scenario overlays required for strategic shocks. The External Strategic Exposure pillar captures structural geostrategic risk, but low-frequency, high-severity events (blockade, major sanctions escalation, chokepoint closure) need dedicated scenario analysis beyond what any composite index can cover.

Next Steps: If Developed Within an Investment Team

If this prototype were embedded within an institutional geopolitics team, next steps would include:

  1. Integrate private sources and internal deal observations. Add S&P, Fitch, and Bloomberg political risk feeds alongside deal-level intelligence from investment teams.

  2. Build an automated monthly watchlist. Turn the flagging trigger table into a dashboard with automated data ingestion (ACLED, FATF, BIS Federal Register) and notification routing to relevant asset class teams.

  3. Develop asset-class-specific scenario templates. Extend the Taiwan scenario approach to other tail-risk vectors (South China Sea shipping disruption, sanctions escalation, ASEAN political transitions) with impact quantification by asset class.

  4. Calibrate weights against historical outcomes. Back-test pillar weights against past deal outcomes and write-downs to validate or refine the weighting scheme.

  5. Create investment committee outputs. Format outputs as standardized briefing notes, PowerPoint decks, and dashboard views for investment committee use.

Conclusion

The peer group separates into three tiers for pension fund allocation across infrastructure, real estate, natural resources, credit, and private equity.

  1. China requires structural risk discounting for direct ownership in strategic sectors. The regulatory environment has liberalized in manufacturing while tightening in data-sensitive and security-relevant domains — a durable shift, not a cyclical one. Export controls, sanctions trajectory, and South China Sea tensions add a separate layer of external risk.

  2. Vietnam scores MODERATE-HIGH on institutional risk but remains the primary structural FDI beneficiary of supply-chain de-risking. Risk-adjusted entry is viable in logistics and energy transition assets with enhanced diligence. FATF grey list exit is the single most important positive catalyst.

  3. Indonesia presents manageable but rising risk concentrated in resource nationalism. Low external strategic exposure is a differentiating advantage. Contractual structuring can substantially mitigate exposure.

  4. Taiwan scores well on domestic institutions but carries the highest external strategic exposure in the peer group. Portfolio-level scenario planning for cross-strait disruption is required.

Scoring is designed for quarterly updates, supplemented by event-driven flags. The cross-asset matrix, risk horizon decomposition, and monitoring triggers turn country-level scores into outputs usable by asset class teams.

Prepared as an independent sample work product demonstrating institutional and geopolitical risk analysis methodology, quantitative scoring, cross-asset translation, and R-based visualization.

Data snapshot: CPI 2025 (Transparency International, 182 countries/territories); WGI 2024 (World Bank, official aggregate percentile ranks); ACLED Asia-Pacific as of 2026-02-21; RSF Press Freedom Index 2024; FATF grey/blacklist as of 13 February 2026; External Strategic Exposure (analyst assessment, Q1 2026).

Scores are peer-relative within the 10-country East and Southeast Asia focus set and are not globally comparable absolute risk levels.