Dr RisQuant™

Send us the portfolio. We return the analysis.

The quantitative arm of Phoenicia Consulting. Send us your deal or portfolio and we return the analysis — calibrated against real government and multilateral portfolios, documented so it survives a validator, and delivered as results you own.

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DFI Economic Capital — toy model

Adjust a single deal and watch the economic capital recompute live. Nothing is sent anywhere — the maths runs entirely on your device. The full assessment adds CreditRisk+, Monte Carlo, portfolio aggregation, and stress testing on your own book.

Single-deal economic capital

Basel IRB · preferred-creditor adjusted

Institution type

Country risk tier (OECD-style)

Exposure (EAD) $100m

Loss given default 45%

Tenor (years) 7y

Effective PD

—

after preferred-creditor adj.

Expected loss

—

PD × LGD × EAD

Economic capital

—

Capital saved

—

vs commercial treatment

Commercial treatment (PD × 1.00)—

Preferred-creditor treatment—

This is the differentiator. No commercial Basel engine recognises that MDBs and DFIs default less than commercial lenders to the same sovereign. The preferred-creditor adjustment is calibrated from IFC, EBRD, and ADB portfolio data. Figures are illustrative; the full assessment calibrates to your portfolio.

Assess this on my own book →

Carries your inputs above straight into the request — no retyping.

Assessment 01

DFI Economic Capital

The problem

Development finance institutions manage over $2 trillion in combined assets but rely on methodologies designed for commercial banks. Standard Basel IRB ignores preferred-creditor status, sovereign risk concentration, and concessional lending structures. No commercial software addresses this gap.

The solution

A three-engine economic capital framework calibrated for DFI portfolios:

Basel IRB engine — regulatory capital with asset-correlation and maturity adjustments.
CreditRisk+ engine — gamma-mixed Poisson loss distribution, analytically tractable.
Monte Carlo Gaussian copula — 10,000+ simulations, correlated defaults, full loss distribution.

Unique differentiator — preferred-creditor adjustment: institution-type PD multipliers (MDB 0.4×, bilateral 0.5×, ECA 0.6×, NDB 0.7×) calibrated from historical recovery data.

What you receive

Economic capital per exposure under all three engines, with the method comparison
Preferred-creditor-adjusted capital and the saving versus commercial treatment
Loss distribution with VaR and Expected Shortfall at 99% / 99.5% / 99.9%
Marginal EC contribution per deal — the basis for limit setting
Concentration analytics: HHI by country and sector, effective N, top-10
Stress results across baseline, adverse and severely adverse scenarios
Written report plus a methodology annex your validator can challenge
Results as Excel and CSV — the outputs are yours to keep and reuse

Delivery: 5 working days · enquire for pricing

Market-gap extensions

Recovery-rate modelling for DFI collateral (sovereign / partial credit guarantees, PRI)
Portfolio optimiser using marginal EC contributions for limit setting
Multi-currency aggregation with FX overlay
Blended-finance structuring: optimal public/private capital mix
OECD DAC reporting integration for ODA eligibility

Assessment 02

Climate Risk ICAAP

The problem

PRA SS5/25 requires regulated firms to complete an internal review and gap analysis by 3 June 2026 with a credible remediation plan. Most challenger banks lack internal capability to quantify transition and physical climate risk within ICAAP. The Big Four charge £150,000+ for this work.

The solution

NGFS scenario engine — four pathways (Net Zero 2050, Delayed Transition, Current Policies, NDCs).
Sector carbon-intensity model — 12 sectors, carbon-price-to-PD transmission.
Physical risk module — 12 UK regions; flood, heat, sea-level factors.
PRA SS5/25 gap analysis — 25 mapped requirements, automated RAG status, remediation roadmap.

What you receive

Baseline versus stressed ECL under all four NGFS pathways, loan by loan
Capital impact quantified for your ICAAP, with scenario comparison
Transition-risk hotspots by sector and physical-risk hotspots by UK region
PRA SS5/25 gap analysis: 25 requirements with RAG status and evidence gaps
Remediation roadmap — phased, with owners and target dates
Board-ready summary plus the methodology annex behind every number
Results as Excel and CSV — the outputs are yours to keep and reuse

Delivery: 5 working days · enquire for pricing

Market-gap extensions

TNFD nature-risk module (biodiversity, water stress, land use)
ILAAP climate liquidity stress (deposit outflow, funding cost)
Scope 3 financed-emissions calculator
Regulatory reporting automation (PRA climate returns, EBA Pillar 3 ESG)
Board training package with interactive scenario exploration

Assessment 03

Synthetic Data Service

The problem

Financial institutions cannot share portfolio data for validation, benchmarking, or regulatory exercises due to confidentiality. This bottlenecks model risk management — especially for smaller institutions lacking diverse internal datasets.

The solution

A dual-method platform grounded in peer-reviewed research published in Springer Computational Economics:

Gaussian copula generator — automatic marginal fitting via AIC, Cholesky correlation structure, inverse-CDF transform.
Block bootstrap generator — time-series-aware, preserves autocorrelation and tail dependence.
Validation suite — KS tests, correlation preservation (Frobenius), moment comparison, VaR/ES benchmarking.
Privacy guard — distance-to-closest-record, re-identification risk, k-anonymity.

What you receive

A synthetic dataset preserving your marginals, correlations and tail behaviour
Validation report: KS tests per variable, correlation preservation, moment comparison
VaR and Expected Shortfall benchmarked against the real data at 95% / 99% / 99.5%
Privacy certificate: distance-to-closest-record, re-identification risk, k-anonymity
Methodology annex grounded in peer-reviewed research — built for validator scrutiny
Data delivered as CSV — yours to share, publish or hand to a regulator

Delivery: 3 working days · enquire for pricing

Market-gap extensions

Conditional synthetic data (e.g. "this portfolio in a 2008-style crisis")
Multi-table relational synthetic data with referential integrity
Fairness-aware data for bias testing in credit scoring
Synthetic time series for IFRS 9 lifetime-PD backtesting
On-demand API generation for institutional clients

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