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For the Yield Architect

AI for Private Credit

Resiliq gives private credit teams a connected workspace for borrower research, underwriting, covenant analysis, stress testing, and portfolio risk decisions. Bring financial and market context together so the credit rationale, downside cases, and monitoring questions are easier to review.

Where work slows down

Challenges We Address

Borrower data is fragmented across financial statements, market databases, and industry reports. Manual underwriting and reactive monitoring leave portfolios exposed. See how Resiliq connects the data and spots risks first.

01

Credit Diligence at Scale

Analyzing borrower financials, covenants, and market context takes weeks per deal. As volumes grow, manual diligence becomes a structural bottleneck.

02

Late Covenant Alerts

Tracking covenants, compliance triggers, and reporting obligations across a growing portfolio in spreadsheets means breaches surface too late to act.

03

Hidden Portfolio Risk

Concentration, sector correlation, and liquidity exposure are hard to model across private credit portfolios. Stress scenarios arrive before spreadsheets catch up.

The operating flow

Structure the Credit Decision

Connect origination research, borrower diligence, underwriting assumptions, covenant questions, and stress scenarios in a repeatable workflow across the credit lifecycle.

Private credit underwriting workspace

Connect borrower evidence to downside risk

Illustrative direct-lending review using sample terms

Build the underwriting view

Bring borrower financials, market context, and open diligence questions into one credit record.

Revenue quality
ReviewNormalisation open
Leverage
5.2xSample entry case
Cash conversion
StableSample history

EBITDA adjustments

3 items

Add-backs remain visible for credit committee review.

Borrower, leverage, and credit terms are illustrative.

What changes for the team

1

Screen & Originate at Scale

Research borrowers, sectors, financial context, and competitive positioning to create a structured initial credit view and prioritise the questions that need underwriting work.

2

Run Parallel Credit Diligence

Coordinate financial, commercial, legal, and market diligence around the borrower so risks, evidence, and open questions are available to the credit committee.

3

Monitor Covenants & Compliance

Use covenant and portfolio context to organise test-date, compliance, and downside questions for proactive credit review and risk discussion.

4

Stress-Test Portfolio Risk

Run credit stress, recovery, and rate-scenario analysis to test borrower and portfolio assumptions before capital is committed or risk is escalated.

Purpose-built capabilities

The work, connected.

Research, diligence, modelling, and decision support stay connected so the team can move from a question to a documented point of view without rebuilding context at every handoff.

01

Coordinated AI Diligence

Coordinate financial, commercial, technology, legal, and risk review through structured workstreams, source context, and a reviewable record of findings.

In the workflow
02

Automated Covenant Tracking & Credit Monitoring

Automate loan covenant compliance tracking, test-date monitoring, and credit health diagnostics for direct lending portfolios.

In the workflow
03

Credit Stress Testing & Scenario Modeling

Run Vasicek and Merton credit risk models, interest rate shock tests, and downside recovery analysis across private credit loan books.

In the workflow
04

Cross-Asset Risk Engine

Use portfolio, factor, scenario, and sensitivity analysis to examine risk exposures across private-market investment questions.

In the workflow

Your questions, answered

Answers to the most frequently asked questions.

How does Resiliq automate loan covenant tracking and compliance monitoring?

Resiliq continuously extracts covenant definitions, testing thresholds, and compliance schedules from credit agreements. The platform monitors incoming borrower financial statements against leverage ratios, debt service coverage ratios (DSCR), and fixed charge coverage tests, automatically flagging covenant drift or breaches before test dates.

Which quantitative models are used for credit portfolio stress testing and downside scenario planning?

Resiliq Quant Lab incorporates deterministic credit risk models including structural default frameworks (Merton and Vasicek models), interest rate shock testing (+100 to +300 bps), amortising cash flow debt service projections, and recovery waterfall modeling. All simulations output audit-ready sensitivity grids for Credit Committee review.

How does the platform assist direct lenders with credit memo preparation and quarterly reviews?

Resiliq synthesises borrower filings, covenant compliance records, and downside stress results into structured quarterly credit review packs and initial credit approval memos, tying every risk metric to verified loan documentation.

How Secure is Resiliq?

Resiliq is designed for defense-grade security and data sovereignty. Engineered by team with deep security background from banking and financial services, the platform implements zero-trust architecture and strict boundaries at tenant, team, deal, and individual artifact levels.

Data is protected end-to-end with forward secrecy and AES-256-GCM encryption. For organizations with long-horizon compliance and secrecy requirements, we support multi-tier, multi-domain post-quantum cryptography (FIPS 203 / ML-KEM) and deployment models that give your firm absolute control over keys, infrastructure, and model lineage.

Your workflow, in context

See Resiliq in your Private Credit workflow.

Book a focused walkthrough of the research, analysis, and agent experiences most relevant to your underwriting and portfolio process.

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AI for Private Credit: Underwriting & Covenants | Resiliq