Numra

What Is Numra?

Defining the Concept

Numra refers to an AI-powered financial data extraction and enrichment platform that automates the collection, normalization, and analysis of company financials, ownership structures, and risk indicators from global regulatory filings, news, and proprietary datasets. Unlike manual research or generic web scrapers, Numra uses natural language processing and knowledge graph technology to read complex documents like SEC 10-Ks, EDGAR filings, UK Companies House accounts, and EU transparency reports extracting structured data (e.g., revenue, EBITDA, subsidiaries, directors) with audit-grade accuracy. Built for investors, lenders, corporate development teams, and compliance officers, Numra turns weeks of manual due diligence into minutes of automated insight enabling faster, deeper, and more confident financial decisions.

Core Technological Differentiation

Financial Document Intelligence Engine

Numra’s models are trained exclusively on financial and legal texts not general web data ensuring domain precision:

• Structure-Aware Parsing: Understands hierarchical report layouts (e.g., “Item 7: Management’s Discussion” in 10-Ks)
• Cross-Reference Resolution: Links entities across sections (e.g., connects “Subsidiary X” in Notes to “Entity Y” in Org Chart)
• Temporal Reasoning: Tracks multi-year trends (e.g., “Revenue 2023: $12.4M; 2022: $10.1M → +22.8 percent”)
• Uncertainty Scoring: Flags low-confidence extractions (e.g., “EBITDA estimated footnote references non-GAAP measure”)

All outputs include source citations (page, paragraph, filing URL) for auditability.

Knowledge Graph of Global Entities

Numra builds a dynamic graph linking:

• Companies: Legal names, aliases, tickers, LEIs, jurisdictions
• People: Directors, officers, beneficial owners—with PEP/sanctions screening
• Relationships: Ownership (%), control (voting rights), management roles
• Financials: Standardized metrics (revenue, net income, debt) across GAAP, IFRS, local standards

The graph reconciles entities across languages and registries (e.g., “Siemens AG” = “SIEMENS AKTIENGESELLSCHAFT” = LEI 549300VZQK4CKF2T8K85).

Workflow-Embedded Analytics

Numra doesn’t just extract—it analyzes:

• Risk Scoring: Aggregates financial health, litigation, sanctions, and ESG flags into composite scores
• Peer Benchmarking: Compares target vs. sector peers on 50+ metrics (e.g., “Debt/EBITDA: Target 4.2x vs. Median 2.8x”)
• Change Detection: Alerts on material shifts (e.g., “Director resignation + 15 percent revenue drop in 6 months”)
• Scenario Modeling: “What if revenue declines 10 percent? Recalculate coverage ratios”

Outputs integrate directly into deal memos, credit apps, and CRM systems.

Target Market and Positioning

Primary Customer Profile

Numra serves finance and risk professionals who need fast, accurate company intelligence:

• Private Equity and VC: Due diligence on targets and portfolio companies
• Commercial Banks and Lenders: Credit risk assessment and portfolio monitoring
• Corporate Development: M&A screening and integration planning
• Compliance and KYC Teams: Ongoing customer due diligence (CDD) and adverse media screening

All face pressure to reduce research time while increasing coverage and defensibility.

Competitive Differentiation

Unlike Bloomberg (expensive, surface-level), manual analysts (slow, inconsistent), or generic AI tools (no financial grounding), Numra is:

• Finance-First: Models trained on 10M+ financial filings across 150 countries
• Source-Transparent: Every data point traces to original document
• Workflow-Native: Outputs ready for PitchBook, DealCloud, Moody’s, or internal templates
• Cost-Effective: $15K/year vs. $250K+ for full-time analyst team

It is the only platform that delivers institutional-grade financial intelligence without institutional overhead.

What Information Is Included?

Data Scope and Coverage

Document Sources

Numra processes:

• Regulatory Filings: SEC (10-K, 10-Q, DEF 14A), EDGAR, UK Companies House, EU Transparency Register, SEDAR (Canada), ASIC (Australia)
• News and Press: Reuters, Bloomberg, PR Newswire, local business journals (for M&A, leadership changes)
• Sanctions and PEP Lists: OFAC, UN, EU, World Bank debarment lists
• Private Company Data: Orbis, Bureau van Dijk, and proprietary network-sourced disclosures

Coverage spans 200+ million entities in 200+ jurisdictions—with daily updates.

Extracted Financial and Risk Metrics

• Income Statement: Revenue, gross profit, EBITDA, net income (normalized across standards)
• Balance Sheet: Total assets, debt, equity, cash
• Cash Flow: Operating, investing, financing activities
• Ownership: Direct/indirect stakes, UBO identification, control chains
• Risk Flags: Litigation mentions, regulatory actions, sanctions matches, ESG controversies

All metrics are time-stamped, sourced, and versioned.

Data Security and Compliance Framework

Encryption and Governance

• In transit: TLS 1.3 for all data movement
• At rest: AES-256 for documents, graphs, and user data
• Authentication: SSO (SAML/OIDC), MFA, IP allowlisting
• Access Control: RBAC with role-based data visibility (e.g., “Analyst: view Tier 2 data; VP: Tier 1 only”)

Regulatory Compliance

• SOC 2 Type II: Annual third-party audit
• GDPR/CCPA: Right-to-erasure; data minimization by design
• FINRA/SEC: Audit trails for all data access and modifications
• ISO 27001: Certified information security management

Numra is approved for use by top-tier investment banks and asset managers.

Where Is Numra Used?

Financial Workflow Applications

Investment Due Diligence

• Target Screening: Scan 500 potential targets in sector; filter by revenue growth >15 percent, debt/EBITDA <3x
• Deep Dive: Auto-extract 3-year financials, cap table, top customers from 10-Ks populate CIM
• Portfolio Monitoring: Alert on covenant breaches (e.g., “Leverage ratio exceeded 5.0x in Q1 filing”)

Credit Risk Assessment

• Application Processing: Ingest borrower’s latest accounts; auto-validate against industry benchmarks
• Ongoing Surveillance: Monitor news and filings for material changes (e.g., “CEO departure + rating downgrade”)
• Stress Testing: Model impact of macro shocks (e.g., “+200 bps rates → DSCR falls to 0.9x”)

M&A and Corporate Strategy

• Competitor Intelligence: Track peer capex, R&D spend, margin trends quarterly
• Integration Planning: Map target subsidiaries, contracts, and key personnel pre-close
• Synergy Modeling: Identify overlap in customers, vendors, facilities via entity graph

Compliance and KYC

• Onboarding: Auto-generate CDD reports with UBO trees, PEP checks, adverse media
• Periodic Review: Flag changes in ownership, sanctions status, or litigation quarterly
• Audit Support: Export full trail of data sources and extraction logic for regulators

Operational Workflow Example

End-to-End LBO Target Analysis

1. Search: “Healthtech companies in EU, revenue 50M–200M euros, EBITDA margin >20 percent”
2. Shortlist: 12 matches; Numra ranks by growth, leverage, and governance risk
3. Deep Dive: For top candidate, extracts 3-year P&L, balance sheet, cap table, top 5 customers
4. Benchmark: Compares metrics to MedTech peers; flags “Customer concentration: 62 percent from Top 1”
5. Report: Generates Word/PDF memo with charts, source links, and risk summary

Result: First-pass analysis in 45 minutes vs. 3–5 days manually.

When Did Numra Emerge?

Founding and Technical Genesis

Origins in Private Equity Pain Points (2021–2023)

Numra was founded in 2021 by Dr. Lena Cho (ex-Blackstone Data Science) and Raj Mehta (ex-Goldman Sachs IB), who observed that 70 percent of deal delays stemmed from slow, inconsistent financial research. Early R&D focused on:

• Fine-tuning transformer models on SEC filings and annual reports
• Building cross-jurisdiction entity resolution (e.g., UK Ltd vs. DE GmbH)
• Validating outputs against auditor-reviewed datasets

Piloted in 2022 with three PE firms; processed 50,000+ filings in beta.

Commercial Launch and Growth (2023–2025)

• Q1 2023: Launched v1 with SEC/UK coverage
• Q4 2023: Added EU, Canada, Australia; integrated with DealCloud
• Q2 2024: Achieved SOC 2 compliance; onboarded 15 asset managers
• Q1 2025: Processes 2M+ documents/month; used by 8 of top 20 PE firms

Key Milestones

• 2022: $12M Series A led by Ribbit Capital
• 2023: First AI tool cited in SEC comment letter (with attorney attestation)
• 2024: 98 percent accuracy on EBITDA extraction (vs. 82 percent manual)
• 2025: Named “Leader” in Gartner Market Guide for AI in Financial Research

Why Does Numra Exist?

Solving the Financial Research Bottleneck

Numra exists because financial analysis remains stubbornly manual and inconsistent. Analysts spend 60–80 percent of time gathering and cleaning data not analyzing it. Errors creep in from misread footnotes, missed amendments, or outdated sources. Firms rely on expensive third-party data or overworked juniors slowing deals and increasing risk. Numra answers a critical need: How can finance teams get institutional-grade intelligence fast, accurate, and audit-ready without armies of analysts? Its purpose is to make deep financial insight scalable, defensible, and democratic.

Strategic Business Imperatives

Speed and Deal Velocity

• PE firms lose 30 percent of targets due to slow diligence (Preqin)
• Banks miss loan opportunities during rate windows
• Corporates delay M&A while waiting for research

Risk and Compliance Pressure

• Regulators fine firms for inadequate KYC (e.g., $150M UBS penalty, 2024)
• Portfolio companies default due to undetected covenant breaches
• ESG controversies emerge from unmonitored subsidiaries

Talent and Cost Constraints

• Junior analyst turnover exceeds 25 percent in IB/PE
• Data subscriptions cost $50K–$500K/year per firm
• Small funds can’t afford Bloomberg or CapIQ

How Is Numra Built?

Core Technical Architecture

AI and Knowledge Layer

• Document Model: Fine-tuned Llama-3-70B on 10M+ financial filings
• Graph Engine: Neo4j-backed entity resolver with 200M+ nodes
• Validation Pipeline: Rules-based checks (e.g., “Assets = Liabilities + Equity”) plus human-in-the-loop review
• Update Scheduler: Daily crawls of 150+ regulatory sites; real-time news alerts

Integration Framework

• APIs: REST endpoints for search, extract, monitor
• Native Plugins: DealCloud, Salesforce, Microsoft Word, Excel
• Export Formats: PDF, Excel, JSON, PitchBook template

Deployment Model

• Cloud (SaaS): AWS GovCloud (U.S.), Frankfurt (EU); 99.95 percent SLA
• Private Cloud: For air-gapped institutions (e.g., central banks)
• Hybrid: Sensitive data on-prem; analytics in cloud

Implementation takes 1–2 weeks including custom workflow mapping.

Why Is Numra Necessary?

Quantifiable Financial Impact

Productivity Gains

• Due diligence time: 5 days → 2 hours per target
• Credit app processing: 3 days → 4 hours
• KYC refresh: Quarterly → continuous

Accuracy and Risk Reduction

• Data errors: 12 percent (manual) → 1.8 percent (Numra)
• Missed risks: 22 percent reduction in portfolio defaults
• Audit findings: Zero in client deployments (2023–2025)

Cost Efficiency

• Research costs: $180K/year (2 analysts) → $15K/year
• Deal velocity: 15 percent more deals closed/year
• Compliance fines: Avoided $500K+ in potential penalties

Who Uses Numra?

Primary User Roles

Investment Professionals

Screen targets, build financial models, monitor portfolio all with auto-sourced data.

Credit Analysts

Assess borrower risk, run stress tests, generate reports without manual entry.

Corporate Development

Track competitors, identify M&A candidates, plan integrations using live data.

Compliance Officers

Automate CDD, screen UBOs, produce audit-ready reports.

Industry Adoption

Private Equity

KKR, Vista Equity: Use Numra for 100 percent of first-pass screening cutting deal cycle by 18 days.

Commercial Banking

JPMorgan Commercial, BNP Paribas: Embed Numra in loan origination reducing underwriting time by 65 percent.

Asset Management

BlackRock Alternatives, Apollo: Monitor 5,000+ portfolio companies for early-warning signals.

Integration and Ecosystem

Native Platform Integrations

Deal and Portfolio Tools

DealCloud: Auto-populate company profiles and deal memos. PitchBook: Enrich targets with financials and ownership. CapIQ: Cross-verify metrics and fill gaps.

CRM and Workflow

Salesforce: Push risk alerts to relationship managers. Microsoft Word: Insert live charts and source links into memos.

Risk and Compliance

Refinitiv World-Check: Augment sanctions screening with financial context. LexisNexis: Link adverse media to entity graph.

API and Extensibility

Numra API Suite

Search: “Find companies with revenue >100M euros in Germany.” Extract: “Pull 3-year EBITDA for Siemens AG.” Monitor: “Alert if debt/EBITDA >4.0x for portfolio companies.”

Developer Tools

Python SDK: Automate batch analysis for portfolio reviews. Webhooks: Trigger workflows on new filings (e.g., “10-K filed → update model”). Postman Collection: Test integrations instantly.

Partner Ecosystem

Data Providers: Bureau van Dijk, Orbis (complementary coverage). Consultants: FTI, Alvarez and Marsal (implementation). Academia: LSE, Wharton (validation studies).

Pricing and Accessibility

Tiered Subscription Model

Analyst Plan

$15,000/year: 500 searches/month, SEC/UK/EU coverage, basic exports.

Team Plan

$45,000/year: Unlimited searches, global coverage, DealCloud/Salesforce plugins, API access.

Enterprise Plan

Custom: Private cloud, custom entity models, SOC 2, dedicated support.

Commercial Flexibility

Usage-Based Add-Ons

• Extra jurisdictions: $5,000/region/year (e.g., LATAM, APAC)
• Custom extraction: $10,000 one-time (e.g., “Extract R&D cap table from biotech 10-Ks”)

Pilot Program

Free 30-day trial; pay only if research time drops >70 percent.

Future Roadmap

Near-Term Enhancements (2025–2026)

Generative Financial Intelligence

• Memo Drafting: “Summarize Q1 risks for Acme Corp” → audit-ready paragraph with citations
• Peer Commentary: “How does Target’s margin compare to peers?” → narrative with benchmarks
• Scenario Narratives: “Explain impact of 10 percent revenue decline” → plain-English risk assessment

Enhanced Regulatory Coverage

• China: CSRC filings and SAFE reports (via licensed partners)
• India: MCA21 and BSE/NSE disclosures
• Brazil: CVM and Receita Federal data

Long-Term Vision (2026–2027)

Autonomous Deal Research

AI proposes target lists, runs preliminary models, and flags red flags presenting findings for human review.

Real-Time Financial Health

Monitor news, filings, and market data to update risk scores hourly not quarterly.

Global Ownership Transparency

Map ultimate beneficial ownership across shell networks in real time supporting AML/CFT efforts.

Benefits of Numra

Operational Excellence

Speed and Throughput

Target screening: 2 weeks → 4 hours. Credit underwriting: 3 days → 4 hours. KYC refresh: Quarterly → continuous.

Accuracy and Quality

Data errors: 12 percent → 1.8 percent. Missed risks: minus 22 percent in portfolios. Audit readiness: 100 percent source-tracked.

Cost Efficiency

Research costs: 180,000 dollars/year → 15,000 dollars/year. Deal velocity: plus 15 percent more closed deals. Compliance: Avoided 500,000 dollars plus in fines.

Strategic Impact

Decision Confidence

Deeper insights: 3-year trends, peer context, ownership webs. Faster iteration: Test 10 scenarios in time one used to take. Defensible conclusions: Every number cited to source.

Risk Mitigation

Early warnings: Spot covenant breaches before defaults. Regulatory alignment: SOC 2, GDPR, FINRA built in. Reputation protection: Avoid ESG blowups via subsidiary monitoring.

Competitive Advantage

First-mover insight: Act on filings hours after release. Talent leverage: One analyst supports 5 deal teams. Scalable diligence: Cover 10x more targets without headcount.

Advantages and Disadvantages

Key Advantages

Finance-Specific Intelligence

Trained on financial filings not generic text ensuring precision and relevance.

Source Transparency

Every data point links to original document critical for audits and compliance.

Workflow Integration

Plugs into existing tools (DealCloud, PitchBook) no new UI to learn.

Proven ROI

70 percent time reduction; 1.8 percent error rate; 98 percent client retention.

Notable Disadvantages

Coverage Gaps in Emerging Markets

Limited depth in Africa, parts of LATAM improving via 2025 partnerships.

Requires Financial Literacy

Users need to understand terms like EBITDA, DSCR, UBO training recommended.

Not a Replacement for Judgment

AI surfaces data; humans assess context, strategy, and soft factors.

Conclusion

The Intelligent Foundation of Modern Finance

Numra operates behind the scenes but its impact is felt in every closed deal, approved loan, and compliant portfolio. In an era where financial data grows exponentially but attention is scarce, it ensures that insight is not drowned in noise.

It is not about replacing analysts. It is about empowering them with intelligence that is deeper, faster, and always defensible. For finance professionals serious about the future of due diligence, Numra is not just a tool. It is the intelligent foundation of modern finance.