Structured company data, without the chaos.

SME Credit Assessment Using Electronic Filing Data

Access structured balance sheet and P&L data from UK companies that file electronically with Companies House. DataLedger provides pre-calculated financial ratios and growth metrics for SME credit assessment and portfolio analysis.

Key use cases:

• Debt ratio analysis: Use pre-calculated debt-to-equity and debt-to-asset ratios for credit risk assessment

• Asset growth monitoring: Track year-on-year asset growth and net asset growth rates to identify expanding businesses

• SME portfolio screening: Filter companies by equity levels, total assets, and liability thresholds for targeted lending

• Financial health tracking: Monitor changes in key ratios across your client base using verified data

Available financial metrics:

• Debt-to-equity ratios (current and previous year)

• Debt-to-asset ratios (current and previous year)

• Asset growth rates (year-on-year percentage change)

• Net asset growth rates (year-on-year percentage change)

• Complete balance sheet line items (when using detailed API calls)

• P&L data including turnover and profit/loss (where companies file full accounts)

Data coverage: Electronic filings only - excludes large corporates that file on paper, but covers the growing SME and digitally-native business segment.

Technical implementation: REST API with financial ratio filters, bulk company screening, data quality indicators.

Progressive SME lenders are using structured electronic filing data for faster credit decisions. Still manually processing company accounts whilst competitors leverage structured data?

Skip Building Companies House Infrastructure - Use Our API Instead

Avoid the cost and complexity of building your own Companies House data pipeline. DataLedger provides ready-to-use structured financial data via API, eliminating months of development work and ongoing infrastructure costs.

Key benefits:

• Avoid infrastructure costs: No need to build ETL pipelines, data storage, or processing systems for Companies House filings

• Reduce engineering overhead: Skip months of development work parsing XBRL files and handling data quality issues

• Enhanced product offering: Provide users with debt ratios, growth metrics, and financial analysis without building the calculation engine

• Faster time-to-market: Integrate financial intelligence features in days, not months

• Ongoing maintenance savings: No need to monitor Companies House API changes or handle data format updates

Implementation advantages:

• On-demand data access: Call our API as needed rather than storing and maintaining your own database

• Pre-calculated financial ratios: Get debt-to-equity, debt-to-asset, and growth rates without building calculation logic

• Quality-assured data: Verified financial metrics (cVerified, pVerified) eliminate data validation work

• Structured JSON responses: Clean, consistent data format perfect for AI/ML applications

• Scalable pricing: Credit-based model grows with your usage without fixed infrastructure costs

Product enhancement opportunities:

• Intelligent onboarding: Auto-populate company profiles reducing user data entry by 90%

• AI-powered insights: Feed structured financial data into LLMs for custom report generation

• Risk scoring features: Embed pre-calculated financial health indicators into your platform

• Competitive analysis tools: Provide users with industry benchmarking using our sector data

• Lead qualification enhancement: Enrich CRM records with growth indicators and financial stability scores

Technical implementation: RESTful API with comprehensive documentation and integration examples. Credit-based pricing eliminates upfront infrastructure investment.

Leading software platforms are focusing on their core product whilst leveraging DataLedger for financial intelligence. Still building Companies House infrastructure whilst competitors ship features faster?

SME Market Research & Industry Analysis

Access structured financial data for comprehensive market research and industry analysis. DataLedger provides detailed balance sheet and P&L data for evidence-based market insights and competitive intelligence.

Key use cases:

• Market sizing and segmentation: Use financial filters to calculate total addressable market by revenue, assets, or geographic region

• Industry trend analysis: Track sector performance using growth rates, debt ratios, and financial health indicators across SIC codes

• Competitive benchmarking: Analyse competitor financial performance using balance sheet and P&L data

• Economic impact assessment: Monitor SME sector health through asset growth and financial stability metrics

• Research report development: Generate data-driven insights using comprehensive electronic filing database

Available analytical capabilities:

• Financial health analysis using debt-to-equity and debt-to-asset ratios

• Growth trend identification through asset growth and net asset growth rates

• Sector performance comparison

• Geographic market analysis using postcode and local authority data

• Employee count analysis for workforce and operational insights

Data coverage: Electronic filing companies - comprehensive coverage of SMEs, growth companies, and digitally-native businesses.

Technical implementation: Bulk data export, advanced filtering APIs, statistical analysis capabilities, and geographic segmentation tools.

Leading market research firms are using structured electronic filing data for comprehensive industry analysis. Still relying on surveys and estimates whilst comprehensive financial data provides definitive market insights?

Advisory Services Using Structured Financial Data

DataLedger provides structured balance sheet and P&L analysis for modern advisory services.

Key use cases:

• Growth company identification: Use asset growth rates to identify expanding businesses for advisory services

• EIS qualifying company analysis: Filter by equity levels, employee counts, and growth indicators for EIS investment advice

• Client benchmarking: Compare client debt-to-equity ratios and growth metrics against sector peers

• Financial health monitoring: Track year-on-year balance sheet changes for existing advisory clients

• Tech sector focus: Electronic filers include many SaaS, consulting, and digital businesses

Available analysis capabilities:

• Pre-calculated debt-to-equity and debt-to-asset ratios for financial health assessment

• Year-on-year asset growth analysis for expansion tracking

• Net asset growth monitoring for wealth creation assessment

• Complete balance sheet breakdown (fixed assets, current assets, liabilities)

• P&L analysis including turnover and margins (where full accounts are filed)

• Employee count data for operational analysis

Data coverage: Companies filing electronically - primarily SMEs, growth companies, and tech businesses rather than traditional large corporates.

Technical implementation: API filtering by growth rates, financial ratios, and balance sheet metrics with quality assurance indicators.

Modern advisory firms are building expertise in the growing SME sector through electronic filing intelligence. Focusing only on traditional large corporates whilst the digital economy expands?

Growth Company Recruitment Intelligence

Target companies with demonstrated financial growth using structured balance sheet metrics. DataLedger's electronic filing database captures dynamic businesses with expanding operations.

Key use cases:

• Growth indicator targeting: Use asset growth rates to identify companies likely expanding their workforce

• Financial stability screening: Filter prospects by debt-to-equity ratios to focus on financially stable potential clients

• Expansion tracking: Monitor year-on-year asset growth and employee count changes for hiring predictions

• Sector specialisation: Electronic filers include many tech, consulting, and digital businesses with active recruitment needs

• Prospect qualification: Focus outreach on companies with positive financial indicators

Available growth indicators:

• Year-on-year asset growth rates (companies expanding their asset base)

• Net asset growth tracking (business expansion indicator)

• Employee count filtering (direct hiring indicator)

• Debt-to-equity analysis for financial stability assessment

• Incorporation date filtering to identify new, potentially expanding businesses

• SIC code targeting for sector-specific recruitment focus

Data coverage: Electronic filing companies only - excludes traditional large corporates but captures the dynamic SME and growth company segment.

Technical implementation: API filtering by employee ranges, growth rate thresholds, financial stability metrics, and incorporation dates.

Leading recruitment agencies are using financial growth indicators to identify hiring opportunities before competitors. Still cold-calling randomly whilst growth data shows exactly which companies are expanding?

Data-Driven Prospect Identification & Lead Qualification

Transform your business development approach using structured financial intelligence. DataLedger provides the data needed for targeted prospecting, lead scoring, and sales pipeline development.

Key use cases:

• Prospect qualification: Filter potential clients by financial health indicators and growth metrics

• Lead scoring and prioritisation: Rank prospects using debt-to-equity ratios, asset growth, and financial stability

• Target market identification: Identify high-value prospects by revenue, assets, and employee count thresholds

• Sales territory planning: Analyse prospect density and financial profiles across geographic regions

• Pipeline development: Build targeted prospect lists using industry, size, and growth criteria

Available targeting capabilities:

• Financial health scoring using pre-calculated debt and asset ratios

• Growth company identification through asset growth and net asset growth rates

• Size-based targeting by revenue, assets, and employee count

• Geographic targeting using postcode and local authority filters

• Industry-specific prospecting across detailed SIC code classifications

• New business identification using incorporation date filtering

Data coverage: Electronic filing companies - ideal for targeting SMEs, growth companies, and tech businesses that often have higher technology adoption rates.

Technical implementation: Advanced search APIs, prospect list generation, growth indicator filtering, and CRM integration capabilities.

Top-performing business development teams are using financial intelligence for targeted prospecting. Still working from basic company directories whilst structured data reveals the best prospects?