We extract insurance quotes, credit card APRs, mortgage rates, and loan terms from money.co.uk. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Credit Cards objects from money.co.uk. All fields typed and schema-versioned.
"card_name": "Platinum Balance Transfer", "provider": "Barclaycard", "apr_rep": 24.9, "balance_transfer_fee": 2.99, "bt_duration_months": 28, "annual_fee": 0, "credit_limit_min": 50
| # | card_name | provider | apr_rep | purchase_rate | balance_transfer_fee | bt_duration_months |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Mortgages objects from money.co.uk. All fields typed and schema-versioned.
"product_name": "2 Year Fixed Rate", "provider": "NatWest", "mortgage_type": "Fixed", "initial_rate": 4.89, "aprc": 6.2, "max_ltv": 85, "fee": 995, "early_repayment_charge": true
| # | product_name | provider | mortgage_type | initial_rate | follow_on_rate | aprc |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Personal Loans objects from money.co.uk. All fields typed and schema-versioned.
"provider": "Tesco Bank", "loan_amount_tier": "7500-15000", "apr_rep": 6.1, "term_min": 12, "term_max": 60, "early_settlement_fee": true, "funding_time": "Same day"
| # | provider | loan_amount_tier | apr_rep | term_min | term_max | monthly_repayment |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Car Insurance objects from money.co.uk. All fields typed and schema-versioned.
"provider": "Admiral", "policy_name": "Comprehensive Plus", "defaqto_rating": 5, "cover_type": "Comprehensive", "excess_compulsory": 150, "windscreen_cover": true, "courtesy_car": true
| # | provider | policy_name | defaqto_rating | cover_type | excess_compulsory | excess_voluntary |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Provider Reviews objects from money.co.uk. All fields typed and schema-versioned.
"provider_name": "Halifax", "product_category": "Mortgages", "overall_rating": 4.2, "review_count": 3482, "customer_service_score": 4.1, "value_for_money_score": 4.3, "review_date": "2026-03-14"
| # | provider_name | product_category | overall_rating | review_count | customer_service_score | value_for_money_score |
|---|---|---|---|---|---|---|
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Our money.co.uk scraper handles dynamic rate tables, nested policy details, and multi-step comparison flows. We normalise complex financial data into clean schemas.
Capture APRs, balance transfer durations, purchase rates, annual fees, and reward structures across all card categories.
Extract fixed, tracker, and variable rates mapped to specific LTV bands, including product fees and early repayment rules.
Normalise representative APRs and total repayment calculations across different borrowing amounts and loan terms.
Scrape compulsory excess, Defaqto ratings, and specific cover inclusions for car, home, and travel insurance products.
Extract download speeds, contract lengths, setup costs, and monthly pricing for telecoms providers.
Collect overall ratings, sub-category scores, and full review text to gauge consumer sentiment.
Track interest rate and APR adjustments daily to maintain an accurate view of the lending market.
Identify hidden costs like arrangement fees, balance transfer percentages, and early settlement charges.
Run continuous pipelines that only emit records when a product's rate, fee, or terms change.
Brief in. Clean data out.
Select the financial categories, providers, or specific product lines you need to track. We design the extraction schema.
We configure crawlers to navigate money.co.uk rate tables, applying UK residential proxies to bypass regional blocks.
Schema validation, null-rate checks, and financial outlier detection before full pipeline launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting accurate rates requires parsing dynamic tables and handling strict regional blocking. Here is how we maintain pipeline stability.
Financial products are often displayed in complex, JavaScript-rendered data grids. We use Playwright to execute the page scripts and normalise these grids into flat, queryable records.
Money.co.uk aggressively blocks non-UK traffic and datacenter IPs. We route all requests through premium UK residential proxy pools to ensure uninterrupted access.
Comparison sites frequently A/B test their layouts. We use multiple fallback chains for critical fields like APR and monthly cost to prevent pipeline breakage.
Instead of dumping the entire catalogue daily, we hash product records and only deliver rows where rates, fees, or terms have changed since the last run.
We monitor extraction output for anomalous values, such as a 0% APR on a standard credit card, triggering alerts before bad data reaches your warehouse.
Banks and lenders track daily APR and interest rate changes across the market to adjust their own product pricing.
Financial institutions identify gaps in specific LTV bands or loan tiers to launch targeted new products.
Analysts track which providers dominate the top positions in comparison tables across different financial categories.
Marketing teams monitor how their products are ranked and displayed on major comparison engines.
Insurance companies compare policy limits, compulsory excess amounts, and Defaqto ratings against market averages.
Customer experience teams mine provider reviews to identify service issues and benchmark against competitors.
"Financial comparison data is highly volatile. Capturing rate changes across hundreds of providers requires infrastructure, not just a script."
Tracking money.co.uk means navigating complex form flows, dynamic rate tables, and strict UK regional blocking. DataFlirt handles the proxy rotation, session management, and table normalisation so your data science team can focus on rate analysis rather than broken DOM selectors.
Everything supported by our money.co.uk scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright handles JavaScript execution for dynamic rate tables and interactive product filters.
We route requests through premium UK residential ISP proxies to avoid geographic blocking and maintain high success rates on financial domains.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About money.co.uk scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available financial comparison data is generally permissible. DataFlirt extracts only public, non-authenticated product details, rates, and reviews. We do not extract personal credit data or bypass authentication walls.
We use UK-based residential ISP proxies combined with realistic browser fingerprints. This ensures our requests appear as standard UK consumer traffic, avoiding blocks applied to datacenter IPs.
We typically run pipelines daily to capture overnight rate changes. For high-priority categories, we can configure sub-daily runs depending on the target volume.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series record for APRs, interest rates, and fees from the date your pipeline starts.
Our minimum engagement covers specific product categories (e.g., all credit cards and personal loans) with weekly or daily delivery. We price based on data volume and extraction frequency.
Yes. We provide a sample extraction of a specific category (e.g., top 100 mortgages) during the scoping phase to validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of mortgage rates or a complete extraction of credit card terms — we scope, build, and operate the pipeline. Tell us what you need.
