• Pricing
Book a demo

Automate your financial report extraction with ScrapingBot

Swiftask integrates with ScrapingBot to automate the collection and analysis of your financial data. Improve accuracy and speed.

Result:

Eliminate manual data entry and gain instant access to your key financial indicators.

Manual financial data collection slows down your analysis

Extracting financial data from web sources is a repetitive and error-prone task. Your teams waste valuable time copy-pasting figures instead of analyzing them.

Main negative impacts:

  • Data entry error risk: Manual handling of financial data drastically increases the risk of errors, impacting your decision-making.
  • Time-consuming processes: Daily or weekly data collection monopolizes your analysts on low-value-added tasks.
  • Lack of decision-making agility: Without automation, your reports are often obsolete by the time they reach decision-makers.

Swiftask automates financial data extraction via ScrapingBot. Your AI agents collect, structure, and analyze information in real-time.

BEFORE / AFTER

What changes with Swiftask

The traditional method

An analyst spends hours navigating financial data sites, copying tables into Excel, and cleaning formats. The process is slow and repetitive.

The Swiftask + ScrapingBot approach

Your AI agent triggers ScrapingBot on a defined schedule. Data is extracted, normalized, and integrated directly into your reporting tools.

Setting up your extraction pipeline

STEP 1 : Swiftask agent configuration

Create a dedicated financial monitoring agent in Swiftask.

STEP 2 : ScrapingBot connection

Integrate ScrapingBot to target your financial data sources.

STEP 3 : Extraction rule definition

Indicate the key indicators to monitor and extract.

STEP 4 : Flow automation

Schedule execution and receive your analyzed reports.

Intelligent extraction capabilities

The agent analyzes web page structures to extract relevant financial tables.

  • Target connector: The agent performs the right actions in scrapingbot based on event context.
  • Automated actions: Extraction of balance sheets, income statements, and ratios. Data format normalization. Alerts for major data changes.
  • Native governance: All extractions are logged to ensure an audit trail.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-scrapingbot@swiftask.ai ). You keep full visibility on every action and every sent message.

Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.

Strategic advantages of automation

1. Data accuracy

Drastic reduction of human errors related to data entry.

2. Productivity gains

Free up time for actual strategic analysis.

3. Real-time reporting

Immediate access to the latest market data.

4. Increased scalability

Monitor hundreds of sources simultaneously.

5. Seamless integration

Direct connection with your management systems.

Data governance and security

Swiftask applies enterprise-grade security standards for your scrapingbot automations.

  • Secure API management: Encrypted connection between Swiftask and ScrapingBot.
  • Access control: Restricted access to sensitive financial data.
  • Compliance and audit: Full traceability of performed extractions.
  • Technological independence: Modular architecture without critical dependencies.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Measurable operational impact

MetricBeforeAfter
Extraction timeSeveral hoursA few minutes
Error rateHigh (manual)Near zero
Update frequencyWeeklyReal-time

Take action with scrapingbot

Eliminate manual data entry and gain instant access to your key financial indicators.