Automated gathering and collation of financial data from multiple sources

Purpose

1. The automation of gathering and collating financial data from multiple sources allows economic consultants to systematically retrieve, organize, and consolidate financial metrics, transactions, and analysis from disparate platforms, APIs, databases, and websites for standardized financial analysis and reporting.

2. This automating workflow eliminates manual data aggregation, enhances accuracy, ensures current data availability, accelerates reporting cycles, and supports regulatory compliance and client insight delivery.

Trigger Conditions

1. Schedule-based trigger: Automator initiates at fixed intervals (e.g., daily, hourly).

2. Data update event: Automatedly starts upon new data availability or changes in connected systems.

3. User-initiated: Economic consultants or analysts execute the automation process upon demand for ad hoc reporting.

Platform Variants

1. Google Sheets

• Feature/Setting: Sheets API – automate financial data fetching, update spreadsheets, and trigger macros via Sheets API (accounts.read, spreadsheets.values.update).
  

2. Microsoft Excel Online

• Feature/Setting: Graph API – automates updates in Excel workbooks by utilizing /me/drive/items/{item-id}/workbook worksheet operations.
  

3. QuickBooks Online

• Feature/Setting: Reports and Transactions API – automate retrieval of transactions, balance sheets, and profit & loss data.
  

4. Xero

• Feature/Setting: Accounting API – automates GET requests to fetch bank transactions, account balances, and financial statements.
  

5. Plaid

• Feature/Setting: Transactions endpoint – automates pulling of financial, banking, and investment data via the /transactions/get endpoint.
  

6. Yodlee

• Feature/Setting: Data Aggregation API – automates retrieval of user-permissioned accounts data, balances, and transactions.
  

7. Salesforce

• Feature/Setting: SOQL queries via REST API – automates the retrieval of financial records and custom report exports.
  

8. Netsuite

• Feature/Setting: SuiteTalk Web Services – automates pulling of core financial and accounting data and report exports.
  

9. SAP

• Feature/Setting: S/4HANA API – automates connection to financial tables for real-time data extraction via OData services.
  

10. Oracle Financials Cloud

• Feature/Setting: Fusion ERP API – automates queries to GL and subledger data using the /finAccounts and /finLedger endpoints.
  

11. Bloomberg Terminal

• Feature/Setting: Excel Add-In API – automates pulling of securities, pricing, and market data directly to spreadsheets.
  

12. Refinitiv (Thomson Reuters)

• Feature/Setting: DataScope Select and Eikon APIs – automates scheduled data pulls for market prices, economic metrics, and tick data.
  

13. S&P Capital IQ

• Feature/Setting: Capital IQ API – automates equity, fixed income, and financial statement extraction for analytics.
  

14. Alpha Vantage

• Feature/Setting: Stock APIs – automates retrieval of stocks, forex, and crypto data for financial dashboarding.
  

15. Yahoo Finance

• Feature/Setting: Finance API or YFinance Python library – automates pulling public company financials and market data programmatically.
  

16. Amazon Web Services (AWS Lambda + S3)

• Feature/Setting: Lambda scheduled invocations – automate extraction, processing, and storing financial datasets in S3.
  

17. Azure Data Factory

• Feature/Setting: Pipeline Automation – automates data ingestion from on-prem & cloud financial sources to target databases.
  

18. Slack

• Feature/Setting: Incoming Webhooks – automate notification of data aggregation completion and alerting for exceptions.
  

19. Dropbox

• Feature/Setting: Dropbox API – automates uploading and syncing consolidated financial reports for distributed teams.
  

20. MongoDB Atlas

• Feature/Setting: Data API – automates the collation of financial records in a document database for analytics automation.
  

Benefits

1. Automates repetitive manual data entry and collation tasks, optimizing analyst productivity.

2. Automated timeliness and frequency of data refreshes for up-to-date and accurate reporting.

3. Automator improves consistency across multi-source, multi-channel data sets.

4. Reduces human error risks and supports auditable, automated compliance.

5. Enabling automatable financial data flows empowers faster insight and decision-making.

6. Automating external and internal data collation strengthens competitive analysis and forecasting accuracy.

7. Boosts stakeholder satisfaction with automatedly generated, timely financial analytics.