Automated Reporting Tools

How I use Claude.ai to save time and hassle chasing submissions from businesses We’ve all had to wait on forecast information, or received incomplete submissions and then had to chase. The good news is that automating this task, which isn’t my favourite(!) is quick and easy using AI. To give an example, I’ve generated a script using a simple prompt in Claude.ai to read reports (in this case csv, word, pdf and powerpoint) and query unclear items or where an explanation is needed. This saves time and allows me to move onto other things. Here’s what the script does: Reads reports in CSV, Word (DOCX), PDF, and PowerPoint (PPTX) formats Automatically detects the file type and processes accordingly Analyzes the report content for unclear items or those needing explanation Generates a formatted HTML email with the findings Sends the email to relevant stakeholders Saves a copy of the email content as an HTML file for record-keeping This versatile automation can save hours of manual work across different document types and ensure that important issues are promptly addressed. And it’s not just useful for treasurers, it can be used by project managers, team leads, and anyone dealing with regular reporting processes using various file formats. Key features of the script: Uses pandas for data manipulation Implements file type detection and appropriate reading methods Utilizes libraries like python-docx, PyPDF2, and python-pptx for different file formats Generates clean, formatted HTML emails using Arial font Easily customizable for different report formats and email content I've included the full code in the comments below. Feel free to adapt it to your needs or reach out if you have any questions! This is just one example of the type of automation that we’re focussing on at Your Treasury - AI your way I’d encourage you to go to Claude.ai and try creating something similar yourself. #Python #Automation #ProjectManagement #DataAnalysis #EmailAutomation #DocumentProcessing ——————————————————- Example prompt Create a Python program where a user uploads a file and python then detects the file type (doc, excel, pdf, PowerPoint) and Python then reads a report and send out emails to relevant stakeholders if anything is unclear or needs more explanation. Produce example code to show this, including the report and a sample email which should be saved as an html file and formatted in Arial text. Prompt me if you have any questions

Financial reporting should be about strategic decision-making, not manual data wrangling. Yet, finance teams still spend days pulling data, reconciling numbers, and formatting reports—only to find errors at the last minute. The process is time-consuming, prone to mistakes, and slows down critical business decisions. Robotic Process Automation (RPA) with tools like UI Path is transforming financial reporting. Instead of manually extracting, cleaning, and consolidating data, automation does it for you—accurately, in real time, and without delays. Here’s how it works: ✅ Data is automatically pulled from multiple sources (ERP, CRM, spreadsheets, banks). ✅ Reconciliations happen instantly, reducing errors and improving accuracy. ✅ Reports are generated in minutes—standardized, formatted, and audit-ready. Without automation, finance teams are stuck in reactive mode, spending 80% of their time on report preparation and only 20% on analysis. The result? Slower decision-making, frustrated CFOs, and outdated insights. A company that automated its reporting process cut preparation time by 60%—freeing up finance teams to focus on forecasting, strategy, and real business impact. If your team is still manually preparing reports, you’re already behind. It’s time to automate and turn your finance team into a real-time data powerhouse. 📩 Let’s talk about how RPA can transform your financial reporting. Drop a comment or send me a message if you’re ready to make the shift! #Automation #RPA #FinanceTransformation #CFO #FinancialReporting

Still emailing reports manually? It's time to modernize your approach. In 2024, the best practice is simple: ➡️ Report Generation: Reports are created and saved directly to storage. ➡️ Automated Detection: A listener app detects new files as they’re saved. ➡️ Automatic Distribution: The listener app packages the files and emails them automatically. This works for CSVs, Excel reports, AI-generated text, images—whatever you need. If the zip file is small enough, it’s sent as an attachment. If it’s too large, a download link is provided instead. As an Azure specialist, here’s how I do it: ➡️ Write a Python program (leveraging open-source tools) to write to Azure Data Lake. ➡️ Create a pipeline using Azure Machine Learning Service, packaging the code into a container with assigned compute. ➡️ Schedule the pipeline through Azure Data Factory. ➡️ Distribute with Logic Apps to handle file detection and email sending. Simple, efficient, and fully automated. #data #cloudengineering #reporting #azure #microsoft