How to Practically Use AI in Fraud Detection and Risk Management?

DAY – 1 – Google Sheets with AI Add-ons

• Automating financial modeling with AI-powered add-ons.
• Using Google Finance API for live market data tracking.
• Building AI-enhanced dashboards for financial analysis.

DAY – 2 – Microsoft Excel with AI Tools

• Extracting AI-driven insights from financial datasets.
• Implementing predictive analytics for forecasting.
• Streamlining data processing with automation tools.
  

DAY – 3 – Co-Pilot in Excel

• Simplifying budget reconciliation with AI.
• Enhancing financial accuracy through intelligent recommendations.
• Reducing manual effort in financial audits and reports.

DAY – 4 – Tableau Public

• Designing interactive financial dashboards.
• Connecting and analyzing real-time financial data.
• Using Tableau’s AI-powered analytics for trend forecasting.

DAY – 5 – Qlik Sense

• Developing smart dashboards for deep data insights.
• Leveraging Qlik’s associative data model for discovery.
• Applying predictive analytics for business strategy.

DAY – 6 – Google Colab

• Running Python-based financial models on cloud notebooks.
• Processing and visualizing large datasets with AI.
• Using cloud-based GPUs/TPUs for complex computations.

DAY – 7 – Chat PDF

• Extracting key insights from financial reports.
• Automating financial document analysis.
• Using AI chat tools for quick financial queries and research.

Note: Dates – 15th, 16th, 21st, 22nd, 23rd, 24th, and 25th April 2025