Analyzing financial impact of political events with real-time news RAG

Using the Bigdata.com SDK, analysts and fintech teams can build a custom RAG pipeline that brings live financial news directly into AI-driven insights. Thus, they can stay ahead of policy-driven market shifts by grounding decisions in insights from live financial news.

This is essential for investors, strategists, and analysts who need to make fast, evidence-backed decisions.

Use case example: Climate change & the 2024 U.S. election

Objective

Use Bigdata.com’s RAG pipeline to understand how climate-related policy positions in the 2024 U.S. presidential election may impact sectors like green energy, ESG investing, and global trade.

Why it matters

Climate policy shifts influence:

• Green tech investments
• Carbon markets and pricing
• Global ESG regulation
• Foreign investment risk in emerging markets

In the lead-up to the 2024 election, financial markets were watching for signals. A potential reversal of U.S. commitments to climate goals or ESG frameworks meant a reshape of investment strategies globally.

The solution with Bigdata RAG

1. Retrieve relevant financial news. Use semantic search with the Bigdata SDK to pull recent news related to climate and the 2024 election. For example:

“A Trump presidency would certainly represent a negative outcome for South Africa and the rest of Africa,” said Mteto Nyati, noting reduced U.S. investment would slow growth agendas across developing regions.” — [Document ID: 43CE65FB8CA2D8D99F82BF40C8BBA374]

2. Structure the data. Convert retrieved news into XML-tagged chunks with document metadata. This enables precise citations and auditability.

3. Generate an answer with citations. Feed the news chunks into an LLM (e.g. GPT-4o-mini) to produce a well-structured response:“ A potential reversal of the Paris 2050 agreement under a Trump presidency could weaken global climate commitments, particularly affecting multinational investment flows.” [43CE65FB8CA2D8D99F82BF40C8BBA374, chunk 9, date 2024-10-01].4. Trace sources. All statements are traceable with clickable links to the original documents on Bigdata.com.

Technical stack

• Data source: Bigdata.com financial news archive
• Search: Similarity-based semantic retrieval
• LLM: OpenAI GPT-4o-mini
• Output: Markdown with embedded citations
• Cost: ~$0.00097 per query

Ideal for:

• Hedge funds and asset managers monitoring political risk
• ESG research teams tracking environmental policy
• Corporate strategy groups scanning for macroeconomic threats
• AI/ML teams building compliant RAG-based applications

Sample query

Question: What impact will climate change policy have on global markets if Trump wins the 2024 U.S. election?

Sample response:

“Climate policy shifts could trigger a pullback from the Paris Agreement, undermine green investment incentives, and reduce U.S. foreign engagement — especially affecting regions like Africa that rely on climate-linked capital and trade.” [43CE65FB8CA2D8D99F82BF40C8BBA374, chunk 5].

Ready to build your own financial news RAG? Follow our step-by-step guide to start building.