From Numbers to Narratives: Using RAG for Risk Management in Indian Equities
Risk in markets isn’t always a spike in volatility.
Sometimes, it’s a sentence hidden in a SEBI order.
1 Before RAG: When Risk Meant Only Numbers
Traditionally, equity risk management in India revolved around quantitative metrics:
- Volatility
- Beta vs NIFTY
- Value at Risk (VaR)
- Drawdowns and correlations
These models were mathematically sound — but they assumedone thing:
All relevant risk is already reflected in prices.
In reality, many of the biggest risks in Indian marketsappear outside price data:
- Regulatory scrutiny
- Governance issues
- Promoter pledging
- Policy changes by RBI or SEBI
By the time prices reacted, it was often too late.
2 The Missing Layer: Context
Two stocks can show identical volatility and beta, yet carry very different risks.
Why?
Because risk is not just statistical — it’s contextual:
- What is the regulator saying?
- What changed in the latest earnings call?
- Is there a governance or compliance overhang?
Traditional models couldn’t read this information.
They could only react after the market moved.
3 Enter RAG: Retrieval-Augmented Generation
RAG (Retrieval-Augmented Generation) bridges this gap.
Instead of relying only on model memory, RAG:
- Retrieves relevant documents (news, filings, policies)
- Reasons over them using a language model
In simple terms:
RAG allows your risk system to read before it decides.
4 RAG Workflow
5 RAG Applied to Indian Equity Risk
In an Indian market setting, RAG-enhanced risk management combines:
Quant Risk (What we already had)
- Volatility
- Liquidity risk
- Correlation
Contextual Risk (What we were missing)
- SEBI & RBI regulations
- Corporate governance signals
- Promoter behavior
- Macro & sectoral narratives
So instead of just saying:
“Risk is high”
The system can say:
“Risk is high due to regulatory overhang and governance concerns, despite stable recent price movement.”
That explanation is actionable.
6 Why This Matters
RAG doesn’t replace traditional models — it completes them.
For a portfolio manager:
- It becomes an early warning system
- Risks are surfaced before prices react
For analysts:
- Risk explanations are traceable and defensible
Risk Is a Story — RAG Helps You Read It
Markets don’t move only on math.
They move on information, interpretation, and timing.
Traditional models taught us how much risk exists.
RAG helps us understand why it exists.
And in a market as complex, regulated, and narrative-driven as India’s —
that difference can be the edge.