Investment Industry Intelligence Dashboard
Turned 20 years of static survey data into an interactive platform policy staff can query in plain English.
Delivered for The Investment Association. Interface shown here uses representative data reflecting the platform's real structure.
Outcome
Deployed internally at The Investment Association. Policy staff can visualise any trend, compare metrics across years and get natural-language summaries of changes, supporting advocacy work, press briefings and regulatory submissions.
Product Interface
2004
3.2£tn
2023
11.4£tn
Change
+256%
Product interface · Representative data
The Challenge
The Investment Association's annual Investment Management Survey covers AUM, asset allocation, firm count and active-vs-passive trends across the UK investment industry, but the data was locked in static spreadsheets and PDFs. Policy staff couldn't easily spot trends, compare years, or answer ad hoc questions without manual digging.
Existing Process
Each year's survey results existed as a standalone report. Comparing across years meant manually cross-referencing spreadsheets, and there was no way to ask a question of the data directly.
The Approach
Built a full-stack dashboard ingesting 20 years of historical survey data into PostgreSQL, with a Next.js frontend and Recharts for interactive visualisation across multiple chart types. An AI layer with retrieval-augmented context over the structured dataset lets staff ask questions in natural language and get answers grounded in the underlying data.
What Was Built
A historical data exploration tool with interactive charts and dashboards, natural-language querying, trend analysis and forecasting views, sentiment and keyword analysis on qualitative survey responses, and administrative tools for updating data and commentary year on year.
- Historical data exploration across 20+ years
- Interactive charts and dashboards
- Natural-language querying
- Trend analysis and forecasting
- Sentiment and keyword analysis
- Admin tools for updating data and commentary
Thimoth's Role
Translated a research and data-access requirement into a usable digital platform, from database design through to the natural-language query layer.
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