Wealth Analytica's portfolio analysis engine models client portfolios against the live Morningstar universe — funds, OEICs, investment trusts, ETFs and single equities. We look through fund holdings to compute real asset allocation, sector exposure and risk metrics. The data refreshes intraday for prices and daily for fund-level analytics. Holdings come from your existing client records via CSV or REST import, so the analytics reflect what the client actually owns.
The data behind the dashboard
Most analytics tools you've used run on a fund universe that's measured in tens of thousands. Ours is 350,000+ instruments — every UK retail fund, every UK and international ETF, every investment trust, plus single equities across 70 global exchanges. The Morningstar feed is live: NAVs settle by end of business; prices on listed instruments refresh intraday. You're not modelling a portfolio against last Friday's data on a Tuesday afternoon.
And we look through. When a client holds a multi-asset fund, the analytics decompose it to the underlying positions — the actual constituent holdings, not the fund's stated style. That's a quietly important detail. Two Defensive funds with the same Morningstar style box can have wildly different real allocations. The look-through view shows you which is which and how that interacts with the rest of the portfolio you're constructing.
What you can do with it
- Compare portfolios. Side-by-side allocation, performance, risk and cost. Build a "current" against a "proposed" view and the deltas surface automatically.
- Stress test. Drop a 2008-style equity drawdown or a 2022-style fixed-income shock onto the portfolio. See what happens to allocation, drawdown and recovery.
- Map to client objectives. Tie the modelled portfolio back to the risk and capacity-for-loss scores from the risk assessment stage. The suitability narrative writes itself.
- Build branded reports. Export a 6-page summary or a 20-page proposal in your firm's colours and logo, with the analytics rendered as charts your clients can actually parse.
- Save anonymously or against the client. Run "what-if" portfolios without touching the client record. Save them as models and reuse across your book.
Bringing your client portfolios in
Upload a clean CSV at portfolio level, push holdings via our REST endpoints, or build a portfolio from scratch in the platform. Whichever route you take, the look-through and Morningstar data layer on top is identical. Deeper CRM integrations are on the roadmap; we'll publish dates as they firm up.
Methodology — what's behind every number
Returns are time-weighted, computed from total-return prices with dividends reinvested. Risk metrics use rolling 36-month windows where the data supports it; where a fund is too new for a clean 36-month series, we show a confidence flag rather than extrapolating to a number that looks more solid than it is. Asset allocation uses Morningstar's look-through dataset where available. ESG scores come from Morningstar Sustainalytics. Every analytic has a source and a refresh cadence — the full set lives on our methodology page.
Where this fits the pipeline
Portfolio analysis is the middle of the lead-to-proposal pipeline. It pulls from the digital fact-find (the client objectives, the timescale, the constraints) and feeds the proposal builder (the analytics, the narrative, the branded report). Used standalone it's a better analytics tool than most. Used as part of the pipeline it's the bit of the workflow where the platform earns its keep.
See the analytics on your own portfolios
Run one of your real client portfolios through the engine. Look-through allocation, risk metrics, the branded report — your data, our analytics, no commitment.