Portfolio Analytics Deep Dive
The Portfolio Analytics section (Analytics → Portfolio) shows aggregate metrics across your entire client book — not individual client data, but the combined picture of your practice's banking systems.
Aggregate Client Book Metrics
The summary row at the top of the Portfolio view shows totals and averages across all clients in your practice:
| Metric | Description | |--------|-------------| | Total Cash Value | Sum of most recent CV snapshots across all clients | | Total Loan Balance | Sum of all active policy loan balances | | Net System Position | Total CV minus total loan balances | | Average LTV | Mean loan-to-value ratio across clients with active loans | | Policies Tracked | Total number of active policies across your practice | | Active Deployments | Total number of active deployment records |
These aggregates use each client's most recent snapshot data. Clients with outdated snapshots (more than 90 days old) are flagged in the data freshness indicator. Stale data from one client affects the aggregate totals.
LTV Distribution
The LTV distribution chart shows a histogram of loan-to-value ratios across your client base. This is one of the most useful views in portfolio analytics because it shows the shape of your practice's capital utilization pattern.
How to read it:
- The X-axis shows LTV in 10% bands (0–10%, 10–20%, etc.)
- The Y-axis shows count of clients in each band
- The distribution tells you whether your practice skews toward clients who are early in capitalization, actively deploying capital, or maintaining high utilization
Common patterns:
| Distribution Shape | What It Suggests | |-------------------|-----------------| | Concentrated at 0–20% | Client book is mostly in capitalization phase; limited active deployment | | Spread across 20–70% | Mix of capitalization and active banking — typical of a mature practice | | Concentrated at 70%+ | High average utilization; worth monitoring for clients approaching carrier limits |
There is no target LTV distribution — the right shape depends entirely on your client base, their policies' ages, and their individual banking system goals. This view is for pattern recognition, not performance evaluation.
Capital Velocity Analysis
Capital velocity measures how many times clients have cycled their capital — deployed it, received a return, and redeployed. The Portfolio Analytics view shows velocity distribution across your practice:
- Mean velocity — average velocity score across clients with active assets
- Velocity histogram — distribution of velocity scores
- Trend — whether mean velocity is rising or falling over the selected period
A rising mean velocity across your practice suggests clients are becoming more active in using their banking systems. A declining mean may reflect clients who are in a capitalization phase with fewer active assets — this is normal for practices that are growing their client base with newer clients.
Snapshot Freshness
The data freshness panel shows how current your clients' data is:
| Freshness Band | Count | |----------------|-------| | Updated in last 30 days | X clients | | 31–90 days | X clients | | 91–180 days | X clients | | 180+ days | X clients |
High counts in the 91+ day bands are the most actionable signal from this view. Each client with stale data is both a data quality issue and a potential touchpoint opportunity — they haven't logged in to update their snapshot, which often means they haven't been thinking about their banking system.
Sort the stale data list by "days since last snapshot" descending to prioritize which clients to reach out to first. Clients with data that's 180+ days old should be the top priority.
Exporting Portfolio Data
The Portfolio Analytics view exports as a CSV that includes one row per client with their current aggregate metrics. This is useful for offline analysis or for sharing a practice snapshot in a report format.
Go to Analytics → Portfolio → Export CSV.
The export reflects the current snapshot data for each client — it is not a historical time series. For historical trend data, use the individual client detail views.