How do we set up Finster AI Screener for our coverage universe and save screens/watchlists for the desk?

Most front-office teams don’t need another screener; they need one that actually matches how the desk thinks about coverage, catalysts, and risk. Finster AI Screener is built for that reality: it lets you define a precise coverage universe, layer in both quantitative filters and event-driven context, and then save those views as reusable screens and watchlists the whole desk can rely on.

Below is a practical, workflow-first guide to setting up Finster AI Screener for your coverage universe and making sure saved screens and watchlists actually stick in day-to-day use.

If you don’t have Screener enabled yet, you can request access here: Get Started

1. Clarify what “coverage universe” means for your desk

Before you touch settings, get clear on how your team defines coverage. In practice, that usually means one or more of:

An index or benchmark (e.g., S&P 500, STOXX 600, sector indices)
Sector / industry mandates (e.g., US SMID tech, European financials, global energy)
Strategy or product lens (e.g., high-yield credit, growth at reasonable price, infra debt)
House lists (e.g., focus list, restricted list, must-know names for your sector pod)
Portfolio / book-level holdings (e.g., current positions plus realistic bench ideas)

Finster AI Screener is designed to flex across all of these. You can:

Filter by index or sector to mirror formal coverage
Upload or construct custom lists to reflect how your actual book is run
Save those parameters so the desk isn’t rebuilding the universe from scratch every time

Have this mental model ready—it will map directly to how you configure screens and watchlists.

2. Set up your base coverage universe in Screener

Once you’re in Screener, your first step is to build a base screen that mirrors your core coverage universe. Think of this as the “canvas” every more complex screen sits on.

2.1 Filter by index, sector, and geography

Start with the structural filters that never change for your desk:

Index filters:
Use the index dropdown or filter to limit to names in your benchmark (e.g., S&P 500, Russell 2000, FTSE 100). This keeps Screener aligned with how performance and risk are measured internally.
Sector / industry filters:
Narrow to GICS/sector tags that match your mandate (e.g., Info Tech, Industrials, Financials). This is particularly important for sector teams and pod structures.
Geography filters:
If you’re region-specific (e.g., Europe-only, APAC ex-Japan), set that at the base screen level. It removes noise and keeps alerts relevant.

This combination gets you a living, updated list of names that reflect formal coverage, not just “the entire universe”.

2.2 Add house rules: liquidity, size, and investability

Next, layer in firm-specific constraints so Screener only shows realistic ideas:

Market cap floors/ceilings – to exclude microcaps or mega caps outside mandate
Liquidity constraints – average daily volume thresholds to keep screens tradable
Listing venue / currency – to align with mandate and hedging preferences

Set these once in your base coverage universe so every saved screen built on top inherits the same investability logic.

2.3 Build custom coverage using watchlists

If your coverage is defined more by house lists or portfolios than formal mandates:

Upload or create a watchlist that matches:
- Your sector pod’s coverage list
- Your current portfolio or book
- A “bench” list of stocks you follow closely
Use this list as the starting universe for subsequent screens (e.g., “only show names in Watchlist: US SMID Tech Coverage”).

This is how you shift Screener from generic wide-net screening to coverage-aware searching that reflects how your desk actually works.

3. Combine quantitative filters with qualitative search

Traditional screening stops at metrics. Finster AI Screener is built to combine metrics and meaning—so you can see both who fits your numbers and who sits on the right (or wrong) side of key events.

3.1 Start with hard filters: valuation, balance sheet, and growth

Define the parameters that matter to your strategy:

Valuation:
P/E, EV/EBITDA, P/B, FCF yield bands, relative to sector or index
Balance sheet & credit:
Leverage ratios, interest coverage, ratings, maturity walls (for credit teams)
Growth and margins:
Revenue growth bands, margin levels, margin trajectory

Apply these in Screener to reduce the universe to a realistic working set—names that look sensible on paper before you add context.

3.2 Add event-driven context via qualitative search

This is where Screener breaks from traditional tools. You can layer natural-language queries over your filtered universe to capture the events that actually move markets:

Examples:

“Recent guidance cuts tied to demand softness in Europe”
“Management commentary on margin pressure from wage inflation”
“Disclosed covenant amendments or liquidity concerns in last 2 quarters”
“Announced but not closed M&A with integration risk flagged on the call”

Under the hood, Finster pulls from filings, earnings transcripts, IR materials, and premium datasets to surface cited, auditable passages that match your query for each name in your coverage universe.

The result: a screen that doesn’t just say “cheap, high growth” but “cheap, high growth, and has just lowered guidance due to channel inventory—per last call, here’s the exact quote”.

4. Save screens so the desk can reuse them

Once you’ve configured your base coverage and layered in quantitative + qualitative filters, save it as a screen. This is how you turn “one-off analysis” into a reusable desk asset.

4.1 When to save a screen

Save a screen whenever:

The structure is something you’ll revisit (e.g., “US SMID Tech – earnings downgrades”, “EU Banks – NII pressure screens”)
It aligns with a recurring workflow:
- Earnings season prep
- Monthly idea reviews
- Risk/hedge checks
- Thematic work (AI exposure, reshoring, regulation-driven screens)

4.2 How saved screens behave in practice

Saved screens in Finster AI Screener:

Auto-refresh against latest data – as filings, transcripts, and datasets update, the same logic runs on a fresher universe
Maintain your base coverage logic – sector/index/house list constraints stay intact so you’re never screening the wrong universe
Stay transparent and auditable – you can always see the filters and queries that define the screen; no black-box behavior

Use clear, desk-specific naming conventions (e.g., US_SMID_Tech_Earnings_Watch, HY_Energy_Downgrade_Risk) so anyone on the desk can understand what each saved screen is for.

5. Build and manage watchlists for day-to-day desk use

Watchlists are your way of telling Finster: “These names matter to us regardless of screens. Watch them like a hawk.”

5.1 Types of watchlists that work well

Most teams benefit from a few standard watchlists:

Core coverage list – all names you’re responsible for, regardless of position
Active book watchlist – current positions and key hedges
Conviction / focus list – names likely to feature in pitches or IC
Monitoring list – names with brewing risk (guidance cuts, leverage concerns, regulatory exposure)

Create these once and treat them as durable desk assets.

5.2 Using watchlists inside Screener

You can use watchlists in three ways:

As the starting universe
- “Only show names in ‘EU Financials Coverage’ watchlist that…”
- Perfect for desk-specific workflows.
As a filter on top of a broader screen
- Screen a sector broadly, then intersect with a watchlist to see “our names inside the broader theme”.
For ongoing monitoring and alerts (where configured)
- Run the same screen against a watchlist periodically (e.g., weekly) to catch:
  - Fresh guidance commentary
  - New risk disclosures
  - Upward/downward revisions

The key is consistency: when watchlists map cleanly to how the desk thinks, Screener feels native to the way you already work.

6. Make screens and watchlists shareable desk infrastructure

Finster is built for team workflows, not individual sandboxes. Once you have a few high-value screens and watchlists in place, the next step is to make them shared infrastructure for the desk.

6.1 Standardize naming and ownership

Use a consistent naming pattern:
Desk / Region – Mandate – Purpose
Examples:
- US_Equity_LongOnly – Core – Earnings_Season_Prep
- HY_Credit – Energy – Downgrade_Monitor
Assign an owner for each critical screen/watchlist (usually a senior analyst or desk head). They are responsible for:
- Periodically validating filters still match mandate
- Updating for changes (benchmark switches, sector handoffs, new constraints)

6.2 Bake screens into existing workflows

Make Screener the first step in workflows you already run:

Earnings prep:
- Start from your coverage watchlist
- Run an “earnings changes / guidance / controversy” screen
- Use results to prioritize reading and client prep
Idea generation:
- Use a “cheap & improving fundamentals” screen across your coverage universe
- Validate outputs via citations directly in filings and transcripts
Risk review:
- Run a “liquidity / leverage / negative commentary” screen over your active book watchlist
- Export or copy outputs into internal risk packs as needed, with sources cited

When Screener is wired into actual desk rituals, screens and watchlists stop being static lists and become living risk and idea tools.

7. Why Screener is safe to scale across the desk

Finance teams are rightly skeptical of generic AI in screening—especially when it’s unclear where a flag or “insight” came from. Screener is designed to be safe in regulated, high-stakes environments:

Every insight cited, every source auditable
- Qualitative hits link back to specific sentences in filings, transcripts, or IR materials.
- Numbers can be traced to table cells in primary sources or licensed data.
No black-box guessing
- When Finster doesn’t have the data, it returns “no answer” rather than hallucinating.
- That’s critical when a missed covenant, rating action, or guidance change actually matters.
Enterprise guardrails by design
- SOC 2 posture, Zero Trust security model, encryption at rest and in transit, audit logging, SAML SSO, and SCIM support.
- Flexible deployment options (including single-tenant / VPC) and a strict “no training on your data” stance.

That’s what makes Screener usable not just by a single power user, but across an entire desk or platform.

Putting it all together

To set up Finster AI Screener for your coverage universe and save screens/watchlists for the desk:

Define the universe – Map your benchmark, sectors, geographies, and house lists into a base coverage screen.
Impose investability – Add liquidity, size, and mandate constraints so results are actually tradable.
Combine metrics with meaning – Layer quantitative filters with qualitative, event-driven search across filings and transcripts.
Save and standardize – Turn the most useful configurations into named screens and watchlists with clear owners.
Wire into workflows – Make those screens the first step in earnings prep, idea reviews, and risk checks.
Leverage traceability – Use citations to validate every number, statement, and “hit” before it reaches a client deck or IC memo.

When you design Screener around how your desk actually runs, you move from “another tool” to a coverage-aware analyst that keeps working in the background at deal speed.

Next Step

If you want help mapping your current coverage, portfolios, and workflows into Finster AI Screener, you can see it live with your use cases:

Get Started