The SEC’s 13F filing database has existed for decades. Every quarter, thousands of institutional managers disclose their long positions in ETFs, closed-end funds, BDCs, and listed equities — and that data has been publicly available the entire time. So why hasn’t it been truly useful? Because public has never meant accessible, and accessible has never meant intelligent.
Dakota changed both of those things. We built the most comprehensive, accurately normalized 13F dataset in the market — and paired it with the only RIA firm and contact intelligence database that can tell you not just what an institution owns, but who they are and who to call. Then we layered AI on top, so anyone can ask questions in plain English and get answers in seconds.
Here are the ten most powerful use cases — who benefits, what the data alone gives them, and what becomes possible the moment AI enters the picture.
The 10 Use Cases
Use Case #1: ETF Distribution & Wholesaler Enablement
Who Benefits: ETF Issuers · Asset Managers · Wholesalers Covering the RIA Channel
Value from the Data: Know exactly which RIAs hold your ETF, the size of their position, how it has changed quarter over quarter, and which competing ETFs they hold alongside yours. Walk into every RIA conversation fully briefed, with no manual research required.
Value from the AI Layer: “Show me all RIAs in the Mid-Atlantic that hold our ETF, have grown their position two consecutive quarters, and have AUM over $500M — and give me the right contact at each firm.”
What used to take a research analyst a full day returns in ten seconds, pre-prioritized for next week’s call list.
Use Case #2: Competitive Intelligence for ETF Issuers
Who Benefits: Product Strategy · Marketing Leadership · Distribution Heads at ETF Companies
Value from the Data: See which RIAs hold your competitors’ ETFs but not yours — filtered by AUM, geography, investment mandate, and channel. Identify exactly where you are losing shelf space and to whom, backed by actual SEC filing data rather than anecdote or survey.
Value from the AI Layer: “Which RIAs currently hold the iShares equivalent of our fund but not ours — and what is the average position size at those firms?”
Instant competitive displacement targeting that previously required weeks of analyst work. Your distribution team walks in knowing exactly who to convert and why.
Use Case #3: Closed-End Fund & BDC Investor Relations
Who Benefits: IR Teams · Distribution Professionals at Closed-End Fund and BDC Sponsors
Value from the Data: Track your full institutional holder base with complete identity — not just filing entity names, but the actual RIA firms, their AUM, their mandate, and the humans responsible for the allocation. Monitor new entrants, position growth, and exits every quarter.
Value from the AI Layer: “Which RIAs initiated a position in our BDC last quarter that we have never spoken to before — and who is the portfolio manager at each firm?”
Quarterly filings become a live new business pipeline with zero manual work. IR teams spend their time on relationships, not spreadsheets.
Use Case #4: RIA Prospecting for Any Asset Manager
Who Benefits: Any Asset Manager · Fund Company · Alternatives Sponsor Targeting the RIA Channel
Value from the Data: 13F data reveals an RIA’s actual investment behavior — not what they say they do, but what they actually own. Dakota’s contact layer tells you who to call. This is revealed preference data at institutional scale, paired with the intelligence to act on it immediately.
Value from the AI Layer: “Find me RIAs with over $1B in AUM that own at least three alternative income vehicles — BDCs, closed-end credit funds, or senior loan ETFs — but have no exposure to private credit funds in our database.”
A hyper-targeted prospect list built from behavioral data in seconds. No cold calling. No guessing. Just a direct path to the right firms.
Use Case #5: RIA Benchmarking & Peer Positioning Analysis
Who Benefits: RIAs Themselves · Investment Consultants · Model Portfolio Providers
Value from the Data: An RIA can see how their own ETF and listed alternatives holdings compare to peer firms of similar size, channel, and mandate. What are the most commonly held funds among firms like theirs? Where are they over- or underweight relative to their cohort?
Value from the AI Layer: “How does our ETF allocation compare to other independent RIAs with $500M–$1B in AUM, and what funds are most commonly held by firms like ours that we don’t currently own?”
Peer benchmarking that used to require a consultant engagement is now a thirty-second conversation. RIAs gain genuine insight into how they are positioned relative to the market.
Use Case #6: Fund Launch & Product Development Research
Who Benefits: Product Teams at Asset Managers · ETF Strategists · Alternatives Product Developers
Value from the Data: Before launching a product, understand actual RIA channel appetite from revealed behavior. Which categories are seeing consistent position growth quarter over quarter? Which RIA segments are most actively adding exposure? What does the holder base of comparable products actually look like?
Value from the AI Layer: “What is the growth trajectory of RIA ownership in senior secured loan ETFs over the last eight quarters, and which RIA segments are driving the most new adoption?”
Market research drawn directly from real institutional behavior — not surveys, not focus groups. Product decisions get made with conviction, not guesswork.
Use Case #7: M&A and Acquisition Due Diligence on RIAs
Who Benefits: RIA Acquirers · Private Equity Firms Targeting RIA Rollups · Investment Banks
Value from the Data: When evaluating an RIA acquisition target, 13F data provides an SEC-verified, independent window into the firm’s actual investment behavior — product preferences, manager relationships, positioning consistency over time. A factual cross-check against whatever the target tells you in a data room.
Value from the AI Layer: “Pull the last eight quarters of 13F filings for XYZ Wealth Management and summarize how their ETF and listed alternatives holdings have evolved — and flag any material shifts in positioning.”
Instant independent due diligence on a target’s investment behavior before a single conversation takes place. A genuine edge in a competitive deal process.
Use Case #8: Capital Introduction & Prime Brokerage
Who Benefits: Prime Brokerage Teams · Capital Introduction Professionals · Hedge Fund IR
Value from the Data: Identify which RIAs are actively participating in listed alternatives and BDCs — a strong behavioral proxy for sophistication and appetite for less liquid, higher-yielding strategies. These are the natural audiences for introductions to hedge funds and private vehicles.
Value from the AI Layer: “Which RIAs with over $2B in AUM have the highest concentration in BDCs and closed-end alternatives and have been growing those positions consistently — and who is the alternatives allocator at each firm?”
A capital introduction list built from behavioral data, not a cold rolodex. Every introduction is warm, relevant, and backed by evidence.
Use Case #9: Institutional Flow Research & Market Analysis
Who Benefits: Financial Journalists · Sell-Side Analysts · Independent Research Firms
Value from the Data: Track institutional sentiment toward specific ETFs, fund categories, or market sectors across the entire RIA channel — a genuine signal of where sophisticated money is moving, backed by SEC filings rather than surveys or anecdote. The most credible flow data available.
Value from the AI Layer: “Has RIA ownership of gold ETFs increased or decreased over the last four quarters, and which AUM segments are driving the change?”
Research-grade institutional flow analysis in plain language, available to anyone — not just quantitative analysts with database infrastructure. A new category of market intelligence, fully democratized.
Use Case #10: CRM Enrichment & Sales Intelligence for Distribution Teams
Who Benefits: Heads of Distribution · Sales Operations · CRM Administrators at Any Firm Selling to RIAs
Value from the Data: Enrich every RIA record in your CRM with live 13F data — what they currently own, what they recently added or trimmed, and how their behavior compares to peers. Your CRM stops being a contact book and becomes a living picture of each client’s actual investment activity.
Value from the AI Layer: “Which of our existing RIA clients have trimmed their position in our fund two quarters in a row — and what else have they been buying in that same category?”
Churn signals and competitive displacement detected automatically, before a relationship is lost. Your distribution team stops reacting and starts anticipating.
The Unifying Insight: Data Without Identity Is Just Noise.
In every one of these use cases, the same dynamic is at work. 13F data reveals what institutions actually own. Dakota’s RIA intelligence layer gives that data identity — turning filing entities into real firms with real people and real contact information. And AI makes all of it accessible to anyone, without requiring a data analyst, a SQL query, or a research team.
The data alone is raw material. The RIA layer gives it identity. AI gives it a voice. No one else has all three — and that combination is not something a competitor can replicate overnight.
13F Data: Normalized, continuously updated SEC filing history
RIA Identity: The firm, the AUM, the mandate, the people
AI Intelligence: Ask any question in plain English, get answers in seconds
See Dakota’s 13F Intelligence Platform in Action
The most comprehensive 13F dataset in the market, paired with the only RIA contact intelligence that makes it actionable — now with AI built in.
Request a demo here!
