AI Adaptation Research Report — SSNC (SS&C Technologies Holdings Inc) · BlackSwan constituent

EventTrader research desk · generated 2026-11-06 03:37 UTC · report ai-adapt-ssnc-20261106 · narrative: AI analyst, checked against the evidence pack

1. Verdict

• Short book, because the filing is silent on AI. The 2026-11-06 scoring run places SS&C Technologies Holdings Inc (SSNC) in the BlackSwan short book, the one-line reason being that the anchor filing contains no sentences about artificial intelligence at all [S5].
• Anchor filing: the 10-Q filed 2026-07-30 for the quarter ended 2026-06-30 [S1].
• Adoption level: "absent" — a final level of 0, with no lexical signal and no model read on record [S5].
• Score and rank: an AI Adaptation Score of 9.397, which sits at the 6.5th percentile of the 6,511-name universe and the 1.0th percentile of the 585-name software sector [S5].
• What would move it: a later filing that actually discusses AI deployment, investment or outcomes in substance, and/or a model read that finds grounded evidence the keyword pass missed [S5].

2. The company

SSNC is SS&C Technologies Holdings Inc, a filer registered with the SEC under CIK 1402436 [S4]. It is classified under SIC code 7372, "Services-Prepackaged Software," and the scoring run groups it in the software sector [S5]. Its shares trade on Nasdaq [S4]. The document reviewed for this report is the company's Form 10-Q, filed 2026-07-30 for the period ending 2026-06-30, under accession 0001193125-26-326105 [S1][S2]. The evidence pack does not describe SSNC's business lines, products or customers beyond this filer identity and classification; it states only what is recorded above.

3. What the filing says about AI

The evidence pack contains no AI sentence from the anchor filing. The feature set drawn from the 10-Q reports 5,993 words of substance and zero AI sentences, with zero substance hits and zero risk hits (ai_sentences: 0, hits_substance: 0, hits_risk: 0) [S5]. Because the pack carries no verbatim AI sentence from the filing, there is nothing here to quote. In the words of the desk's convention: the filing reviewed does not state anything about artificial intelligence that the scoring pass detected [S1][S5].

4. The AI Adaptation Score

The adoption level is "absent," level 0, with a lexical component of 0 [S5]. There is no model read: model_status is "none," so there is no confidence figure, no credibility figure and no sub-scores to report [S5]. The grounded-quotes list is empty [S5].

The AI Adaptation Score itself is 9.397, with a margin of 21.112, and the run assigns SSNC to the "non_adopter" cluster [S5]. Its components are: level 0.0, greenfield 0.0, credibility 0.0, trajectory 5.886 and investment 3.511 [S5]. In other words, the entire score is carried by the trajectory and investment components; the level, greenfield and credibility components each contribute zero [S5]. On the percentile scales, SSNC sits at the 6.5th percentile across the 6,511-company universe and at the 1.0th percentile among the 585 software companies (SIC 7370–7379) [S5]. These are given values from the scoring run; this report does not recompute them.

5. Trajectory

The previous periodic report was a 10-Q filed 2026-04-30, accession 0001193125-26-197201 [S3]. That filing was also scored at level 0, "absent," with zero AI sentences and a substance density of 0.0 [S5]. The anchor 10-Q repeats the same reading: level 0, "absent," zero AI sentences [S5]. The level therefore did not move between the two periods — it stayed at "absent" across both quarters reviewed [S3][S5].

6. Recent developments

The evidence pack carries no headlines. Its headlines block is marked "empty" over a 45-day window, with no items [S5]. There are accordingly no recent developments to list here. The price feed records a quote of 78.07 for SSNC, flagged as stale [S6].

7. What would change the verdict

Moving SSNC out of the short book would require evidence the current pack does not contain. Concretely, a later filing would have to contain substantive AI sentences — language describing AI that is deployed, invested in, built natively, or tied to outcomes — rather than the zero AI sentences the two most recent 10-Qs show [S5]. A model read, which is currently absent (model_status "none"), could also change the picture if it surfaced grounded quotes and credible sub-scores that the lexical pass did not capture [S5]. Lifting the level, greenfield or credibility components above their current zero would raise the score directly, since those three now contribute nothing [S5]. This report makes no forecast that any such change will occur; it states only the conditions the method would read differently.

8. Risks and caveats

A filing-based score can only see what is written in the document it reads. The pass over this 10-Q counted 5,993 words and found no AI language [S5]; a keyword and sentence count cannot see AI work a company is doing but chooses not to disclose, nor can it weigh engineering embedded in products that the filing never names. An "absent" level is a statement about the filing's text, not a claim about the company's internal activity. The absence of a model read (model_status "none") means no second, semantic opinion has been applied to confirm or soften the lexical zero [S5]. The headlines block being empty removes an external cross-check for this window [S5], and the price quote is flagged stale [S6]. The verdict would be falsified if the anchor filing in fact contains AI disclosure the pass missed, or if a future read recovers grounded AI evidence — in which case the level and components should be re-examined against the method on the fund page [S5].

9. Watch list

Three things to watch. First, the next periodic filing from SSNC, which would succeed the anchor 10-Q filed 2026-07-30 and can be tracked through EDGAR company submissions for CIK 1402436 [S1][S4]. Second, the model read, which is currently "none" — a pending or completed read would add sub-scores, confidence and credibility that the present score lacks [S5]. Third, the next EventTrader scoring run, which would refresh the AI Adaptation Score, the cluster assignment and the percentile ranks against the AMF-BLACKSWAN book [S5].

Place in the book

• Rank 8 of 10 in AMF-BLACKSWAN (Swan Composite v1.1.0, scoring run 2026-11-06): the book holds the lowest composites [S5].
• Composite: 0.50 × 9.4 (AAS) + 0.25 × 50.0 (story) + 0.25 × 71.5 (market) = 35.1 [S5].
• Market verdict 71.5: over the last 90 days SSNC rose more and fell less than the software universe's median daily return (down-capture 0.76, up-capture 1.62, L = 0.86; 33 down / 19 up days) — the Failure-To-Adapt fund's selection signal, 50 = moves with the software universe's median daily return [S5].
• AI Story Score 50.0: no AI story or a neutral one in the AI stories written about the company [S5].
• Weight: rank factor 1.22 (rank 8 of 10) × story factor 1.00 × market factor 1.00, normalised across the book and clamped to 5–20% → 7.8% [S5].

Sources

• S1 — SSNC 10-Q filed 2026-07-30 — SEC primary document (the anchor filing the score reads) — https://www.sec.gov/Archives/edgar/data/1402436/000119312526326105/ssnc-20260630.htm
• S2 — EDGAR filing index for accession 0001193125-26-326105 — https://www.sec.gov/Archives/edgar/data/1402436/000119312526326105/
• S3 — SSNC 10-Q filed 2026-04-30 — the previous periodic report (trajectory) — https://www.sec.gov/Archives/edgar/data/1402436/000119312526197201/
• S4 — SEC EDGAR company submissions — SS&C Technologies Holdings Inc (CIK 1402436) — https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=1402436
• S5 — EventTrader AI Adaptation Score, scoring run 2026-11-06 — the AMF-BLACKSWAN fund page (method, composition) — https://cymetica.com/fund-performance/AMF-BLACKSWAN
• S6 — EventTrader real-price feed — SSNC quote — https://cymetica.com/api/v1/prices/SSNC

Method and disclaimer

The AI Adaptation Score reads each company's own periodic SEC reports (10-K, 10-Q, 20-F, 40-F): deterministic features (AI sentences by section, proprietary-model, deployment, outcome, investment and vendor language, boilerplate and negation excluded) set an adoption level on a 0–4 rubric; a model read of the filing's AI sentences confirms the level and scores credibility and greenfield (the business built with AI from the ground up rather than retrofitted); the score combines level, greenfield, credibility, trajectory against the previous report and investment, measured against the company's sector, with greenfield carrying the highest reward. The books are composed by Swan Composite v1.1.0: each company's composite is 50% AI Adaptation Score + 25% AI Story Score + 25% market verdict — the AI Story Score is the sentiment of the AI stories written about it, the belief network of companies named in the same stories and the price reaction to those stories (no story scores neutral); the market verdict is the Failure-To-Adapt fund's selection signal, the signed down/up capture ratio of the stock against the software universe's median return over 90 days (a stock that falls more and rises less than its peers scores below 50). AMF-BLACKSWAN holds the ten lowest composites that pass the liquidity screen and the new-listing gate and AMF-WHITESWAN the ten highest, weighted by conviction (rank, story agreement and market agreement, each leg 5–20%), recomposed on every scoring run. Every quote in this report is the filing's text verbatim; every factual sentence names its source; a source the platform could not reach is reported as missing, never filled in.

This report is information, not investment advice. Figures come from the cited sources as of their dates. Nothing here is a recommendation to buy, sell or hold any asset.