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Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

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Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#31

Post by kbennatti »

kbennatti wrote: post #29
kbennatti wrote: post #28

Earlier quoted context omitted.

Yes, it did. BUT here's the thing -> Nikola was first a SPAC and by the time it filed its first filing as Nikola, the Hidenburg report was already out so its not a true example of our algorithms preceding short reports. Our algos did beat Hidenburg to the punch on a number of other companies though. A bit outdated but check this out - https://bedrock.substack.com/p/bedrock-ai-vs-activist-shorts

Nikola red flags for you! (all algorithmic) 1. "For example, in September 2020, our founder and former executive chairman, Trevor R. Milton, stepped down from his positions with us." 2. "During the fourth quarter of 2020, the Company ceased operations related to the Powersports business unit in order to focus on the Company's primary mission of commercial production of semi-trucks and construction of hydrogen fueling…

just a sample

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#32

Post by scottydelta »

nodesocket wrote: post #17
scottydelta wrote: post #2

Hey guys, congrats on the Launch. Is there any API to get the metrics you guys calculate on SEC Filings? I recently launched https://quantale.io which is a web-based Bloomberg Terminal alternative and we monitor SEC filings in real-time to show them to users[1]. It would be great to show additional data related to the SEC filings if there was an API. [1] https://quantale.io/dashboard/sec-filings

How are you different than the native macOS WeBull application? WeBull comes the closest I have seen to a Bloomberg terminal.

WeBull only provides financial and newsmedia data about the stocks but Quantale is the first of it's kind to provide not only Financial and newsmedia data but also real-time data from SEC, Reddit, and Twitter.

Along with that, additional features include:

- Top trending stocks from the internet in real-time

- Sentiment of the discussions using a pytorch model.

- Ability to save posts(reddit, twitter, news headline, sec filings)

- Ability to create watchlist to watch and monitor a group of tickers like SPACs.

Features in Roadmap:

- Alerts on change in the activity of stocks

- Level 2 Data

- Options Data

- Brokerage so that users can trade directly from Quantale

Please try it out at https://quantale.io and any feedback is appreciated. Feel free to reach me at vikash@quantale.io

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#33

Post by piesauce »

DSingularity wrote: post #27
kbennatti wrote: post #18

Earlier quoted context omitted.

We don't sell to filers. Ever. Got to protect against conflicts of interest. That's one of the reasons we don't have a true free version of the product. That said, we're using language models so replacing words with synonyms won't evade the model as long as its expressing the same thing.

Do you have any deeper protections than simply not selling to filers? It doesn’t seem so hard for a motivated filer to circumvent by using friendly hedgefunds to lend their licenses.

We constantly retrain our red flag models and they are tested for robustness (whichever way the company decides to express the existence of a risk, like say an investigation, we ensure that the models pick it up)

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#34

Post by naturalauction »

kbennatti wrote: post #6
c3pa wrote: post #3

> Our algorithms picked up these red flags and more, and assessed Sino-Forest as high risk when we ran our models on the company’s historical filings. When you're backtesting your models, how do you distinguish between novel fraud that the industry is _now_ aware of vs. fraud that was visible but ignored -- if your model has learned _from_ Sino-forest, how do you know it would have caught Sino-Forest at the time? > F…

Great q. Sino-Forest is an out-of-sample test so our models didn't technically "learn" from it. That said, very valid comment. Historical testing only goes so far. Assessing whether our algorithms work in deployment has been cool. Check out some of our live, in deployment examples here - https://bedrock.substack.com/p/bedrock-ai-vs-activist-shorts

>https://bedrock.substack.com/p/bedrock-ai-vs-activist-shorts

How often are companies rated with a risk factor this high. As in does a risk factor in the 80s mean that fraud is extremely likely or is it just notifying humans that this filing might be worth reading over with a fine-toothed comb.

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#35

Post by MattGaiser »

Former equity analyst intern and now a software engineer here. My Dad also works in the investment world (and is a CPA and a developer coincidentally) and after Sino Forest happened, he wanted someone to parse annual reports and AIFs create a "weasel word index." Ever thought of doing that?

Basically rank companies in estimated honesty by the language they choose to use.

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#36

Post by Seabiscuit »

Interesting site. I currently work at a hedge fund, but have a small dose of NLP in my academic background, so it's always interesting to see concepts like this come out.

Two questions: - Are you using EDGAR's 'Facts' function? It seems to make SEC Filings a lot more like structured text than they have been previously, but I haven't seen really convincing tools developed to use it yet

- How/do you ever see yourself interfacing with similar 'red flag' screening tools that just work on the numerical side i.e. accounting ratios ?

Also, you've got a grammatical error on your Values and Vision page. Normally I wouldn't comment to point that kind of thing out, but for an NLP startup it seems more appropriate ('its volume' not 'it's volume')!

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#37

Post by kbennatti »

MattGaiser wrote: post #35

Former equity analyst intern and now a software engineer here. My Dad also works in the investment world (and is a CPA and a developer coincidentally) and after Sino Forest happened, he wanted someone to parse annual reports and AIFs create a "weasel word index." Ever thought of doing that? Basically rank companies in estimated honesty by the language they choose to use.

Aw cool! Can I hang out with your Dad? ;) We do pick up on overly promotional/jargon-y language to some extent. For the most part, however, word lists haven't worked for us.

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#38

Post by kbennatti »

Seabiscuit wrote: post #36

Interesting site. I currently work at a hedge fund, but have a small dose of NLP in my academic background, so it's always interesting to see concepts like this come out. Two questions: - Are you using EDGAR's 'Facts' function? It seems to make SEC Filings a lot more like structured text than they have been previously, but I haven't seen really convincing tools developed to use it yet - How/do you ever see yourself i…

Thanks for website edit! Fixed.

We don't rely on XBRL for parsing. It's not very consistent/reliable and its mostly for numeric content. We've definitely considered integrating ratios both into our dashboard. It isn't a current priority because ratios are already well supported elsewhere.

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#39

Post by paisible »

kbennatti wrote: post #26
paisible wrote: post #19

Congrats on the launch guys! Fellow Canadian from Montreal here :) I'm curious, what tools / methodology did you follow to generate the high-quality labels, and how many different labels did you end generating? I'm also very curious whether you view the discovery and generation of new labels (and accompanying high-quality training datasets) as a continuing and core part of your development going forward?

Ooh I love MTL. That's the first place I lived in Canada. Great q. We used SEC enforcement actions related to fraud as our gold label (fairly common practice in academia). Really key thing here is that you need to be careful about what years you're using for training because if you include years that are too late in the fraud cycle, you end up with significant target leakage e.g. the filings we'll say, "we're being i…

Thanks for the quick answer! Follow-up around this as it's a space I'm actively working in: did you use or build any tools for the labeling process, or was it Excel? :D Also, do you ultimately see/position your solution as an AI-powered exploration tool that allows humans to derive better insights, faster (but where the NLP side of things is simply to assist in this discovery process), or do you see the models (and resulting flags) eventually being able to completely replace the human intuition?

Re: Launch HN: Bedrock AI (YC S21) – Using ML to identify red flags in SEC filings

#40

Post by ZeroCool2u »

I've worked with 10-K's and 8-K's extensively for the purposes of using them for NLP. This is extremely arduous work and a clear winner in terms of profitable ideas, so kudos to the team for the launch, this is really impressive.

Perhaps this is giving a bit too much away in terms of the secret sauce, but would love if you could talk a bit about how you handle the wild disparities in the structure of the documents. Do you parse the XBRL?

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