90% of investors using alternative data are seeing a return on their investment

Learn how you can do the same

WEBINAR AIRED: NOVEMBER 8, 2017

Putting Alternative Data to Use

Ninety percent of asset managers and hedge funds who are using alternative data sets as part of their investment strategies say the use of this data is paying off by delivering hoped-for returns.

To get more insights on alternative data, watch this webinar on demand, featuring a panel of industry experts from Greenwich Associates, Dun & Bradstreet, and Liquidnet. They discuss key findings from a recently released paper on how asset managers and hedge funds are finding, using, and benefiting from alternative data sources.

Watch on demand to learn:

  • Why a significant number of asset managers and hedge funds plan to increase alternative data spending in 2018.
  • The reason today’s alternative data will only be alternative for so long.
  • How investors are finding new alternative data sets and what they are doing to take action on those findings.
  • The challenges investors face when using alternative data.
  • Steps you can take to better leverage alternative data in your organization.

Presented by:

Arcadia Data
StreamSets
Trifacta
Waterline Data

Transcript

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everybody I think we're ready to get started

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and pay personal

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thanks for joining and welcome to Credit Associates

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Market structure update we

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will be continuing our coverage of

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the alternative data space and

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more specifically we're going to look beyond the definition

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and categorization of alternative

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data and get more effectively putting that

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data into use managing

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director hair Greenwich Associates I'm

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responsible for the market structure and Technology

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practice and I'll be the host today

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I'm going to be joined by a

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great panel at panels going to be moderated

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by Kevin who's our head of research

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within the market structure and Technology

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practice is going to be joined by

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Paul last-minute who is the practice

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lead an advisor for financial

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services are at Arcadia data

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Adam Sussman head

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of Market structure and liquidity Partnerships

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at liquid man and biotic

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senior director Global alliances

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and great

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paddle I'm sure it's going

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to be very interesting in

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just a couple of housekeeping

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items if you're hearing an

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echo in your ears are ringing please

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check the audio settings make sure the telephone

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is selected so

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you're not getting duplicate audio

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feed coming through the

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presentation questions please

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feel free to type them in the dialog box will

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try to answer as many as we can during the webinar

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or certainly at the end when

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when time allows the Q&A if

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we don't get to them absolutely

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come back to you post

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the webinar in Iraq

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ban if you have additional questions

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after the webinar we're going to give you

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the contact details for the participants

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please feel free to reach out directly

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I think we also have a few polling questions in

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the webinar today so please feel

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free to provide input when

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when when they come up on Friday and

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then finally I'm as always encourage

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you to fill out the survey following the event

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always looking to improve and we certainly

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want to make sure we cover those

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areas and our future webinar that are

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most interest to you

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our clients and friends in the industry so

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before I turn it over to Kevin

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in the panel let me pick

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up a minute just to plug Granite Associates

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in the market structure practice in particular in

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the practice we here

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are focused on everything the changes

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in the ecosystem of institutional

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Financial Services whether that be changes

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and that how they

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may impact the market

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participants and those folks

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that glue the buy and sell side together differentiator

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in here tremendous amount of

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research with

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the market participant in general and

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this year I'm going to ask about three

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and a half million questions to 65,000

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Market participants on the

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phone is the basis of the

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data that then informed our analysis

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and opinion so we think we've

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got a great perspective and

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it's based on data and

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the market with

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that with that marketing blurb out of the way

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let's let's push forward into the end

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of the presentation today

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first

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day of talking about alternative

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data we are we

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are Awash in in Dade everyday

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see some of the components on

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the slide everyday with creating

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2 1/2 quintillion

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bytes of data so both posted

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on how many which quintillion and

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1802 that 2.5

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and you'll get through a quintillion start

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stacking up those Blu-ray disc and get the

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Eiffel Towers fall think

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of how much data that is that we create

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and then some specific examples from

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their Bank of Walmart

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near Walmart processing a

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million customer transactions every

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hour right literally

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every piece of media from

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around the world whether that be in

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print in radio

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was that be social and make that

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available in America

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I'm in does that for free amended

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amount of information V in there and

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look at the Facebook they're

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uploading over 400 million photos every

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day I have

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to have Twitter versus the New York Times Twitter

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today is going to post more

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words in their New York Times has printed

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in the last 50 years think

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about that for a fact and

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what that means is a tremendous

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business out there and you'll see that there

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are projections that this is going to gross I fold

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over the coming

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year it's a big business today it's

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going to be a much as we

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go forward and we think it's going to be

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a very

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important role in the investment on

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the investment decision making

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oh wait we try to make a very basic

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do you hear of the alternative alternative

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data ecosystem and

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who are the market participants there

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the least amount

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of data Originators and

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these are everyone from you may

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you may have seen traditional data

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originated those

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type of things it really has

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turned into a morph into anybody

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that has an exhaust from

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their day-to-day operations and

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another component

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of that ecosystem who are

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the providers of

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the Big Data platform those folks

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that can take the data in

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normalize it and make it applicable

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in useful for Market participants

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and I want that happens you need the subject

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matter experts those folks that not

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only can identify the the alternative

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data but

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understand what it means and how

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it impacts an investment decision

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and then it gets all the way around to the beneficiaries

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whether that be the asset manager is all

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the way down to individual

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investors like all of us here

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today and

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I'm trying to put together a bit of a an

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ecosystem view the

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intense Harrison to be exhausted

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because quite honestly I

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shut this down by probably

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80% to get the name on

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this flight the

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attention was really just a show where

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we think some of those categories

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are in the alternative ecosystem

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in in to show some of the names

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that are out here something you know

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right so

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you see Arcadia is in there but they're Bloomberg

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in fact that and CR another.

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& Bradstreet on here but you see

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also other than you maybe have

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never heard of and these are all

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very active names in the alternative date

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of space let's

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let's turn it over to our first question

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I think I first pull question is going to

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ask for the participants

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here we

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do you think you fit in

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that alternative data ecosystem

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thanks

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for getting us started and kind

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of like the same question

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Akai Kevin an audience thanks

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we're clearly

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a source of the

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state of it but you'd call hear a date originator

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Aaron we provide data

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and business intelligence on both public

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and private companies and have

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unique transaction data

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we also have proprietary scores

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are developed by around 11:16 most

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of which focused on the

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value of Trade Credit transactions

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payment behaviors of public and private companies

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information about business

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relationships businesses supply chain

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that information we found

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especially in the The Evolution

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here of alternative data has become

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valuable to other

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by sides ability to

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provide predictive signals within

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their algorithm so that's kind of how the data is

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used today Adam

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from liquid knots perspective where do you sit in this

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ecosystem Dad

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thanks Kevin liquid net

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you know being a broker-dealer and

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having a front-end interface

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that Services

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800 by

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side firms globally

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would sit somewhere between you

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know a beneficiary and a

[00:09:11.899]
in a big data provide

[00:09:15.899]
better we acquired a company

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earlier this year called switch

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and work extensively with london-based

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trading desks

[00:09:25.299]
to be able to transform data

[00:09:28.500]
a combination of Market data fundamental

[00:09:31.000]
data and alternative data into

[00:09:33.100]
actionable insights and

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then integrate those inside seamlessly

[00:09:37.600]
into the end of the year.

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Acquisition you know we've

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acquired the ability of ingest

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this all

[00:09:48.000]
kinds of data including alternative data

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and then process

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in such a way to make it relevant for

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for our customers true

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beneficiary of that data to

[00:10:04.799]
but yeah I

[00:10:08.600]
really

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have to be hard with

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everybody Arcadia

[00:10:18.000]
data we are on the technology

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side but we do the date of visualization

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so what we do is we enable

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the end-users the beneficiaries

[00:10:27.299]
the subject matter expert

[00:10:28.799]
tell the visual eyes to be able to see

[00:10:31.000]
the day that I put together and

[00:10:33.700]
to really get the the value

[00:10:35.899]
out of it and all its granular Lori

[00:10:38.200]
are

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the results of the Paul,

[00:10:43.700]
glad to see our audience is a pretty good mix

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of the ecosystem as well but

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a good number of a resonator on

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big data analytics platform the 1st

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which is all

[00:11:05.000]
going to take us through a good

[00:11:07.000]
visual youth kudelka to

[00:11:09.000]
feel what we talk about these things they

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always feel a bit fluffy

[00:11:13.399]
and in the clouds no pun

[00:11:15.399]
intended really understand

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how this can be used in practice

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we think we pick would be helpful

[00:11:22.200]
for the audience and

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get

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everybody to think about what

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alternative date is what they're using it for and

[00:11:39.700]
really to get the conversation going later

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on and I'll

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look at an example of an unconventional

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with alternative data

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so it's really about look

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at your conventional portfolio analysis in

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this example if you're looking

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at retail stores or or something like

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that and if no remote

[00:12:00.399]
standard performance chart you

[00:12:02.899]
looking for for you

[00:12:05.000]
know what's the trade in value and that's all conventional

[00:12:07.799]
apple bloom again here now

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is say okay how can you enrich

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that and you enrich that

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with alternative data sets that's the

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story here so I'm looking again at

[00:12:18.100]
a retail stores in a lot

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of it could be looking at different

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types of data points

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or beta acids and

[00:12:33.799]
tying them together to

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location and then

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you're able to from that really

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be able to see Apples to Apples when you're going from location

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location location that's pretty important I

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think I'm looking at another one

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is going past the

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show in this

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case scenario

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I want to buy a little bit looking

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at this sort of data that that Dun

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& Bradstreet has an account

[00:13:01.799]
with the scenario right so I'm picking up

[00:13:03.899]
a portfolio manager they have fun I'll

[00:13:06.100]
call it a bucket of opportunities to read your

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water companies that they may want to invested

[00:13:11.200]
and from that of

[00:13:13.899]
course you have your fundamental due diligence

[00:13:15.899]
is performed that's right

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here that's your candy bar charts

[00:13:20.700]
and then line charts and things like that but

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the question after that is what

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else can inform the decision-making

[00:13:28.000]
so one of it is

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you know how healthy is the company I'm

[00:13:32.200]
looking at commercial credit scores Financial

[00:13:34.700]
stress what's the health of the

[00:13:36.700]
suppliers are there are

[00:13:38.700]
there any dependencies of the suppliers are

[00:13:41.899]
able to deliver and then the products

[00:13:44.299]
that this company is very good at you

[00:13:46.700]
know starts to fall behind looking

[00:13:51.100]
at other investors are you

[00:13:57.600]
first of the table or

[00:13:59.899]
a lot of people looking at it and so I just

[00:14:01.899]
came up with this network's chart that shows

[00:14:05.299]
that what is the type

[00:14:07.500]
of stuff that. Dun & Bradstreet has and

[00:14:10.500]
it'll take another look it almost gives

[00:14:12.799]
few more examples of how you might

[00:14:14.799]
be able to visualize this again these

[00:14:16.799]
are just ideas just get the ideas

[00:14:19.299]
going so you don't look at the idea

[00:14:21.299]
of a company help that we

[00:14:23.299]
talked about a little bit earlier

[00:14:25.700]
looking at the company

[00:14:27.899]
relationships substitute

[00:14:30.399]
Sherry I'll make it to the show The Beneficial

[00:14:32.899]
owners what's the percent of it.

[00:14:35.200]
So the thing and going

[00:14:37.200]
back to the other idea where

[00:14:44.700]
are they located I

[00:14:48.600]
was just looking at my

[00:14:54.500]
own I looked at in touch this would be

[00:14:56.500]
interesting this might provide

[00:14:58.500]
additional Insight so it just

[00:15:00.600]
shows the idea of being able to explore

[00:15:03.200]
and come up with your own insides based

[00:15:05.200]
on the data.

[00:15:08.500]
I was

[00:15:15.100]
going to pick up on you as

[00:15:19.700]
one of the more interesting factors that we

[00:15:22.000]
found that the data

[00:15:24.299]
that we provide both alive

[00:15:28.000]
and active and in Trials what we found this

[00:15:30.000]
interesting that once you put

[00:15:32.100]
it in the hands of the real

[00:15:34.100]
smart quance

[00:15:36.200]
that works with the hedge funds and some of the other portfolio

[00:15:38.600]
managers it's exciting

[00:15:42.100]
to see how they come up with with their

[00:15:44.100]
own ideas

[00:15:46.200]
as you just a articulated that

[00:15:48.799]
maybe we are nobody else is ever saw that but I

[00:15:50.799]
think that's the value here when you look at what

[00:15:53.000]
the meaning of alternative data is regardless

[00:15:55.200]
of what kind of data every

[00:15:58.200]
every end user

[00:16:00.200]
has their own value Ford

[00:16:02.299]
based on their strategy based on

[00:16:04.299]
on the kind of algorithms day they

[00:16:06.500]
deploy based on how smart they are not

[00:16:08.799]
whatever their experience might be and

[00:16:11.200]
I think that is a opener

[00:16:14.500]
for us here and

[00:16:16.500]
you probably

[00:16:19.200]
see it too I might be interested

[00:16:21.399]
in hearing what from Adams

[00:16:23.500]
point of view with you see the same kind of think

[00:16:25.600]
that I'm from your end uses about

[00:16:27.700]
to a creative aspect of this

[00:16:31.299]
yeah I know that's it that's a great question to

[00:16:33.299]
any other way this is the kind

[00:16:35.399]
of use cases that we found and

[00:16:39.399]
the applications for alternative

[00:16:41.899]
data the way that

[00:16:43.899]
I would kind of split it out as

[00:16:45.899]
between the single stock

[00:16:48.399]
folks out

[00:16:50.500]
there and and inverses programmatic

[00:16:52.799]
trading and then

[00:16:54.799]
also thinking about it along the lines

[00:16:56.899]
of you know discretionary meeting

[00:16:59.799]
that there's a human deeply involved in the investment

[00:17:02.200]
process vs. systemic

[00:17:04.799]
in the type of data as

[00:17:06.799]
well you know how the

[00:17:08.900]
data gets fed into that those processes

[00:17:11.299]
varies widely between

[00:17:13.799]
you know those kind of four different

[00:17:15.799]
those four

[00:17:17.900]
different in

[00:17:20.000]
a ways of waste

[00:17:29.000]
and now it is the Traders

[00:17:31.000]
are acting more and

[00:17:33.000]
more as it's

[00:17:35.799]
kind of like substitutes for what

[00:17:37.900]
the traditional sales Trader used

[00:17:39.900]
to do I told you know as we

[00:17:42.000]
all know that you know that the compact

[00:17:44.299]
among the poles brackets in the decline

[00:17:46.299]
of November or folks

[00:17:48.500]
Manning and so has

[00:17:52.500]
become the person that the portfolio

[00:17:54.900]
manager looks to for

[00:17:57.200]
what's happening in the marketplace so you

[00:17:59.900]
know that's the kind of data and

[00:18:02.000]
the way that they use that day that you know is

[00:18:04.299]
probably about the

[00:18:06.299]
investment process because you

[00:18:09.000]
know the p.m. is already gone through that right

[00:18:11.099]
now what's

[00:18:14.000]
happening in the market did I

[00:18:16.099]
might need to know in

[00:18:18.099]
order to kind of sides

[00:18:20.299]
that I want to get done or the

[00:18:22.299]
urgency of

[00:18:24.400]
completing the order and

[00:18:26.599]
that's where it gets back to you know

[00:18:29.000]
give it back to

[00:18:31.099]
you know that I had a smorgasbord

[00:18:33.500]
of data providers out there would

[00:18:35.500]
be more along the lines of in

[00:18:37.500]
a real time real

[00:18:40.299]
time alternate day too maybe that's

[00:18:42.299]
better that you know sentiment analysis or

[00:18:46.200]
you know the near time media

[00:18:48.700]
content from gdl things like that

[00:18:50.700]
and the process that uses

[00:18:54.700]
his to say we're going to

[00:18:56.700]
we're going to look for abnormal

[00:18:58.700]
changes in the actual behavior of the stock

[00:19:01.099]
that's the first thing to look at right and

[00:19:04.299]
then you know that that alternate

[00:19:06.700]
data is is explanatory right

[00:19:09.700]
so then we try to say okay there's some

[00:19:11.799]
there's something happening and you need to pay

[00:19:13.799]
attention now let you

[00:19:15.799]
know help you find any explanation

[00:19:17.900]
for why that happened

[00:19:20.000]
does a slightly different use case for what

[00:19:22.099]
we're at what we're going through here but I think it makes sense that

[00:19:24.400]
you know on the trading desk you're going

[00:19:26.400]
to be looking for more real-time data when

[00:19:28.500]
you're going up to the portfolio management

[00:19:30.599]
level as you're all you're probably looking at

[00:19:32.700]
in a longer time Horizons

[00:19:34.700]
when it comes to the kind of data

[00:19:36.799]
that you're looking at

[00:19:43.700]
no it's okay. I was just going to say anything about

[00:19:45.700]
this could be to you to you to you as well

[00:19:47.700]
but you know you finding out the

[00:19:49.700]
Traders are quickly getting getting

[00:19:51.700]
the joke or it's in the valley or

[00:19:53.700]
is it feel like it's been a steep learning curve group

[00:19:57.200]
about that maybe has been doing what they do

[00:19:59.400]
to the family of her for a long time you

[00:20:02.700]
know what I mean by

[00:20:19.799]
side is a very heterogeneous

[00:20:22.299]
population right you got up all

[00:20:24.400]
sorts of different kinds of personalities and

[00:20:26.500]
work clothes so it's hard to

[00:20:28.500]
paint them with the broad brush-stroke

[00:20:30.500]
but I would say that everybody

[00:20:33.900]
is has looked at

[00:20:35.900]
things like in our social at the social

[00:20:38.099]
velocity index in for some people

[00:20:40.200]
it's been relevant in for other people

[00:20:42.700]
you know annoyed so

[00:20:45.000]
I don't know if it's still like about me know getting

[00:20:47.000]
the Joker not as to whether he knows more

[00:20:49.200]
about you know how much

[00:20:51.299]
does it really help than

[00:20:53.299]
an Executor on the objectives of

[00:20:55.299]
their portfolio manager if you're buying

[00:20:57.400]
a hold you know shop

[00:20:59.500]
and you're holding names for 5 10

[00:21:01.500]
years and then it's just not it's just not

[00:21:03.700]
going to be alright in

[00:21:06.099]
the portfolio manager may not care that Trump

[00:21:08.599]
has tweeted something just

[00:21:11.400]
be annoyed by knowing that so

[00:21:14.000]
that other shops where

[00:21:16.200]
they might they might still be lonely

[00:21:18.700]
but they're training around position

[00:21:20.900]
right so they're going to hold

[00:21:23.000]
a stock for a long period of time but they

[00:21:25.000]
might trade around it and thighs up inside

[00:21:27.099]
down depending on market conditions that's

[00:21:29.700]
where you start to get into work

[00:21:32.299]
clothes where this kind of data becomes

[00:21:34.900]
irrelevant and you know really helps

[00:21:37.500]
them add performance to the to

[00:21:39.599]
the portfolio move

[00:21:41.900]
to an even more you know higher

[00:21:44.299]
turnover shop like a hedge fund Trader

[00:21:46.400]
actually had some discretion over

[00:21:48.599]
the size of the of the

[00:21:50.599]
position you know then now

[00:21:52.700]
your get you know to the real Cutting

[00:21:55.299]
Edge Xbox and

[00:22:00.200]
from from Donna Bradford perspective I

[00:22:02.200]
think we

[00:22:04.599]
indicated

[00:22:07.099]
more from the with the the

[00:22:09.799]
duck wanting to date at

[00:22:11.900]
the big data analyst

[00:22:14.599]
at the shop so they undoubtedly

[00:22:17.700]
will get the joke they

[00:22:20.299]
are so immersed in this

[00:22:22.500]
that once you get them to

[00:22:24.799]
understand that

[00:22:26.700]
all big data is not equal alternative

[00:22:29.299]
day does not equal and social media date

[00:22:31.500]
is different from geolocation

[00:22:33.700]
data the data

[00:22:36.000]
that we provide which is on a business

[00:22:38.000]
performance payment Behavior things like that

[00:22:40.099]
very quickly the eyes

[00:22:42.200]
open oh yeah that could be something

[00:22:44.299]
I never considered because honestly when you look

[00:22:46.400]
at the the Twitter than the square

[00:22:48.900]
spaces that's almost old knows

[00:22:51.099]
that the dead has had some Muse

[00:22:53.099]
some people don't actually think that there's

[00:22:55.400]
other financial data business performance

[00:22:57.400]
data once you get you a

[00:22:59.500]
present that it's very quickly absorb

[00:23:01.700]
and then the quads would want to dig deep

[00:23:03.900]
into it and try to understand where

[00:23:06.000]
some of the correlations are and we've

[00:23:08.099]
done a lot of that ourselves but they come up with their

[00:23:10.099]
own often and then or ask us

[00:23:12.099]
and then interative process to make

[00:23:14.099]
some but hey can you do this hey what

[00:23:16.200]
if I do this can you do that so yeah

[00:23:18.500]
because I think we're dealing with the quants

[00:23:20.599]
they're all over it and

[00:23:23.299]
I think that I think the

[00:23:25.299]
two you up again Paul I think the

[00:23:27.299]
kind of tools in Arcadia provides really

[00:23:29.500]
the way that that they want to look at things that

[00:23:31.700]
the charts

[00:23:34.500]
and graphs that you show here just on these couple

[00:23:37.299]
of slides is it.

[00:23:39.400]
That's the way that they used to before

[00:23:49.799]
okay yeah thanks X Factor that

[00:23:51.799]
we

[00:23:54.099]
see some questions talking about you

[00:23:56.500]
know providing access natural language

[00:23:58.599]
processing and so

[00:24:00.599]
forth with your questions

[00:24:02.599]
play question by next

[00:24:04.900]
talking about you know how this all right

[00:24:07.099]
and so we have Twitter

[00:24:15.299]
feeds things like that and a

[00:24:17.700]
lot of it looked at it putting into

[00:24:19.700]
it they don't like you what the data repository

[00:24:22.799]
where you put in

[00:24:25.500]
a native format rifle pre-processing

[00:24:28.099]
so glad they liked it a lot more

[00:24:30.099]
to it but

[00:24:32.099]
I'll just leave it at that

[00:24:33.799]
traditionally what you

[00:24:35.799]
have is you have these layers on top of it so yeah if

[00:24:37.799]
you extract the data warehouse putting

[00:24:40.299]
into these cubes putting it into

[00:24:42.400]
a data visualization server so

[00:24:44.500]
that people can get

[00:24:46.599]
access to it to make all

[00:24:48.700]
this work you know you're

[00:24:50.799]
going from this layered

[00:24:52.799]
architecture and

[00:24:56.500]
going directly to you where the data

[00:24:58.500]
results so I'm taking that same story

[00:25:00.500]
got all these data sources and they're

[00:25:02.500]
going into that they don't like the difference

[00:25:04.900]
fear is that you're

[00:25:07.000]
able to do your visual analytics.

[00:25:09.299]
But if I

[00:25:11.299]
was just referring to is you're actually going

[00:25:13.799]
directly to that date or you're inside

[00:25:15.799]
it and you're getting direct

[00:25:18.000]
access to it to do the official analytics

[00:25:20.400]
on and it's from that they

[00:25:22.599]
are able to do have the web-based interface

[00:25:25.299]
and build out these customized

[00:25:27.299]
application directly

[00:25:30.500]
on that data or just give me a little background

[00:25:33.799]
download that you see or things that I did

[00:25:35.900]
on my own just by exploring

[00:25:38.299]
looking at the data trying to figure out what the story

[00:25:40.400]
would be and if I

[00:25:42.400]
didn't have a data scientist working

[00:25:44.799]
on it was really you

[00:25:47.099]
Billy just to be able to explore it and I'm

[00:25:49.200]
not a I'm not a programmer myself

[00:25:52.099]
that's what he

[00:25:56.799]
was talking about he's asking how

[00:25:58.799]
does Arcadia data provide natural language

[00:26:01.099]
processing capabilities before

[00:26:03.599]
the visualization and also about

[00:26:05.799]
looking at strange so

[00:26:08.000]
going back to this the natural

[00:26:10.000]
language processing and so it was all that is being

[00:26:12.099]
done at the lake level or you could see

[00:26:14.200]
it as a source of data so you

[00:26:16.400]
have some machine learning algorithms things

[00:26:19.000]
like that that are going through and trying to figure out okay

[00:26:21.400]
what is the sentiment what is what are people

[00:26:23.700]
thinking about certain certain

[00:26:25.700]
brand that is to me a

[00:26:27.900]
data source and that were able

[00:26:29.900]
to access it and then you're able to make some sense

[00:26:31.900]
out of it and join it with other things

[00:26:33.900]
so we are not processing

[00:26:36.599]
in that sense we are

[00:26:38.900]
able to take that data unstructured

[00:26:41.400]
data real-time data historical

[00:26:43.599]
data and be able to allow

[00:26:45.799]
the end-user the subject matter expert

[00:26:48.099]
to really be able to see it and look at it

[00:26:52.900]
that's quite all the great day to hear

[00:26:58.500]
from the results of the study that we not

[00:27:01.099]
too long ago trying to understand what people

[00:27:03.700]
are actively using

[00:27:06.099]
today one of the findings

[00:27:08.299]
from here with that social media date of the

[00:27:12.400]
first thing that they think it's

[00:27:14.700]
pretty common at this point.

[00:27:16.700]
The manager can Edge find

[00:27:18.799]
so much though it's feeling

[00:27:20.900]
a little less alternative and more of

[00:27:23.000]
a normal normal course of business rate

[00:27:29.299]
other examples of where I'm

[00:27:31.400]
alternative data what type of alternative geolocation

[00:27:43.500]
satellite imagery

[00:27:52.900]
Spice in your life and

[00:27:55.000]
many of them probably more than you realize right

[00:27:57.500]
everything from your phone to quite possibly

[00:27:59.799]
your car I know my oven has a

[00:28:01.900]
Wi-Fi connection right so it's just it's really

[00:28:04.099]
going on and on and on and Illustrated

[00:28:09.500]
very well through Paul's demo

[00:28:11.799]
is finding that

[00:28:13.900]
data or realizing it existed non-trivial

[00:28:17.400]
on however the real tricky

[00:28:19.500]
part of taking a data and knowing exactly what

[00:28:22.500]
to do with it which

[00:28:24.700]
was the

[00:28:29.000]
date of birth strategy do

[00:28:31.099]
you have a portfolio manager

[00:28:33.099]
with a strategy who looks

[00:28:35.299]
to find data to support that idea or

[00:28:38.700]
do you have or call your master out

[00:28:40.700]
looking for data that

[00:28:42.700]
will potentially create a

[00:28:44.700]
new investment strategy under

[00:28:46.900]
no single answer that question

[00:28:48.900]
if we were to look at a high level tends

[00:28:51.500]
to be asset manager

[00:28:53.200]
surreal

[00:28:55.799]
money and bastard to have a strategy and

[00:28:58.000]
look for data to help enhance

[00:29:00.500]
a strategy of support that strategy

[00:29:02.700]
were at the hedge fund anyone

[00:29:05.500]
are more likely to just

[00:29:07.900]
start digging around through data I'm

[00:29:10.099]
looking for something interesting looking for a new correlation

[00:29:12.700]
to God you got for the visualization play

[00:29:15.799]
some

[00:29:17.900]
play that's what I was referring

[00:29:20.099]
to earlier right I feel like I could take

[00:29:22.099]
these categories and they

[00:29:24.200]
would pretty much line up with

[00:29:26.200]
you know whether the asset

[00:29:28.500]
manager or hedge fund was

[00:29:30.799]
single stock or

[00:29:32.799]
no program base

[00:29:35.000]
and or discretionary

[00:29:38.200]
vs. quantitative right

[00:29:40.700]
so you

[00:29:42.700]
know you like I don't think that you're going to find

[00:29:44.900]
a single stock

[00:29:47.599]
from that's going to say new types

[00:29:49.599]
of data Inspire new strategy idea

[00:29:51.900]
right

[00:29:53.099]
you know that they're already going

[00:29:55.099]
through a process to try to you know pick

[00:29:57.200]
a stock that's not going to change the

[00:29:59.799]
but the data

[00:30:02.000]
that they use could better inform

[00:30:04.500]
you know the preamble

[00:30:07.400]
are you finding

[00:30:09.400]
Adam yet that you're having customer

[00:30:11.599]
call and and point out hey you

[00:30:13.799]
know I did I did I did something that I wouldn't

[00:30:16.000]
have done without this or do you think it's a little still

[00:30:18.099]
too early days for that

[00:30:20.900]
anecdotally

[00:30:24.299]
yes we we do hear

[00:30:26.299]
that and it's usually

[00:30:28.500]
so far and this is probably as

[00:30:31.599]
indicative of where we are

[00:30:33.599]
in our life cycle of integrating

[00:30:35.900]
hotas into our front

[00:30:38.200]
end system is anything else is

[00:30:41.299]
that it

[00:30:43.700]
has more to do with

[00:30:46.099]
where went in a chilling

[00:30:48.099]
at any data in the right context

[00:30:50.400]
as opposed to you know

[00:30:52.500]
the data itself

[00:30:55.000]
right so it could be that someone told

[00:30:57.000]
us that you know hey I found

[00:30:59.099]
something really interesting via

[00:31:01.700]
you know the feed

[00:31:03.700]
from inside or score or from estimize

[00:31:05.900]
or Wall Street Horizons

[00:31:08.500]
you know a few of the data

[00:31:10.799]
providers that we have feeding into the system

[00:31:13.000]
but

[00:31:15.000]
it has more to do with where they were

[00:31:17.000]
in the process and how we

[00:31:19.099]
alerted them to the

[00:31:21.299]
change in the data then it was

[00:31:23.700]
like the data itself if that makes

[00:31:25.799]
any sense so that's all you know how I think

[00:31:27.799]
this is how this data gets integrated

[00:31:30.200]
into the process and how if

[00:31:32.299]
there's a human involved you know what

[00:31:34.599]
kind of contacts are shown around the

[00:31:38.000]
change in the data is as

[00:31:40.000]
important as you

[00:31:42.000]
know the other issues

[00:31:44.299]
that we've discussed

[00:31:45.599]
just

[00:31:48.700]
a reminder to the audience if you do have questions

[00:31:50.900]
please feel free to submit them through the through

[00:31:53.599]
the gotowebinar interface and thought

[00:31:55.599]
I was going to take it over to you and are

[00:31:57.599]
you off tonight I to stop one client

[00:31:59.700]
find ideas based on your data they

[00:32:02.500]
want to keep those ideas to themselves so are

[00:32:04.700]
you having clients to explain to you how

[00:32:06.799]
they're using it and if not it's

[00:32:08.799]
that up

[00:32:18.599]
they can you probably hit on the

[00:32:20.900]
the one of the most challenging things we

[00:32:22.900]
have to do so certainly

[00:32:25.900]
it as we would expect there are some

[00:32:28.400]
that share very

[00:32:30.400]
little to nothing there are others that

[00:32:32.599]
will outline the purposes

[00:32:35.799]
of of working with us and trying to get

[00:32:37.900]
us to understand what else

[00:32:39.900]
we might be able to do with the data

[00:32:42.099]
that help they have to share

[00:32:44.400]
some of the how they're using it or

[00:32:46.400]
at least frame

[00:32:48.400]
of a particular use case or scenario

[00:32:51.599]
what did Nick would help them it doesn't necessarily tell

[00:32:54.000]
us how they use it but they but they will

[00:32:56.200]
frame some scenarios for us and

[00:32:58.400]
help us understand what they're

[00:33:00.400]
looking for and if we could manipulate

[00:33:03.000]
data to provide

[00:33:05.099]
what they're looking for but it

[00:33:07.099]
does make it that at the nature of the

[00:33:09.099]
business and we do this going in it

[00:33:11.299]
does make it very different

[00:33:13.400]
from other businesses applying

[00:33:15.500]
data because we know we're not going

[00:33:17.500]
to know a whole lot about how

[00:33:19.799]
I think about it

[00:33:22.000]
the best clients we have the one that again the most

[00:33:24.099]
value of the ones are going to provide the least amount of information

[00:33:26.200]
back to us by definition

[00:33:28.200]
so that

[00:33:30.299]
combined with the the element of of

[00:33:32.400]
the the heterogeneity of

[00:33:34.500]
that no

[00:33:37.099]
two are alike so it's going to depend on how

[00:33:39.200]
many days that they have what their

[00:33:41.200]
technology is like what different

[00:33:43.299]
strategies they deploy where they are on their

[00:33:45.400]
cycle so just because had

[00:33:48.200]
fun decks using the data very

[00:33:50.900]
effectively Identify some opportunities

[00:33:53.200]
that doesn't mean that other hedge funds will so

[00:33:55.200]
not only do we not know precisely

[00:33:57.400]
how everyone is using the data but

[00:33:59.500]
even if we did that sometimes would

[00:34:02.099]
challenges find

[00:34:04.900]
the same guy to the next one everything is unique

[00:34:07.099]
and it makes it somewhat challenging but

[00:34:09.300]
it also was interesting when you begin to recognize

[00:34:11.900]
the value in many many

[00:34:14.500]
different had fun too many scenarios for

[00:34:20.000]
you as a true

[00:34:28.000]
value of the app that right I suspect

[00:34:30.000]
that I provided

[00:34:32.599]
in the value it

[00:34:36.000]
yeah yeah it is I mean obviously we

[00:34:38.000]
have our are a framework

[00:34:40.099]
for pricing and how we charge

[00:34:42.099]
for our data

[00:34:44.099]
sets but to some extent you hit

[00:34:46.099]
on a point in that the value of data

[00:34:48.300]
is a really

[00:34:50.800]
shell could easily be measured

[00:34:53.000]
by the value to that particular and

[00:34:56.199]
user and since we don't know the specific

[00:34:58.500]
value how much they might be making on it or how

[00:35:00.500]
they're using it we have really have no

[00:35:02.599]
other way to the frame it other than pricing

[00:35:06.900]
and packaging it by quality

[00:35:09.300]
of data type of data we have and

[00:35:12.199]
I think that works certainly

[00:35:14.300]
for now hopefully over time will

[00:35:16.800]
grow more intelligent about the uses

[00:35:18.900]
and and the market will become more

[00:35:20.900]
understanding and accepting of

[00:35:22.900]
that and we can have more variable

[00:35:25.000]
pricing strategy for for now it's

[00:35:27.699]
pretty easy on our side although we are aware

[00:35:29.800]
that there are unknowns there

[00:35:31.800]
that could change things over time

[00:35:33.599]
Kershaw rental in and finding

[00:35:35.699]
that value right it's it's at the corner

[00:35:37.800]
earlier it's one of the hardest part

[00:35:39.800]
even for the end users you

[00:35:42.400]
can see here when we add to her

[00:35:44.699]
folks looking at alternative date

[00:35:46.699]
of the use of data visualization

[00:35:49.000]
tools are number one growing

[00:35:51.300]
number

[00:35:53.500]
of the providers are you can't

[00:36:00.900]
help but notice you know Excel

[00:36:02.900]
just won't go away not

[00:36:05.800]
necessarily that we wanted to go away but the

[00:36:07.800]
power of excelling interesting

[00:36:10.300]
although I may befall put the deal

[00:36:12.300]
you have to imagine that is as

[00:36:14.900]
the customizable as

[00:36:17.099]
XL is your point earlier ride

[00:36:19.099]
you did what you did without without being

[00:36:21.300]
a programmer that you're still have

[00:36:23.500]
a hard time especially a data set guide

[00:36:25.500]
non-standard and very very big

[00:36:28.000]
I'm exhausted yeah

[00:36:30.400]
I know shows

[00:36:34.099]
that the use of alternative

[00:36:36.500]
data to temperature your

[00:36:38.800]
strategies or how you out you're going

[00:36:40.900]
to look at it it's very very much

[00:36:43.800]
a self-serve sort

[00:36:46.000]
of process right now you need

[00:36:48.099]
to be able to be

[00:36:50.300]
able to use your mic XLR but like Kevin

[00:36:52.500]
said XL everybody knows how to use it and

[00:36:54.900]
they're

[00:36:59.099]
really doing the expiration on the Rhone

[00:37:01.099]
earlier

[00:37:04.000]
that it's really it's a service

[00:37:06.800]
they are driving process and

[00:37:10.199]
they're also working you know it is in

[00:37:12.300]
group shout it's also

[00:37:17.000]
yeah by the tool that allows for

[00:37:28.300]
the conversation about value clearly

[00:37:30.599]
investment Community is being

[00:37:32.599]
value of the

[00:37:34.900]
headlines out of our research that we put out

[00:37:37.000]
last month with

[00:37:39.000]
90% of the end up with

[00:37:41.699]
that are currently using alternative data

[00:37:43.800]
they're getting their return in

[00:37:46.199]
the bathroom already planning to spend more money

[00:37:48.900]
on this in the future

[00:37:52.099]
so what

[00:37:54.900]
if we know what is the next to

[00:37:57.900]
we in some ways

[00:37:59.900]
it's so obvious that this year

[00:38:02.000]
but not everybody's doing

[00:38:04.099]
it as

[00:38:07.500]
you better think about what else you can do with the data

[00:38:09.599]
how do you get it out there more you

[00:38:12.800]
know what are some of the major parties and

[00:38:14.900]
think that you're focused

[00:38:18.500]
I

[00:38:21.199]
think we're looking at not

[00:38:24.000]
just that the data applications

[00:38:27.400]
in this way but also where where else

[00:38:29.400]
does it fit in this industry

[00:38:31.400]
idea how can I date a cyst

[00:38:33.599]
for instance m&a

[00:38:35.599]
in a private Equity so

[00:38:38.000]
there are other factors that

[00:38:40.000]
we're considering and how to bring out some

[00:38:42.000]
of the date that we have to

[00:38:44.599]
make it and apply more effectively

[00:38:47.000]
in this business more broadly specifically

[00:38:50.099]
when you're looking at evaluation it's

[00:38:52.699]
weird talking in

[00:38:55.599]
this discussion here is primarily in the equity

[00:38:57.800]
space but in the same way that we

[00:38:59.900]
may be able to look at our private

[00:39:02.199]
company data and how it applies

[00:39:04.199]
to say private investor private Equity the

[00:39:06.400]
same holds true for fixed-income right by

[00:39:10.099]
our data and that way to to learn

[00:39:12.199]
more about a particular entity and

[00:39:14.800]
how it's how

[00:39:17.400]
it's linked in

[00:39:18.500]
I work in a business elements have

[00:39:21.500]
more information we can apply hot what

[00:39:23.599]
what kind of scores can we create for instance

[00:39:25.699]
to predict business

[00:39:27.699]
performance in a different way so we're always looking at

[00:39:29.800]
that and we learn from those

[00:39:32.199]
are trialling and those that are actively using

[00:39:34.199]
we also learn from people

[00:39:36.500]
like you and people like bike

[00:39:38.800]
Arcadia friends instead have ways of presenting

[00:39:41.300]
and displaying data that

[00:39:43.500]
bring out some of these opportunities so

[00:39:46.599]
it is always tricky and we know that probably

[00:39:48.699]
the most interesting part of this

[00:39:50.699]
is and you said I think

[00:39:52.800]
of money reports Kevin I said he won't turn the date

[00:39:55.000]
is only alternative for short time it's

[00:39:57.199]
consistently evolving so how we going to do

[00:39:59.400]
this next year and Beyond is something

[00:40:01.599]
that challenges I think all of us here

[00:40:03.699]
in this small company

[00:40:07.099]
right here trying to tell your daddy to as many people as

[00:40:09.199]
you can but on the other hand if you sell it to

[00:40:11.199]
everybody does it says it started and lose

[00:40:13.300]
value if I did not.

[00:40:16.800]
yeah it's at the challenge and not

[00:40:19.000]
just selling it but in marketing it because

[00:40:21.199]
if you know if we want to

[00:40:23.199]
when you want a phone call or if you're talking to you

[00:40:25.800]
want to say while everybody uses this so you should

[00:40:28.000]
too there's a an

[00:40:30.300]
aspect that you mention that because well you know if everybody's

[00:40:32.500]
using it I don't necessarily want to use it but

[00:40:35.300]
at the same time without that kind

[00:40:37.400]
of validation that others are getting value

[00:40:39.500]
from it you lose some of the potential

[00:40:42.500]
value in the selling point so they everybody

[00:40:44.599]
in this business has a similar challenge but

[00:40:47.099]
I think we know and I think everybody were

[00:40:49.300]
talking with nose so

[00:40:51.500]
it's not as if they think

[00:40:54.599]
nobody's using it they know that others use

[00:40:56.699]
it maybe you're not telling them but it is

[00:41:01.500]
check in and out of

[00:41:03.500]
your customers because alternative

[00:41:05.599]
date of the world is so big they probably

[00:41:07.800]
don't even know what to ask for it

[00:41:09.800]
so how do you guys figure out what

[00:41:12.400]
day to could be used to your

[00:41:14.599]
customer base us

[00:41:17.800]
one of the subject matter you

[00:41:20.199]
know experts or areas of expertise

[00:41:22.699]
that we gain through the acquisition

[00:41:24.800]
with oat I have a very in

[00:41:27.199]
a robust process through which they can

[00:41:29.300]
take in a inject data and

[00:41:31.800]
then c e you know what the

[00:41:34.099]
see if there's any outfit in there see

[00:41:37.199]
what type of outfit is see

[00:41:40.099]
if it's one

[00:41:42.199]
way to measure a data set is

[00:41:44.199]
over in Ohio over a long

[00:41:46.500]
or abroad list of stocks

[00:41:48.900]
if it is raining

[00:41:51.500]
Alpha signals then you

[00:41:53.699]
know what you know how much golf is

[00:41:55.699]
there when it's looking across do you know

[00:41:57.800]
a large set of fire buy and sell signals

[00:42:01.500]
Enterprise customer doesn't

[00:42:04.199]
really matter right we're

[00:42:06.500]
going to show a piece

[00:42:08.599]
of data to someone that only

[00:42:10.599]
has 10 names on

[00:42:12.599]
their blotter you know being

[00:42:14.800]
right 51% of the time isn't

[00:42:16.800]
good enough so you

[00:42:18.800]
know again depending on who

[00:42:20.800]
were looking to the service

[00:42:22.900]
and who's consuming the data you

[00:42:25.300]
know the kind

[00:42:27.300]
of outcomes that we're looking for

[00:42:29.300]
Change and so but

[00:42:31.400]
those are the ones that

[00:42:33.699]
manage that process

[00:42:35.800]
in there you know evaluating different

[00:42:38.699]
data sets and thinking

[00:42:40.699]
about how we might incorporate it into

[00:42:42.800]
our front end

[00:42:44.900]
trading system but then also for

[00:42:46.900]
you know I owe

[00:42:49.900]
you know the kind of original

[00:42:52.500]
otash consumers that might

[00:42:55.000]
not be using it only for training

[00:42:57.500]
purposes but might also be using

[00:42:59.599]
it for the investment

[00:43:01.400]
as well

[00:43:04.500]
yeah it's

[00:43:06.500]
going back to you know it's only alternative for

[00:43:08.800]
certain amount of time it's really

[00:43:10.800]
about how well if used right cuz

[00:43:13.900]
everybody can. It's not really the dataset that's

[00:43:15.900]
going to get you how you how the

[00:43:18.199]
the portfolio manager

[00:43:20.199]
has been able to tie together Analyze

[00:43:22.900]
That looked at it and you

[00:43:25.000]
know how their team is able to put it together and it's

[00:43:29.400]
not actually two data sets by myself just

[00:43:34.699]
to get really a specific on our

[00:43:36.699]
use cases you know the way we think

[00:43:38.800]
about it is that you

[00:43:41.199]
would quit

[00:43:43.300]
eating without data and lower liquidity

[00:43:45.500]
without intelligent kind

[00:43:48.000]
of Reckless right because you could be

[00:43:50.000]
making a big trade at the wrong

[00:43:52.000]
time if you don't have the right date

[00:43:54.000]
in front of you but conversely

[00:43:56.099]
data without liquidity

[00:43:58.900]
is useless right so what

[00:44:01.000]
we're trying to do is bring together you

[00:44:03.400]
know all these days that

[00:44:05.900]
have some support but then also

[00:44:07.900]
be no show that out

[00:44:09.900]
a time where someone knows they

[00:44:12.000]
can take action there is a inability

[00:44:14.300]
to execute on that idea in

[00:44:16.699]
a right now I

[00:44:20.599]
think you bring up an interesting point that

[00:44:22.900]
there's such a

[00:44:24.900]
rush and focus on

[00:44:27.000]
big data and and the outset

[00:44:29.800]
of this call laid out

[00:44:31.800]
how much data cable kind of everybody

[00:44:38.699]
wants more data the more

[00:44:40.900]
there is only one and

[00:44:43.000]
there is a risk involved then you just hit it that what

[00:44:46.699]
day does not better necessarily unless

[00:44:48.699]
it's smart and actually it could be

[00:44:50.699]
risky or if you're not do you have

[00:44:53.000]
when you're not smart

[00:44:55.000]
enough and more

[00:44:57.000]
if you have of making that mistake and

[00:44:59.300]
that they can be compounded may wait over because

[00:45:02.300]
of the bed today that you have on

[00:45:04.300]
the bed was you using it so I

[00:45:07.000]
think that's something you'll have to bring out on that

[00:45:09.000]
nor lot of our trials are

[00:45:12.500]
our customers and Prospects are asking

[00:45:14.699]
for long histories of the date I want

[00:45:16.800]
more than they want more and more testing and

[00:45:20.199]
history so they can try to prove it

[00:45:22.199]
out but there is a risk factor

[00:45:24.199]
involved whatever

[00:45:30.400]
the price tag is $10,000

[00:45:33.900]
on a data set that you know because

[00:45:35.900]
you found a correlation and nobody's ever found

[00:45:37.900]
before that you need to make sure that

[00:45:39.900]
it's not like the price

[00:45:41.900]
of butter in Bangladesh compared to the S&P

[00:45:43.900]
500 right back. It's actually called

[00:45:46.199]
H3

[00:45:57.099]
audience that's really

[00:45:59.199]
active in the space and thank you everybody

[00:46:01.199]
for filling out those questions when you

[00:46:03.300]
register the vast majority of a book

[00:46:05.599]
about on the webinar today are I'm

[00:46:07.800]
in some way shape or form actively involved in

[00:46:09.900]
the states which which

[00:46:11.900]
is great and when we asked about him

[00:46:14.099]
what what comes to mind

[00:46:16.199]
when you think alternative date of the list of

[00:46:18.500]
responses is

[00:46:20.500]
Ali dawah how much

[00:46:22.599]
really just friend called how big

[00:46:24.800]
this Market is and how it's only going

[00:46:26.900]
to get bigger yeah

[00:46:29.000]
so I mean really just can be any

[00:46:31.000]
type of data I'm

[00:46:33.099]
applying at the financial services really only goes

[00:46:35.199]
back to you know how creative

[00:46:37.500]
you know the end users of

[00:46:39.500]
matter expert quad can be with

[00:46:41.500]
it the

[00:46:43.599]
understanding for the how do you put some workout

[00:46:46.000]
interact with talked about a lot of the dynamic

[00:46:48.099]
the ready today you want to sell

[00:46:50.099]
as much as you can to make money but if you felt too

[00:46:52.099]
much you're not going to make much money understanding

[00:46:54.599]
of complexities are you are

[00:46:56.599]
pretty important

[00:46:58.400]
does it doesn't new you

[00:47:00.500]
know when new world and in many many

[00:47:02.599]
ways to write the the data didn't

[00:47:04.599]
exist before the tools to use to

[00:47:06.599]
utilize it didn't exist before I

[00:47:10.500]
need to know what to do with the situation today

[00:47:12.900]
over that is no small thing of

[00:47:15.500]
course yeah this is definitely a case of Pinot

[00:47:18.599]
first-mover advantages huge

[00:47:20.599]
decide

[00:47:23.599]
if you have information that nobody else does which

[00:47:26.400]
is something obviously that's as old as Wall

[00:47:28.400]
Street I'm in most certainly applies here

[00:47:30.400]
and will be quite a bit I'm more more

[00:47:32.400]
value there so so before

[00:47:34.699]
I before we wrap it up and

[00:47:36.699]
call it may be any search Final

[00:47:39.000]
the big sauce from any

[00:47:41.099]
of our panelist what the audience to think about

[00:47:43.099]
and and and

[00:47:45.400]
yet it will end up all

[00:47:47.800]
bobetta I just what

[00:47:50.000]
I said this is Paul again and we'll exchange from

[00:47:52.099]
the the research report that we that

[00:47:54.099]
we were going to try and everything

[00:47:57.300]
else the other alternative

[00:47:59.500]
data as a process and

[00:48:01.500]
it's an iterative process and it's an exploratory

[00:48:03.599]
process and I

[00:48:05.599]
think it's just going to get a lot more interesting

[00:48:07.699]
as we as we go forward

[00:48:14.599]
final thoughts well

[00:48:17.900]
I think your first of all one

[00:48:20.500]
thing to recognize this when at

[00:48:22.699]
a time now when Capital

[00:48:25.400]
markets investing you become

[00:48:27.400]
so much more efficient and

[00:48:29.599]
your passive investing is growing I

[00:48:31.599]
think you have to look at it is it's

[00:48:33.699]
becoming more and more difficult that little sliver

[00:48:35.699]
of valve is more of a challenge to

[00:48:37.699]
reach in sometime Hill alternative data

[00:48:39.699]
can be the difference between Alpha and beta for

[00:48:42.800]
any professional investor so looking

[00:48:45.800]
at turning over every Rock and trying to

[00:48:47.800]
understand where the value is and

[00:48:50.400]
trying to stay ahead of the curve is

[00:48:52.900]
really a challenge as no

[00:48:55.199]
more more money comes in from the fiduciary

[00:48:57.500]
there is so much more of its

[00:48:59.599]
going past is that if you're if you're active

[00:49:02.000]
and your manager going to head that

[00:49:04.099]
way you've got to identify the

[00:49:06.500]
data and most importantly find the best

[00:49:08.599]
ways to use it and apply it to fit

[00:49:10.800]
the strategies that that you have and

[00:49:12.800]
whether it's finding

[00:49:14.699]
no data from a provider

[00:49:17.000]
such a stunning bride Street or or or

[00:49:19.300]
getting a platform like Arcadia that

[00:49:21.300]
to be able to bring out

[00:49:23.400]
some of those opportunities or

[00:49:25.599]
apply it to trade broker

[00:49:29.800]
like liquid everybody's

[00:49:33.099]
radar now it was looking to

[00:49:35.199]
try to identify that that

[00:49:37.400]
particular flavor that's going to take them all

[00:49:39.500]
over the top and then she supposed

[00:49:42.000]
to be I think

[00:49:46.400]
that no matter where you fall in

[00:49:48.500]
the ecosystem no

[00:49:50.500]
becoming more familiar with

[00:49:52.699]
alternative data and the processes

[00:49:55.199]
that are you convert

[00:49:57.599]
that into you know whether it sent

[00:49:59.599]
to men or in the living room kitchen whatever

[00:50:01.900]
it is no to me that's just like

[00:50:04.199]
a new form of literacy that everyone

[00:50:06.699]
in this industry is going to have to have some

[00:50:08.900]
level of comfort with you

[00:50:11.199]
know it had like it reminds me of being

[00:50:13.199]
a going back to the early

[00:50:15.699]
nineties and electronic trading and if you didn't

[00:50:17.900]
know the basics of how

[00:50:20.000]
computers work Torino

[00:50:22.599]
simple jargon around

[00:50:24.599]
programming in a year were going

[00:50:27.000]
to be a programmer

[00:50:29.199]
I'm not a date but I think

[00:50:31.400]
it's incumbent upon anyone in this industry

[00:50:33.400]
that they become more familiar

[00:50:35.400]
with data science and it's just

[00:50:37.400]
basic constructs so that when

[00:50:39.599]
they are looking at or reading

[00:50:41.900]
about different types of products

[00:50:43.800]
different types of data they

[00:50:45.900]
can kind of quickly filter

[00:50:48.099]
out what might be worth investigating versus

[00:50:51.199]
what may not be as relevant for their own

[00:50:56.099]
let

[00:50:58.800]
me talk to quick questions out of the panel first

[00:51:01.000]
one is alternative

[00:51:06.500]
income

[00:51:08.800]
portfolio managers are

[00:51:10.900]
given at the traffic insecurities that I

[00:51:13.000]
left liquid with lower price transparency me

[00:51:15.500]
about

[00:51:20.400]
credit score and spend office

[00:51:22.900]
in the market that impact

[00:51:25.199]
set it up a company or

[00:51:27.300]
not all that much different than two factors that can impact

[00:51:29.599]
of the equity in

[00:51:31.599]
a company understanding understanding

[00:51:35.199]
profactor

[00:51:37.900]
the reason it all the way

[00:51:39.900]
back up some of that would

[00:51:42.000]
have now become the obvious answers of taking

[00:51:44.199]
pictures of parking lot time to stand

[00:51:46.199]
up for down

[00:51:48.300]
for a retail

[00:51:50.300]
chain and in some ways the opacity

[00:51:53.099]
of pricing and even

[00:51:56.500]
more right for alternative data because

[00:51:59.199]
everybody.

[00:52:02.199]
Trying to figure out how they can better

[00:52:04.400]
understand valuation door or

[00:52:06.400]
predict the direction of the market because the market

[00:52:08.500]
is I

[00:52:13.699]
think I can I think

[00:52:15.800]
I can be even more useful

[00:52:25.199]
you know the early used to make

[00:52:27.800]
sure that's all work before applying to more complex

[00:52:29.800]
probably doesn't

[00:52:32.000]
go back to Adams associated

[00:52:47.400]
with the use of any

[00:52:49.400]
Edge funds from

[00:52:52.000]
embracing them to the fullest extent you

[00:53:01.699]
collect as a farm and what you do with it but

[00:53:03.900]
it's some Jazzy unknown hurting

[00:53:06.199]
its adoption

[00:53:09.300]
from the point

[00:53:11.800]
of view of a data provider

[00:53:13.800]
or day or a source yeah

[00:53:16.699]
they're there are things that as

[00:53:19.199]
you noted that the

[00:53:21.400]
limited

[00:53:24.099]
to disclose based on the way

[00:53:26.199]
we collect the data that

[00:53:28.199]
we or were fully aware

[00:53:30.199]
that if we were able to disclose it make

[00:53:32.400]
that more transparent it would become more

[00:53:34.400]
valuable to the fund

[00:53:36.699]
there and there's a number of times where we

[00:53:38.800]
have to find ways to aggregate

[00:53:41.599]
disguise and otherwise

[00:53:43.599]
obfuscate the

[00:53:45.900]
ability of some of the funds

[00:53:48.900]
not only to see the

[00:53:51.400]
details but to

[00:53:53.400]
be able to reverse engineer it so

[00:53:55.500]
we got to make sure that they can't

[00:53:57.599]
recently reverse-engineer the data because

[00:53:59.800]
of the agreement we have the collecting it so

[00:54:02.000]
yeah that's certainly inhibits

[00:54:04.400]
awesome as well as many other data

[00:54:06.500]
provided it

[00:54:08.599]
doesn't ugly shoes that are legal

[00:54:10.699]
agreement issues all that fall into place when

[00:54:13.300]
you look in alternative date I think that that's

[00:54:15.599]
at the corner of adult alternative for a reason

[00:54:17.599]
because sometimes we don't really know what

[00:54:20.500]
were able to reasonably

[00:54:22.900]
disclose and end and that you said it before

[00:54:24.900]
Kevin what's your oven disclosing

[00:54:27.699]
about the way you live

[00:54:29.900]
your life and how much of that is if

[00:54:31.900]
worth

[00:54:36.699]
no no ahead and interesting

[00:54:38.900]
concept but if you go back to sleep

[00:54:40.900]
early around

[00:54:44.099]
the the primary

[00:54:47.599]
networks what would happen

[00:54:49.599]
Aaron and how

[00:54:55.099]
and when do something like that come into the all

[00:54:57.099]
data space.

[00:54:59.300]
Time will tell me a space to

[00:55:01.300]
watch up and then

[00:55:08.599]
we actually asked for from

[00:55:10.699]
everybody on the line so I think we're here

[00:55:12.900]
we'll get back to those folks individually

[00:55:15.900]
and certainly if we have not addressed the particular

[00:55:18.300]
question feel free to reach out to us would

[00:55:21.000]
love to make that connection let

[00:55:23.300]
me think all Adam

[00:55:25.599]
Bob and everybody on the line for the

[00:55:27.599]
participation the fact that we did go over

[00:55:29.599]
certainly talks to the interesting

[00:55:33.300]
nature of the subject it continues to evolve

[00:55:35.400]
into on our radar

[00:55:37.500]
and happy to share

[00:55:39.500]
that with you as we as

[00:55:41.599]
we progressed if there's anything

[00:55:43.699]
further that we can do once

[00:55:46.199]
again please get back to you got our contact

[00:55:48.199]
at the

[00:55:50.199]
vet thanks again for your time and

[00:55:52.300]
it will be back again later

[00:55:54.300]
thanks everybody preciate it thank

[00:55:56.400]
you thank you