Assertion certainty 4/5 debate potential 2/5

A major New York bank hired 13,000 compliance reviewers since 2012

Apoorv Agarwal · AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC) · May 13, 2019 · at 3:37

Apoorv Agarwal, CEO of Text IQ, illustrates the immense labor scale and expense major financial institutions incur using traditional compliance methods.

0:00 / 0:09exact quote · 9.8s
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“A major bank in New York alone, they've hired over 13,000 people since 2012 looking for sensitive needles in this haystack.”

quote is from the automated transcript, cleaned for reading: filler sounds and stutters are removed, nothing is rephrased. names can be misheard (the analysis reads context, assessments check outside sources). how →

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Insight
Structuring enterprise unstructured data requires unsupervised machine learning
“There's just so many different types of documents and types of data that there's just no way we can, you know, tackle this problem using supervised machine learning. So a lot of the machine learning we use in-house you know, is, is mostly unsupervised and that…”
Apoorv Agarwal May 13, 2019 ▶ 9:37 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Insight
Enterprise AI only needs to outperform keyword searches and human reviewers
“The bar is not to be hundred percent accurate. The bar is search tomes and 500 humans, right? And as it turns out that bar is not that hard to beat with AI.”
Apoorv Agarwal May 13, 2019 ▶ 14:39 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Assertion Not checkable as stated
Enterprise compliance still relies mostly on keyword search and manual review
“The status quo method, the most popular method of finding these needles in a haystack remains to be based on search terms, ah, and manual review.”
Apoorv Agarwal May 13, 2019 ▶ 3:24 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Assertion Supported
Text IQ infers employee roles and relationships to flag sensitive information
“We can analyze human communication, we can infer things about roles of people within an organization, their relationship, and that allows us to zoom into or find many different kinds of sensitive information.”
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Insight
Agarwal: Analyzing short text requires different ML techniques due to context limits
“Dealing with short text, it's a totally different you know, animal compared to longer text. There's very little context.”
Apoorv Agarwal May 13, 2019 ▶ 10:58 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
Assertion Not checkable as stated
Text IQ achieved profitability by 2017 with a 100% pilot conversion rate
“We've been profitable since 2017 but really the metric that we are proud of is that we, we've had a hundred percent pilot to customer conversion rate.”
Apoorv Agarwal May 13, 2019 ▶ 2:11 AI for Sensitive Information // Apoorv Agarwal, Text IQ (FirstMark's Data Driven NYC)
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