Forbes 30-under-30 girlboss arrested for selling company to JPMorgan for $175m pretending they had 4 million users when they only had 250k

JPMC reached out via email to a random sample of the list Frank provided – approximately 400,000 purported customers of Frank – with offers to open Chase checking or savings accounts. Of those 400,000, only 103 even clicked through to Frank’s website.

As an email list proprietor, I can say: not a great click rate. Here’s Javice’s version:

Chase undermined Frank’s value by pursuing poorly conceived business plans focused on monetizing student FAFSA® data and conducting direct marketing campaigns aimed at Frank’s historical customers. The proposed business plans disregarded the regulatory environment in which the financial aid platform operated, failed to capitalize on Ms. Javice’s past successes, and discounted the very skills for which JPMorgan Bank hired her. More specifically, the new team focused primarily on mining the personal information of Frank’s legacy customers to blast them with marketing emails promoting consumer financial products, including credit cards and personal loans.

In Javice’s story, she objected to JPMorgan’s efforts to market to her customers, for regulatory and, one assumes, aesthetic reasons; JPMorgan retaliated by subjecting her “to overzealous internal investigations and fishing expeditions” and eventually firing her.

JPMorgan’s story is considerably more interesting. In its story, the 0.026% click rate on the test email was evidence that Javice’s email list was not what JPMorgan had hoped for. So it “initiated a comprehensive investigation into Frank and the Merger,” mostly by reading through Javice’s old emails, which are now on JPMorgan’s servers.[1] Oh boy did that turn up some good stuff!

During due diligence for the merger, Javice told JPMorgan that Frank had 4.25 million users. “Users,” to JPMorgan, seems to have meant something close to “people we can send emails to”:

At an initial July 2021 meeting, Javice told JPMC that Frank had significant engagement with college-aged students, a market segment that JPMC wanted to grow. Javice stated that Frank had 4.25 million users, expressly defining a “user” as an individual who created a Frank account by entering a first name, last name, email, and phone number on Frank’s website. …

Based on the July 21 meeting and the data room materials, JPMC confirmed Frank’s definition of its customers base, namely, customers are users who created a Frank account. Thereafter, as part of due diligence on Javice’s 4.265 million customer account claim, JPMC made an unambiguous request to Javice for a list of Frank’s customer accounts that included important data, such as first names, last names, dates of birth, phone numbers, mailing addresses, and email addresses. …

Specifically, JPMC sought to confirm its thesis that Frank’s acquisition of 4.265 million customer accounts demonstrated that Frank had created momentum, growth, and scale by developing meaningful relationships with millions of students. That momentum, growth, and scale, JPMC believed, indicated that Frank was a proven acquisition machine for college-aged students and would continue – and even increase – its customer account base once Frank merged with and into JPMC. If Frank’s customer base existed, JPMC could proceed with the deal.

But, JPMorgan now says, Frank only really had about 300,000 customer accounts. So Javice allegedly asked a Frank engineer to make up a fake list. It did not go great:

She sent Frank’s Director of Engineering an email with a link to an article entitled “Generating Tabular Synthetic Data Using GANs.” The article notes that “[t]he goal is to generate synthetic data that is similar to the actual data in terms of statistics and demographics.” The article suggests that “it[’]s fairly simpl[e] to use GANs to generate synthetic data where the actual data is sensitive in nature and can’t be shared publicly.”

Javice, Amar, and the Director of Engineering then had a Zoom meeting during which Javice and Amar asked the Director of Engineering to help them create a synthetic list of customer data. She asked the Director of Engineering if he could help her take a known set of FAFSA application data and use it to artificially augment a much larger set of anonymous data that her systems had collected over time. The Director of Engineering questioned whether creating and using such a data set was legal, but Javice tried to assure the engineer by claiming that this was perfectly acceptable in an investment situation and she did not believe that anyone would end up in an “orange jumpsuit” over this project.

The Director of Engineering was not persuaded and told Javice and Amar that he would not perform the task and only would send them the file containing Frank’s actual users, which amounted to approximately 293,000 individuals at that time.

Aieee, this is not legal advice, but if your boss is prone to using the phrase “orange jumpsuit” you should quit! And probably go claim your whistle-blower reward while you’re at it. Anyway Javice then allegedly “sought help from external sources”:

Javice then turned to a data science professor at a New York City area college (the “Data Science Professor”) who advertised his “creative solutions” to data problems. Javice provided the Data Science Professor a list of 293,192 individuals who had started or submitted a FAFSA application through Frank. She then directed the Data Science Professor to use “synthetic data” techniques to create 4.265 million customer names, email addresses, birthdays, and other personal information based on the list Javice supplied.

The professor allegedly created the list, with lots of hilarious guidance along the way that JPMorgan now has:

Regarding creating physical addresses, the Data Science Professor wrote to Javice, “I can’t seem to find addresses in my raw files . . . . Should I attempt to fabricate them?” Javice responded “I just wouldn’t want the street to not exist in the state.” Later, the Data Science Professor determined that “‘real addresses’ may not be doable,” and Javice responded “If we can’t do real addresses what[’]s the best we can do for that?” …

Javice was particularly concerned with the email addresses, asking the Data Science Professor “will the fake emails look real with an eye check or better to use unique ID?” He responded “[t]hey will look fake,” at which point Javice agreed to use a “unique ID” instead.

Eventually the list was done and the professor sent Frank an invoice for $13,300, listing his hours devoted to tasks like “college major generation.” This was not the invoice Javice wanted, so:

In response to the initial invoice, Javice demanded that he remove all the details admitting to how they had created fake customers – and added a $4,700 bonus. In an email to the Data Science Professor at 12:39 p.m. on August 5, 2021, Javice wrote: “send the invoice back at $18k and just one line item for data analysis.” In total, Javice paid the Data Science Professor over $800 per hour for his work creating the Fake Customer List, which is 270% of his usual hourly rate.

The Data Science Professor provided Javice the revised invoice via email seven minutes later at 12:46 p.m., commenting “Wow. Thank you. Here is the new invoice.”