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Wayne-based fintech startup QuantaVerse has a well-defined idea, deep domain expertise, a clear market opportunity, proprietary technology, an increasing amount of funding, and some strong supporters.
What more could you ask for starters?
Founded by former SEI Investments (NASDAQ: SEIC) executive David McLaughlin in 2014, QuantaVerse uses a combination of data science techniques to filter through a bank's data as well as external data to flag potential money laundering cases and other potential crimes.
As QuantaVerse states on its website: "Our Risk Reduction solutions reveal which of your customers represent unacceptable risk of using your services and platforms to launder money, fund terrorism, or commit other financial crimes."
Just google "money laundering penalties" to get an idea of whats been going on recently. And its a global problem, not limited to US banks.
Penalties, ranging from billions to thousands, have been assessed. In some cases, there are indications of deliberate laxness or negligence, but in most cases lack of compliance resources or simply an antiquated 'needle in the haystack' approach may be at fault.
Whether the economic benefit is cost avoidance (reducing the expected value of potential penalties or the risk to the bank's reputation), or reducing compliance costs through a better mix of technology and personnel, the economic case can be compelling if the technology performs.
QuantaVerse was a big hit at the IMPACT 2016 Capital Conference held in Philadelphia in late November, being chosen as the winner of the “People’s Choice Award” based on polling of conference attendees. QuantaVerse was one of three companies presenting at the conference to be selected to enter the IMPACT “Lion’s Den”, and received investment offers totaling $300,000 as a result. While exact terms for some of those outstanding offers still need to be worked out, the additional investors could bring QuantaVerse's cumulative investment to $1.8 million.
McLaughlin said, "As flattered as we are to receive investment offers, the validation provided by the technology and capital community, particularly given the deep expertise our region has in banking and finance, is truly gratifying.”
QuantaVerse's team uses a broad spectrum of data science techniques, from basic capabilities such as text harvesting and metadata management, to more advanced techniques, including elastic robotic harvesting, neural network analysis, and use of deep learning frameworks. AI is the hottest buzzword going, and though there may be AI attributes to some of QuantaVerse's methodologies, its beyond my knowledge base to say whether they meet specific criteria to be called AI. But McLaughlin uses the term sparingly.
Getting the data in a usable format is another challenge. "Normalizing data across multiple systems has traditionally been hard for them [banks], but something we do as a normal course of our work,” McLaughlin said.
Another issue QuantaVerse is just starting to tackle is educating the regulators. Getting their buy-in, or at least understanding of what QuantaVerse does, is crucial.
QuantaVerse has a small handful (both large and small) of beta customers ongoing now, and has 5 to 10 employees. It expects to roll out its go-to-market plan in 2017, and will also seek a Series A during the year.
McLaughlin may also have QuantaVerse pursue a few corollary financial services-oriented applications as well.
This article in American Banker gives a good look at McLaughlin's thinking.