Kartik chopra biography pdf

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And Devron's technology has the "potential to alter the data science and AI landscape," he added. Devron allows firms to pull together data from across an organization that might be difficult to otherwise combine. The startup's founder and CEO Kartik Chopra is no stranger to wrangling data across different systems. As a former CIA intelligence officer targeting adversarial technologies in Russia and China, Chopra spent years pouring over large sets of transactional data to sniff out malicious activity, bad actors, and fraud.

But analyzing the data wasn't the hard part — the bigger challenge was harnessing the data that was spread across different systems, departments, geographies, and authorization levels. An uncanny situation is currently playing out among financial institutions, wherein sharing data between different systems or business lines is time-consuming, costly, and sometimes limited by privacy and regulatory constraints.

Computers are easy to move. Data is not easy to move.

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A month after leaving the CIA in , Chopra founded Devron after realizing there's a swath of other firms, both in public and private sectors, that were navigating the same data struggles. The upstart, which launched in the fall of , has "a handful" of financial services clients, Chopra said, declining to disclose specifics. Most of those clients use Devron's tech for financial spend analysis to proactively offer customers promotional offers or banking products, as well as detecting fraud across separate transactional systems, Chopra said.

The fintech navigates data-privacy regulations and technology headaches stemming from data movement by bringing the algorithms to the data instead of the data to the algorithms, Chopra said. Most firms will extract or copy data and send it to the application where the algorithm crunches numbers for analysis. Devron's product relies on sending the algorithm to the application where the data resides, and using AI models that pull in relevant data and create customer profiles.

The newly created customer profiles are then removed from the application where the data resides, and can be combined with similar profiles from other applications, Chopra said. The algorithms are also removed from the databases after creating the profiles.