As a leading Data Scientist and Machine Learning Expert, Dwipam Katariya serves US customers by safeguarding some of their most sensitive information: their finances. Not only does the algorithmic work he does enhance security measures throughout the field, but it also improves the customer experience.
Working on the customer intent prediction team, Dwipam researched and benchmark a state-of-the-art recommender model framework. This framework relies on clickstream data to assess the digital behavior of customers and bolsters that information by looking at offline customer transaction history. This system promises to reduce 21% identity fraud in real time and improves customer identity resolution. This reduction ensures customer peace of mind and can save the FinTechs themselves millions per year in fraud costs.
Dwipam Katariya’s framework was published at the International Conference in Machine Learning, one of the most renowned and elite machine learning conferences in the world. The conference had less than a 25% acceptance rate during the year that the Machine Learning Research was shared there, making this feat even more impressive than it already was.
Dwipam’s contributions go even further; he led a Machine Learning research agenda committed to making the customer experience tailored and information-rich. His team supports a model that is constantly being refined to timely personalize financially-relevant information and important messages to customers based on their financial situation. This model services millions of US customers, which helps them manage their finances with ease and pulls insights from their transaction history.
Before his current role, Dwipam did not work in the financial services field at all. Instead, he supported an on-demand manufacturing company that serves major multinational businesses and US government organizations for their manufacturing needs. When a customer needs something produced, they contact the organization via their website, get a pricing quote, and finally place an order to get made.
Accurately pricing quotes is critical for the business’s success; if a quoted price is too low, the product becomes unprofitable but if it’s too high, they risk losing customers. Dwipam developed a machine learning solution that accurately priced manufacturing parts within seconds, improving the organization’s approach to pricing and ramping up its ability to accelerate revenue.
When used correctly, data is so powerful. Businesses that fail to use data in the right ways are leaving money on the table, shorting the experience their customers can have, and losing market share to more technologically advanced organizations. We live in an age where data is all around us, but it’s people like Dwipam that turn that data into something useful and actionable.
Dwipam is not only a leading scientist with a unique experience in Machine Learning but is also a seasoned inventor credited with multiple patents in his field. As, a member of IEEE, Harvard Square, IAENG, IFIA, and SAS society Dwipam networks with other brilliant minds in data science to stay current on new developments in his industry and use those advancements to add value wherever he is. He also mentors other AI and ML professionals, peer reviews machine learning research papers for Data Science Journal(DSJ) at codata.org, and even writes scholarly articles for world-renowned and most-read publications such as Towards Data Science and Analytics Vidya.
