Fintech

Use Cases Across Fintech

• Lending

  Fintech has fundamentally altered the lending landscape, and machine learning has shined as a game-changing technology for lenders. From making smart underwriting decisions and reducing friction between lenders and consumers to identifying new customers and reducing the churn of existing customer bases, DataRobot’s automated machine learning platform helps fintech lending organizations make better predictions, faster.

• Payments

  Improvements in the flow of capital across borders is one of the most significant benefits of fintech, allowing businesses and consumers to participate in the financial ecosystem in exciting new ways – but significant challenges remain. Fraud has always been a concern in the banking and payments industries. DataRobot’s automated machine learning platform allows companies to build predictive models to identify payment transactions that need closer human inspection. By deploying machine learning models in real-time production, DataRobot helps companies find bad payments before they cause permanent damage.

• Digital Wealth

  In an industry dominated by personal wealth advisors, fintech has begun to automate the interactions between advisors and consumers in a way that increases transparency and reduces transactional fees. Machine learning will play a major role in the development of the digital wealth market, addressing the need for increased automation of portfolio management as “robo-advisors” begin to interact more frequently with customers. DataRobot’s automated machine learning platform plays a critical role in aligning consumers with the right opportunities to match their risk tolerance and financial profile.