Fintech hero


Fintech organizations, whether launched two years ago or 20 years ago, are all vying for the same thing: RESULTS. In all corners of Fintech — be it payments, investing, lending, digital wealth, personal finance, capital markets or one of the myriad other areas — firms are looking to leverage AI and predictive modeling to increase revenues, grow their customer base, improve efficiency and manage risk. The time is now for Fintech firms to take their business to the next level.

Discover how enterprise AI is driving the Fintech revolution.

DataRobot captures the knowledge, experience, and best practices of the world’s leading data scientists, delivering unmatched levels of automation and ease-of-use for enterprise AI initiatives. From AI in banking, to AI in asset management, to AI in credit risk: DataRobot enables Fintech users and companies to build and deploy highly accurate enterprise AI models in a fraction of the time.

Fintech use cases

Casos de uso na Fintech

DataRobot is popular with fintechs because it can increase modeling efficiency and accuracy while speeding up fintech operations to give them a competitive advantage over established banks and traditional financial services organizations.

  • Empréstimos

    Fintech has fundamentally altered the lending landscape, and machine learning in banking 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 enterprise AI platform helps Fintech lending organizations make better predictions faster.

  • Pagamentos

    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 enterprise AI 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.

  • Gestão de Patrimônio Digital

    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. Artificial intelligence in Fintech 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 enterprise AI platform plays a critical role in aligning consumers with the right opportunities to match their risk tolerance and financial profile.

DataRobot Ajuda Fintechs Com:

  • Transações Fraudulentas com Cartões de Crédito
    O custo de fraude em cartões de crédito atinge bilhões de dólares por ano. Com a predição exata de quais transações têm o potencial de ser fraudulentas, os bancos podem reduzir significativamente as transações ilegais, ao mesmo tempo oferecendo aos portadores de cartões uma excelente experiência como clientes.
  • Taxas de Inadimplência de Crédito
    Individuals or businesses often need loans. Making accurate judgments using machine learning and credit risk assessments to mitigate the likelihood of default can make the difference between a successful and unsuccessful loan portfolio.
  • Gestão de Patrimônio Digital
    Algorítimos de machine learning auxiliam empresas de consultoria de patrimônio digital a automatizarem muitos serviços de gestão de portfólio para se tornarem mais eficientes e efetivas.
  • Marketing Direto
    Para maximizar o ROI, é importante aumentar as taxas de retorno às ações de marketing e minimizar a comunicação mal-direcionada. O modelagem de algorítimos mais atual retornam os melhores resultados, mas a expertise de ciência de dados requerida para implementá-los é difícil de obter.
Pauline McKinney

Vice-Presidente, Análise de dados, Wellen Capital

  • Fintech é estimulante. É uma força verdadeiramente disruptiva na economia À medida que a interação entre consumidores, organizações e instituições financeiras se torna mais harmônica, existem oportunidades significativas para que organizações fintech usem modelos preditivos. Automated machine learning permite que empresas fintech criem modelos mais simples e mais precisos de underwriting, detectem fraudes em seus fluxogramas e encontrem os clientes certos para seus produtos

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