Fintech

While predictive algorithms are now found in most fintech processes — from marketing to underwriting — a challenge has risen to determine the future of the industry. The need to integrate seamlessly with marketers, underwriters, financial analysts and other fintech professionals will force machine learning platforms working in fintech to do more than just pump out predictions: they have to drive results.

Discover how automated machine learning is driving the fintech revolution.

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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 machine learning initiatives. DataRobot enables Fintech users and companies to build and deploy highly accurate machine learning models in a fraction of the time.

DataRobot in the News

FinTech Finance: FinTech Connect Live 2017, Justin Dickerson Video Interview

Jan 30, 2018
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The Fintech Times: DataRobot – The Leader in Automated Machine Learning and AI

Jan 19, 2018
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Banking Technology: Fintech Connect Live 2017 – The Unleashing of AI and ML

Jan 05, 2018
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FinancialPlanning: In|Vest 2017 – DataRobot Live Demo

Aug 23, 2017
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Our expert says:

“Fintech is exciting. It’s truly a disruptive force in the economy. As the interaction between consumers, businesses, and financial institutions becomes frictionless, there are significant opportunities for fintech organizations to use predictive models. Automated machine learning allows fintech companies to create simpler and more accurate underwriting models, detect fraud in their workflows, and find the right customers for their products.” – Justin Dickerson, DataRobot’s General Manager of 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.

Blockchain

Cryptocurrency and distributed ledger technology is one of the most exciting developments in fintech. Blockchain technology is still in early development, which makes it an ideal candidate for machine learning solutions. These early use cases include detection of identity theft, cyber-attack, and fraudulent and illicit blockchain transactions. DataRobot is flexible enough to allow blockchain-focused companies to build models that detect all these threats in real-time.

DataRobot Helps Fintechs With:

Credit Card Fraudulent Transactions

The cost of credit card fraud is billions of dollars per year. By accurately predicting which transactions are likely fraudulent, banks can significantly reduce illegal transactions while providing cardholders with excellent customer experience.

Blockchain

As a relatively new financial system, blockchain is particularly vulnerable to security threats. Build and deploy machine learning algorithms that can detect anomalous behavior anywhere along the chain.

Credit Default Rates

Individuals or businesses often need loans. Making accurate judgments on the likelihood of default is the difference between a successful and unsuccessful loan portfolio.

Digital Wealth Management

Machine learning algorithms help digital wealth advisory companies automate many portfolio management services to be more efficient and effective.

Direct Marketing

To maximize ROI, it’s important to boost marketing response rates and minimize misdirected communication. The most up-to-date modeling algorithms return the best results, but the data science expertise required to implement them is difficult to come by.

 
Stefan Hansel
Stefan Hansel
Senior Manager of Risk, Avant
Avant is an online lending platform that is the leading provider of credit alternatives to middle income consumers in the US & UK. Avant offers its technology solutions to bank and non-bank partners via its “Powered By Avant” product to provide an innovative digital lending experience to their customers.

What our Customers in Fintech Say:

  • "At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource."

    Akshay Tandon
    Akshay Tandon

    VP of Strategy and Analytics, LendingTree

  • "DataRobot allows us to understand the data that’s being fed into our models without blindly feeding whatever we get into our system. DataRobot makes my team very effective."

    Deena Narayanaswamy
    Deena Narayanaswamy

    Head of Data Insights, Avant

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