Financial Services

See how SparkCognition's work with artificial intelligence and new technologies impacts the financial services industry.

  • The Darwin Difference: Why Darwin Stands Out From the AutoML Pack

    The Darwin Difference: Why Darwin Stands Out From the AutoML Pack

    Darwin™️ is an automated model building product that allows you to go from data to model in less time than traditional methods, enabling the rapid prototyping of scenarios and extraction of insights.

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  • Use Case: A Full Framework for Automated Loan Processing

    Use Case: A Full Framework for Automated Loan Processing

    With AMB, lenders can expect an increase in loans offered, with optimized interest pricing and lower defaults, and a forecasted 20% ROI.

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  • Customer Success Story: Predicting Customer Complaints for Telecom

    Customer Success Story: Predicting Customer Complaints for Telecom

    With the power of NLP and auto ML a major telecom provider expects to reduce complaint call volume by 33%, all while increasing brand loyalty.

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  • Darwin Demo: Fraud Detection4:24

    Darwin Demo: Fraud Detection

    This video shows how Darwin, an automated model building tool, empowers data scientists by using historical data sets to build a model that detects fraudulent transactions.

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  • Darwin Demo: Predicting Insurance Pricing3:40

    Darwin Demo: Predicting Insurance Pricing

    This video shows how Darwin, an automated model building tool, empowers data scientists by using historical data sets to build a model that predicts insurance pricing.

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  • Darwin Demo: Predicting Customer Churn4:10

    Darwin Demo: Predicting Customer Churn

    This demo shows how Darwin creates a machine learning model to predict customer churn.

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  • Darwin Demo: Automated Loan Approval3:56

    Darwin Demo: Automated Loan Approval

    This video shows how Darwin, an automated model building tool, empowers data scientists to build a model that lending institutions can use to understand their customer base and better price loans.

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  • How to Maximize ROI From AI in Finance: Banking, Investing, and Insurance

    How to Maximize ROI From AI in Finance: Banking, Investing, and Insurance

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  • Use Case: Preventing Customer Churn for Retail Banks

    Use Case: Preventing Customer Churn for Retail Banks

    As competition, banks are expected to lose revenue due to customer churn. Natural language processing and automated machine learning generate insights into why customers churn and how to retain them.

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  • Use Case: Predicting Financial Market Regimes with AI

    Use Case: Predicting Financial Market Regimes with AI

    The ability to more accurately predict market volatility, price changes, and price change directions comes with AI. To find the best possible methodology, one investment and trading company staged an

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  • Use Case: Optimizing Energy Trading with Machine Learning

    Use Case: Optimizing Energy Trading with Machine Learning

    Utilities need to accurately forecast pricing for whole sales and retail markets to provide competitive offerings. Machine learning solutions allow utilities to move beyond the traditional approach.

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  • Use Case: Alternative Data for Investment Management

    Use Case: Alternative Data for Investment Management

    From hedge fund managers to mutual funds and even private equity managers, alternative data has the power to improve valuation of securities and boost the clarity of the investment process.

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  • Predicting Customer Insurance Costs with Artificial Intelligence2:59

    Predicting Customer Insurance Costs with Artificial Intelligence

    Predict customer insurance costs using machine learning. Darwin builds neuroevolution tailored models that reduce the amount of tie spent building and maintaining models. Darwin. Automated Model

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  • Customer Success Story: KYC Process Automation for Banking

    Customer Success Story: KYC Process Automation for Banking

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  • Why AI is Now Ready to Reach its Full Potential2:18

    Why AI is Now Ready to Reach its Full Potential

    Why AI is Now Ready to Reach its Full Potential.Now in its third wave, why is artificial intelligence only now truly disrupting the way we approach problem-solving? Usman Shuja of SparkCognition

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  • White Paper: Extracting Value from Financial Documents

    White Paper: Extracting Value from Financial Documents

    Financial institutions are saddled with huge amounts of documentation. According to Oracle, only 20% of all generated data is structured data, formatted to be easily understood by machines. The rest

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  • TM17 - "AI in Finance" - Moiz Kohari17:24

    TM17 - "AI in Finance" - Moiz Kohari

    TM17 - "AI in Finance" - Moiz Kohari. After stating, “Data is the most important commodity we have,” Kohari addressed how siloed data can lead to inefficiencies and time and money spent reconciling.

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  • TM17 - "The Future of Finance" - Rumi Morales15:24

    TM17 - "The Future of Finance" - Rumi Morales

    TM17 - "The Future of Finance". Morales noted that while most people in the finance industry think that AI will disrupt their business, few are investing in it. She explored the ways AI will be

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  • Cognitive Computing Market: Escalating Investments in Big Data Analytics to Bolster Opportunities

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  • Global Personal Artificial Intelligence And Robotics Market 2017 Overview by Key Finding, Scope, Top Impacting Factors, Investment Pockets,

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