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How to Maximize ROI From AI in Finance: Banking, Investing, and Insurance
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.
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
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.
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.
Darwin Demo: Predicting Customer Churn with Artificial Intelligence
Predicting customer churn using machine learning. Darwin. Automated Model Building. Get Insights Faster.
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
Customer Success Story: KYC Process Automation for Banking
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
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
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.
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
Cognitive Computing Market: Escalating Investments in Big Data Analytics to Bolster Opportunities
Global Personal Artificial Intelligence And Robotics Market 2017 Overview by Key Finding, Scope, Top Impacting Factors, Investment Pockets,
AI in Big Data Analytics and IoT Market 2017 In Depth Analysis by Industry Driving Factors, Future Trends, Investment Analysis and Forecast
USAF Plans to Make Future Money Decisions With a Little Help from AI
The Air Force wants to use artificial intelligence to help it make budgetary decisions. The military’s Defense Innovation Unit Experimental (DIUx) awarded Texas-based SparkCognition a $100,000...
In the money July 3: Austin’s largest funding round of 2017, plus cash for the cloud
The Future of Artificial Intelligence: Verticalized Applications, Investment Opportunities, and the Human Intelligence Gap
Austin-Based AI Startup SparkCognition Closes Series B Funding with Boeing and Verizon
Today, we at SparkCognition are thrilled to announce that we have closed an initial $32.5 million series B funding round. The investment is led by Verizon Ventures with key participation...
Increasing Use of Cyber Insurance Requirements in Contracts