The consistently evolving BFSI industry is data-driven, which stores huge volumes of unstructured information, most of which is not utilized properly. With the introduction of AI, machine learning, and other advanced analytics, banking institutes are now able to tap into the unstructured data that provides them with key insights about the consumers. Progress in big data and analytics has led to the emergence of new products, services, and solutions. Moreover, after the integration of machine learning with these services and solutions, the banking and financial services have become agiler and smarter. Additionally, fraud detection helps in identifying patterns in clustered data and has the ability to differentiate fraudulent activity from normal activity. Machine learning is also used to provide personalized product offering based on the patterns recognized from the user activities, which eventually leads to customer retention. The major applications of BFSI using machine learning include fraud and risk management, customer segmentation, sales and marketing campaign management, investment prediction, digital assistance, others (compliance management and credit underwriting).

Last updated on: Dec 5, 2019

Machine Learning Software

  • 1

    IBM Watson machine learning software helps enterprises to use their data to create, train, and deploy self-learning models. It also helps users in building analytical models and neural networks. IBM data science experience is a cloudbased, social workspace that helps data professionals to consolidate, create, and collaborate across multiple open sources tools, such as R and Python. The company's machine learning software makes it easy and cost-effective for the users to implement AI and machine learning assets in public, private, hybrid or multicloud environments. It facilitates the users to decentralize and distribute their model training by using Apache Spark to train machine learning and deep learning models on structured and unstructured data, whether it resides in relational databases, Hadoop and object storage.

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    • Enterprise
    • New York, USA
    • Founded: 1911
    • $50BN to $100BN
    • 1,00,001 to 5,00,000
  • 2

    SAS best machine learning software offers major features like automated model tuning, powerful data manipulation and management, flexible web-based programming environment, integrated text analytics, model assessment and scoring, and modern statistical, data mining, and machine-learning techniques. Their best machine learning software facilitate the end-to-end data mining and machine learning process with a visual and programming interface. It also boosts analytics teams of all skill levels with a simple yet powerful and automated way to tackle all tasks in the analytics life cycle.

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    • Enterprise
    • North Carolina, USA
    • Founded: 1976
    • $1BN to $5BN
    • 10,001 to 15,000
  • 3

    Azure Machine Learning is a fully managed best machine learning software service for advanced analytics in the cloud. It enables enterprises to build advanced analytic web services quickly and eradicate much of the heavy lifting associated with deploying machine learning in modern data-driven applications.

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    • Enterprise
    • Washington, USA
    • Founded: 1975
    • More than $100 BN
    • 1,00,001 to 5,00,000
  • 4

    Google engine can perform large scale training on a managed cluster and can also manage the trained models for large scale online and batch predictions. Major features of Google Cloud AutoML Machine Learning Software include portable models, notebook developer experience, scalable service, managed service, HyperTune, and the ability to discover and share samples. The company's Advanced Solutions Lab (ASL) supports businesses to partner with Google Cloud and apply machine learning software to tackle high-impact business challenges. The solution offers a unique opportunity for technical teams to understand from Google’s machine learning software experts.

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    • Enterprise
    • California, USA
    • Founded: 1998
    • More than $100 BN
    • 75,001 to 1,00,000
  • 5

    SAP's Machine Learning Software Foundation offers instantly consumable services, such as image processing, natural language processing, and tabular and time-series processing that help enterprises to learn from data, extract knowledge, and gain new insights. It helps organizations to incorporate intelligence into enterprise applications, without massive computing or data scientists. SAP's Conversational AI helps in developing bots that truly understand humans quickly, and easily. And it also includes off-the-shelf customer support bot for specific industries.

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    • Enterprise
    • Weinheim, Germany
    • Founded: 1972
    • $10BN to $50BN
    • 75,001 to 1,00,000
  • 6

    Amazon Machine Learning Software Amazon Forecast eases the job of obtaining predictions for user’s application using simple APIs without the need to implement custom prediction generation code or handle any infrastructure. It is considered to be highly scalable, and has the ability to generate billions of predictions on a daily basis and can serve those predictions in real time and at a high throughput as well. Amazon's best machine learning software helps in improving the quality of healthcare, fight human trafficking, provide better customer service, and protect users from fraud. Amazon's Machine Learning Software for Telecommunication industry helps the users in implementing frameworks end-to-end ML process on the AWS Cloud using Jupyter Notebook.

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    • Enterprise
    • Washington, USA
    • Founded: 1994
    • More than $100 BN
    • 5,00,001 & more
  • 7

    Baidu has developed best machine learning softare algorithms for voice and image recognition, as well as natural language processing, to help provide smarter, more useful, and more personalized search results. Baidu makes its technology available to other companies to develop their algorithms and applications. The company has made most of its software and systems open source and provided access to it on an “as-a-service” basis. Baidu’s open source deep learning platform, PaddlePaddle supports neural network architectures, including convolutional neural networks and recurrent neural networks. The platform is fully scalable and is designed to enhance mathematical operations using BLAS libraries, including Intel MKL, ATLAS, OpenBLAS and cuBLAS.

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    • Startup
    • Beijing, China
    • Founded: 2000
    • $10BN to $50BN
    • 45,001 to 50,000
  • 8

    The major business functions where FICO uses AI and best machine learning software are financial crimes, marketing, cybersecurity, customer management, threat detection, and strategic planning. FICO has more than 130 patents in analytics and decision management technology, including 70 in AI. FICP has introduced new explainable artificial intelligence toolkit (xAI Toolkit) which meets customers’ increasing demand for industry-leading artificial intelligence. This solution enhances decision performance by integrating predictive and prescriptive models directly into real-time business operations to create faster, more impactful business outcomes. It also offers Intuitive end user experience and delvers direct and immediate access to data and insights dynamically.

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    • Enterprise
    • California, USA
    • Founded: 1956
    • $500MN to $1BN
    • 1,001 to 5,000
  • 9

    Oracle's best machine learning software enable data scientists and analysts to work in collaboration to explore their data visually and design new analytical methodologies in the Autonomous Data Warehouse Cloud. Oracle's optimum, parallel and scalable in-Database implementations of best machine learning software algorithms are exposed via SQL and PL/SQL using Apache Zeppelin-based notebook technology. The company's best machine learning software notebooks facilitate teams to collaborate to build, assess, and deploy machine learning solutions, while improving data scientist productivity. They also focus on ease of use and simplified machine learning software for data science from preparation through deployment all in the Autonomous Database.

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    • Enterprise
    • California, USA
    • Founded: 1977
    • $10BN to $50BN
    • 1,00,001 to 5,00,000
  • 10

    Dell EMC is designed to meet customer needs no matter what they are in their Artificial Intelligence (AI) journey. It delivers a strong portfolio of modern infrastructure and AI-enabled IT solutions, including dedicated AI consulting services. Dell EMC solutions allow technology firms to start small and grow according to their AI use cases, expertise and business goals. Dell Precision workstations support in deploying and managing cognitive technology platforms, including Machine Learning (ML) Software, Artificial Intelligence (AI) and Deep Learning (DL). Dell Precision Optimizer uses Machine Learning Software developed on new, powerful Dell Precision workstations to enhance system reliability with automated updates and provide analytics to address bottlenecks.

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    • Enterprise
    • Texas, USA
    • Founded: 1984
    • $50BN to $100BN
    • 1,00,001 to 5,00,000
  • 11

    With Sparkling Water, users can drive computation from Scala/R/Python and utilize the H2O Flow UI. Recently, the company introduced Driverless AI, which helps to prepare data, calibrate parameters, and determine the optimal algorithms for tackling specific business problems with machine learning software. Furthermore, it automates feature engineering, the process by which key variables are selected to build a model.

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    • Enterprise
    • California, USA
    • Founded: 2012
    • Below $10 MN
    • 101 to 500
    • Startup
    • Zurich, Switzerland
    • Founded: 2008
    • Below $10 MN
    • 1 to 50
    • Startup
    • New York, US
    • Founded: 2013
    • $11MN to $50MN
    • 101 to 500
    • Startup
    • Massachusetts, US
    • Founded: 2006
    • $11MN to $50MN
    • 51 to 100
    • Enterprise
    • San Francisco, California, US
    • Founded: 2010
    • Below $10 MN
    • 51 to 100
    • Enterprise
    • California, USA
    • Founded: 2000
    • $500MN to $1BN
    • 1,001 to 5,000
    • Enterprise
    • California, USA
    • Founded: 1997
    • $1BN to $5BN
    • 5,001 to 10,000
    • Startup
    • California, USA
    • Founded: 2013
    • Below $10 MN
    • 101 to 500
    • Enterprise
    • California, USA
    • Founded: 1979
    • $1BN to $5BN
    • 10,001 to 15,000
  • 20

    The Cambridge based company Luminoso combines natural language with artificial intelligence to analyze text-based data. The machine learning software is the perfect example of no-code text analytics. The software can analyze any text-based data from call transcripts, open-ended survey responses, product reviews, chatbot or live chat transcripts, emails, articles, to NPS open-ends. It can process data in 15 languages including Korean, Chinese, English, Dutch, Italian, German, French, Russian, Swedish, Portuguese, Spanish, Arabic and Japanese.

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    • Startup
    • Massachusetts, US
    • Founded: 2010
    • Below $10 MN
    • 1 to 50

Machine Learning Software in BFSI Quadrant

Comparing 38 vendors in Machine Learning Software across 114 criteria.

Find the best Machine Learning Software solution for your business, using ratings and reviews from buyers, analysts, vendors and industry experts

EVALUATION CRITERIA

Below criteria are most commonly used for comparing Machine Learning Software tools.
  • Breadth and Depth of Product Offerings
    • Products/Solutions Offered
    • licenses
    • Services
      • Professional Services (Consulting & Training)
      • Managed services (Support & Maintenance)
    • Organization Size
      • Small and Medium sized Enterprise
      • Large Enterprises (Revenue> 500 Million)
  • Product Features and Functionality
    • cutomer satisfaction
    • Types of Offerings
      • Software Tools
      • Platform
      • Services
    • Product Features
      • Data visualization and exploration
      • Model Evaluation and Interpretation Tools
      • Modeling APIs
      • Machine Learning Algorithms
      • Model assessment and scoring
      • APIs for Batch and Real-time Predictions
      • Data Transformations
  • Focus on Product Innovation
    • Product Innovation
    • R&D Spend
    • New Product Developments
      • Product Upgradation
      • New Product Launches
  • Product Differentiation and Impact on Customer Value
    • Customer Feedback Frequency
    • Solution Scalability
  • Product Quality and Reliability
    • Level of Support
    • Customer Redressal Mechanism/Program
    • services
      • Technical Support
      • Customer Support
      • Sales Support
      • Others, please specify
    • Pre Sales Support
      • Software Requirement Specification (SRS)
      • Product Demos
      • Proof of Concept
      • Dedicated Account Manager (DAM)
    • Channel for Delivery of Support Services
      • On-Site Support
      • Remote Support

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Marie Stelle

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