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Gartner Data & Analytics Summit

March 6–9, 2017 at Grapevine, Texas, United States

Solution Provider Session Report

Predictive Analysis Automation: Analytics at the Speed of Business
Ryohei Fujimaki, Ph.D., Research Fellow at NEC Corporation & Mr. Tomohiro Oka, Vice President of IT Innovation Department at Sumitomo Mitsui Banking Corporation

Key Messages

1) Predictive analysis automation disrupts predictive analytics.
2) Anyone can produce as good predictions as talented data scientists in hours.
3) Automation enables continuous delivery of business value by consistently evolving models.
4) Transparent features and models discover deep data insights, and enhance business decisions driven by predictions.

Summary

Self-service predictive analytics: Everyone seeking to expand their business in today’s digitally connected era is talking about it, and everyone recognizes its inherent potential to accelerate business growth. But, to date, the complexities of traditional predictive analytics technologies make it near impossible to create accurate prediction models without a significant amount of time and a strong pool of highly talented data scientists. NEC changes all that with predictive analysis automation, a radical new artificial intelligence (AI) technology with the potential to transform the concept of predictive data analytics, and ultimately the way we do business. How?

  1. Slashing data analysis timeframes from months to hours
    NEC’s predictive analysis automation technology uses AI to dramatically reduce the time required for feature engineering and predictive modeling from months to just hours.
  2. Anyone can do it
    Automation enables businesses to produce high-ROI predictions without talented data scientists. This not only helps alleviate the shortage of data science expertise, but can also help talented data scientists improve the productivity of predictive analytics up to 100 times.
  3. Continuous delivery of business value
    Features and predictive models can be automatically redesigned to reflect changing data, ensuring long-term relevance and continuous value.
  4. Transparent and deep insights
    AI-generated features and predictive models are transparent, providing data insights that help deepen understanding about customers, products, services, and enhance business decisions driven by predictions.

Japanese multinational banking company Sumitomo Mitsui Banking Corporation (SMBC) has already tried NEC’s predictive analysis automation technology to see if it could improve the company’s data analysis, and help identify diversifying customer needs and better products. The new technology was described as “amazing” after it dramatically shortened data analysis timeframes from two or three months to less than one day. It also attained equal or higher levels of accuracy, and provided specific grounds for predictions not available with conventional technologies.

The horizontal, industry-agnostic predictive analysis automation technology is already being expanded across various industries and business operations. The technology is offered as a self-service predictive analytics platform to help businesses with an existing pool of data scientists to optimize the potential of their in-house data and boost data scientist productivity. It is also offered as a managed service, which helps determine appropriate business models, collate data and automate prediction models for integration into business operations, and deliver continuous model accuracy and business value. Whichever way this game-changing technology enters the market, we believe predictive analysis automation can promote efficient, transparent, agile and profitable data analytics, at the speed of business.

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