New services and accelerators move AI projects into the fast lane for swift ROI and material business impact
Demand for Artificial Intelligence (AI) expertise and technologies is being driven by compelling business value from across industries. Teradata
, the leading data and analytics company, is helping clients capitalize on the power of AI to deliver high value business outcomes in the areas of fraud detection, manufacturing performance optimization, risk modelling, and precision recommendation engines.
To help clients accelerate their AI initiatives, Teradata leads with data science acumen and deep learning algorithms that significantly outperform most rules-based and machine learning approaches. For example:
- Danske Bank worked with Teradata to create and launch a state of-the-art, AI-driven fraud detection platform expected to meet 100 percent ROI in its first year of production. The engine uses deep learning to analyze tens of thousands of latent features, scoring millions of online banking transactions in real-time to provide actionable insight regarding both true and false fraudulent activity. By significantly reducing the cost of investigating false-positives, Danske Bank increases its overall efficiency and is poised for substantial savings.
- A mobile services provider is using deep learning and natural language processing techniques to apply 300+ routine response types to manage customers’ common questions in two languages, and automating routine queries at a much lower cost so human agents can focus on complex requests that require more personal customer attention.
- A major shipping/logistics distributor now uses AI for image matching techniques that reduce costly “lost package” resolution time, saving the business $25 million a year – a significant return on an initial AI investment.
- A government postal service organization now uses AI-driven image recognition and deep learning processes to improve the sorting of over 115 million parcels a year, resulting in valuable operational efficiencies that reduce sorting time and radically lower cost.
“Teradata can help companies to get started now in AI. Our offerings are delivered by hands-on consulting services teams of data scientists with expertise in deep learning techniques such as convolutional neural networks, generative adversarial networks, and recurrent neural networks,” said Rick Farnell, Senior Vice President, Think Big Analytics, a Teradata Company. “Teradata teams also apply open source innovation to drive business value, including TensorFlow, Keras, and Caffe.”
Setbacks in deploying AI are often caused by such issues as identifying appropriate AI use cases, technical bottlenecks integrating open source tools and special hardware, and operationalizing and supporting autonomous decisions. Notably, a recent Teradata survey found that 91 percent of IT and business decision makers foresee barriers to AI realization.*
Companies seeking to invest in AI will benefit from Teradata services and accelerators – and find that with Teradata analytics expertise and repeatable practices, they can quickly overcome these challenges and operationalize AI. Today, Teradata is introducing new services that enable the delivery of faster business results and lower implementation risk from AI, including:
- AI Strategy Service – Review enterprise capabilities and recommend top AI use cases aligned to business strategies.
- AI Rapid Analytic Consulting Engagement – Gives clients insight into the potential business value of analytic solutions before an investment is made through proof of value.
- AI Foundation Service – Builds and deploys a Deep Learning platform through a collaborative client engagement. This service integrates data sources, models and business processes.
- AI Analytics-as-a-Service – Designs and oversees mechanisms to optimize and improve existing business processes using AI. Teradata manages an iterative, stage-gate process for analytic models from development to handover to operations.
Teradata is also introducing AI “accelerators” composed of best practices, code, IP, and proven design patterns to help accelerate deployment of AI solutions and ensure quick ROI.
- AnalyticOps Accelerator – provides an end-to-end framework to facilitate the generation, validation, deployment, and management of deep learning models at scale. This accelerator is available now.
- Financial Crimes Accelerator – uses deep learning to detect patterns across retail banking products and channels such as credit card, debit card, online, branch banking, ATM, wire transfer, and call centers. Continuously monitors and thwarts fraudulent schemes used by criminal actors to exploit the system, leading to quick time to value. This accelerator is being deployed in Q4, and will be available more broadly in the first quarter of 2018.
Forrester Research recognizes the rising demand for contextual insights and new business opportunities from AI: “Artificial intelligence technologies will be rapidly assimilated into analytics practices, giving business users unprecedented access to powerful insights that drive action.” Forrester says this phenomenon is “driven by the business’ voracious appetite for deeper contextual insights that drive customer engagement via mobile and the IoT. These trends represent the beginning of an insights revolution that will kick-start a strategic move among many firms to become insights-driven businesses…Those that are truly insights-driven businesses will steal $1.2 trillion per annum from their less-informed peers by 2020.” **
Teradata’s new AI services and accelerators are being showcased this week at the Teradata PARTNERS Conference in Anaheim, where attendees can learn more by visiting the Teradata exhibit. In addition, the conference offers sessions by leading AI analysts and practitioners who will present AI use cases and address current trends.
*---- The State of Artificial Intelligence for Enterprises
, Teradata, October 11, 2017
**--- Forrester Predictions 2017
: Artificial Intelligence Will Drive The Insights Revolution: Advanced Insights Will Spark Digital Transformation In The Year Ahead, by James McCormick, November 2, 2016
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