BIG DATA MANAGEMENT

RepRisk and J.P. Morgan Collaborate to Provide Better Access to ESG Data

RepRisk | November 09, 2020

RepRisk, a main ESG data science firm consolidating AI and human knowledge, today reported it is working with J.P. Morgan to offer front-office chiefs admittance to ESG hazard data through J.P. Morgan's flagship multi-resource data and analytics platform, DataQuery.

RepRisk offers quantitative danger analytics and proprietary measurements for public and private companies from each area and market over the globe, serving driving monetary establishments and corporates in their ESG joining and danger the board processes across operations, business relationships, and ventures.

“We are thrilled to be the latest addition to DataQuery as it further expands and evolves its valuable access to ESG risk data,” said Alexandra Mihailescu Cichon, Executive Vice President Sales and Marketing at RepRisk. “RepRisk systematically identifies and assesses material ESG risks, providing actionable market insights for industry professionals. Offering our data via J.P. Morgan’s DataQuery will provide users with risk-focused data for risk management, portfolio optimization, and alpha generation. Additionally, it marks the growing momentum of ESG integration in the industry as a whole.”

DataQuery is J.P. Morgan's multi-resource data and analytics application for institutional customers. The platform highlights proprietary monetary market data from the bank's driving Research and Trading organizations and is developing with the expansion of confided in providers in its data marketplace. DataQuery provides customers with chronicled time arrangement capabilities, market observing, progressed representations, and data extraction across channels. RepRisk's comprehensive ESG dataset will be accessible for consumption over the entirety of DataQuery's customer confronting channels, offering admittance to material ESG hazard data for more than 150,000 companies.

Richard Crozier, Head of Product for Data and Analytics at J.P. Morgan's Securities Services, remarked, "In an ever progressively data-driven world, offering customers the decision of best-of-breed data providers through a consistent experience is critical. We are eager to have RepRisk on the DataQuery platform, permitting us to present a smoothed out route for customers to incorporate ESG factors into their venture methodologies." Today's declaration is part of J.P. Morgan's dedication and methodology to convey the requirements of purchase side customers by providing customers admittance to a selection of arrangements over the venture lifecycle, incorporating front office capabilities in data, analytics, and hazard.

About RepRisk

Founded in 1998 and headquartered in Switzerland, RepRisk is a pioneer in ESG data science that leverages the combination of AI and machine learning with human intelligence to systematically analyze public information and identify material ESG risks. RepRisk’s flagship product, the RepRisk ESG Risk Platform, is the world’s largest and most comprehensive due diligence database on ESG and business conduct risks, with expertise in 20 languages and coverage of 150,000+ public and private companies and 35,000+ infrastructure projects. For more than a decade, the world’s leading financial institutions and corporations have trusted RepRisk for due diligence and risk management across their operations, business relationships, and investments.

Spotlight

Global network access/Connectivity trends (Fixed/Mobile/Wi-Fi) Traffic from wireless and mobile devices will account for 71 percent of total IP traffic by 2022. By 2022, wired devices will account for 29 percent of IP traffic, and Wi-Fi and mobile devices will account for 71 percent of IP traffic. In 2017, also, wired devices accounted for less than half of the global IP traffic, at 48 percent. Globally, mobile data traffic will increase sevenfold between 2017 and 2022. Mobile data traffic will grow at a CAGR of 46 percent between 2017 and 2022, reaching 77.5 exabytes per month by 2022. Global mobile data traffic will grow nearly twice as fast as fixed IP traffic from 2017 to 2022. Fixed IP traffic will grow at a CAGR of 24 percent between 2017 and 2022, while mobile traffic grows at a CAGR of 46 percent. Global mobile data traffic was 9 percent of total IP traffic in 2017 and will be 20 percent of total IP traffic by 2022.


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DATA ARCHITECTURE

Linq Analytics Extends Master Data Management and FP&A Capabilities

Linq Analytics | January 18, 2022

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BIG DATA MANAGEMENT

Dashbot Launches Conversational Data Cloud™ to Provide a Centralized View of All Chatbot Data

Dashbot | July 04, 2022

Dashbot, a conversational AI and data platform, today announced the launch of its proprietary Conversational Data Cloud™, letting customers build and optimize their chatbots from their businesses’ own conversational data. Dashbot’s Conversational Data Cloud™ turns unstructured, noisy, interrelated and often tangled conversational data into immediate action. Across an ever-increasing number of communication channels (contact centers, support tickets, social media, IVR, live chat, etc), a business can get up to three million customer messages per day. The pandemic has significantly accelerated this flood of customer communications. In addition, the complexity of human language makes it impossible to predict every way users will speak with bots. As a result, over 50% of chatbot sessions fail. Optimizing existing bots can reduce failure rate by up to 35% and reduce escalation rate by up to 57%. Dashbot’s Conversational Data CloudTM enables businesses to: Centralize all conversational data including chatbot transcripts, Zendesk, email and live agent voice calls. Decipher tens of thousands of daily conversations and transcripts. Group similar messages and topics to determine areas of failure and opportunities for new use cases, leveraging its proprietary machine learning algorithms. “We’re expanding beyond reporting and analytics to be able to ingest raw conversational data which can be difficult, but also very valuable for our customers,” said Andrew Hong, CEO of Dashbot. “We’re on a mission to decipher language, which is one of the most complex types of data that has ever existed. We listened to our customers that are challenged to make sense of all their conversational data, so we built our Conversational Data Cloud™ to help businesses automate, analyze and optimize their conversation channels.” Dashbot’s Conversational Data Cloud™ is powered by three core features: Transcript Transformer: Ability to search and categorize thousands of daily transcripts DashbotML: State of the art machine learning models hypertuned from over 10 billion conversations. Topic Modeling to visualize flow and conversation loops. Phrase clustering (message grouping) to identify new use cases and unhandled topics. Automated Training Data: Export messages as training data to optimize NLP model. One Dashbot customer example is Intuit. With QuickBooks Assistant having so much unstructured data, they were spending days trying to manually identify mishandled or unhandled intents. In turn, their customers were getting annoyed with inaccurate responses and escalation to a live agent. They were able to leverage Dashbot’s Conversational Data CloudTM to benchmark the current state of their chatbots, and then identify and prioritize the highest impact tactics to improve. About Dashbot Dashbot is a conversational AI and data platform helping businesses to build and optimize their interactive voice response and chatbots. With Dashbot’s Conversational Data Cloud, the company is turning the most unstructured, noisy, interrelated and often tangled conversational data into immediate action. They are the only company to surface patterns with mishandled and unhandled intents to improve NLP engines, leveraging their proprietary Conversational Data Cloud™. Dashbot works with leading enterprises such as Intuit, Expedia, Geico, Google and Travelers, among many others.

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BIG DATA MANAGEMENT

Clarity AI’s Sustainability Data and Capabilities Will Support BlackRock’s Enterprise SFDR Reporting

Clarity AI | June 01, 2022

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DATA ARCHITECTURE

Skyflow Launches Integration to Build Privacy and Data Protection into the Snowflake Data Cloud

Skyflow | June 17, 2022

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Spotlight

Global network access/Connectivity trends (Fixed/Mobile/Wi-Fi) Traffic from wireless and mobile devices will account for 71 percent of total IP traffic by 2022. By 2022, wired devices will account for 29 percent of IP traffic, and Wi-Fi and mobile devices will account for 71 percent of IP traffic. In 2017, also, wired devices accounted for less than half of the global IP traffic, at 48 percent. Globally, mobile data traffic will increase sevenfold between 2017 and 2022. Mobile data traffic will grow at a CAGR of 46 percent between 2017 and 2022, reaching 77.5 exabytes per month by 2022. Global mobile data traffic will grow nearly twice as fast as fixed IP traffic from 2017 to 2022. Fixed IP traffic will grow at a CAGR of 24 percent between 2017 and 2022, while mobile traffic grows at a CAGR of 46 percent. Global mobile data traffic was 9 percent of total IP traffic in 2017 and will be 20 percent of total IP traffic by 2022.

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