Remove Analytics Remove Customer Experience Remove Education Remove Financial Services
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Conversational AI use cases for enterprises

IBM Big Data Hub

Predictive analytics integrates with NLP, ML and DL to enhance decision-making capabilities, extract insights, and use historical data to forecast future behavior, preferences and trends. ML and DL lie at the core of predictive analytics, enabling models to learn from data, identify patterns and make predictions about future events.

Analytics 100
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The most valuable AI use cases for business

IBM Big Data Hub

There’s no need to make customers wait for the answers to frequently asked questions (FAQs) or to take the next step to purchase. And digital customer service agents can boost customer satisfaction by offering advice and guidance to customer service agents.

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Protecting the bank in a digital world

CGI

As financial services organizations are learning, defences against financial crime must be joined up and layered, bringing together both operational and intelligence resources. Customer experience (balancing against risk). Education and attitude (in terms of regulatory compliance and encouraging whistle blowers).

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Tuesday’s Relativity Fest 2019 Sessions: eDiscovery Trends

eDiscovery Daily

It has provided a framework for the development of software and services. In the increasingly non-linear and fast-moving legal technology world in which we now live and work, where cloud-based solutions, analytics, machine learning, and AI are impacting the data-driven decisions being made, is it time to rethink the EDRM?

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Infosource Global Capture & IDP Vertical Market Analysis 2022-2023 Update

Info Source

The Finance sector, led by Banks and Financial Institutions, has been at the forefront of embracing technologies. We expect this sector to be at the forefront of embracing Advanced AI technologies to further enhance customer facing processes with a strong focus on Customer Experience.