As global customer markets rapidly become more sophisticated and accustomed to utilizing cognitive technology in their everyday lives, the customer of tomorrow will not only expect smarter and faster service delivery, but highly intelligent and personalized self-service options will soon become a necessity. As such, enterprises world-wide are under pressure to advance their business operations to keep up with this market trend.
Performance and consistency in business can only be created with innovation and inspiration. TransUnion recently worked with us to produce a tremendous Nexidia Analytics success story, where they worked first to meet the Four V's of Big Data, but then they challenged NICE Nexidia to meet the same criteria from the standpoint of data analysis.
Ahead of their participation in the Advanced Analytics and Intelligent Automation for Insurance Conference, we spoke with Hiek Van Der Scheer, Chief Analytics Officer, Aegon and Deepak Nagappan Anitha, Analytics Solutions Manager, Direct Line Group Digital to explore the methods they have adopted to identify the projects that will deliver the greatest ROI from analytics technologies.
Download this piece to learn about:
- How to ensure you identify and select advanced analytics and intelligent automation projects that will present the biggest return
- How do you ensure your pilot projects are a success
- What is the best method of building the business case and securing leadership buy-in
Intelligent automation is increasingly being used by insurers as a way to streamline processes and improve customer satisfaction. However, effective implementation of these technologies needs considerable planning before execution. This infographic will take you through six key considerations that are needed before you can truly embrace intelligent automation, including:
- How to establish compelling and transparent key success factors
- How do develop your people capabilities before implementation
- Assessing if collaboration with disruptors is likely to be beneficial
In this ebook we interview a selection of industry experts familiar with the technology to gain insight into the lessons learnt from their experiences with machine learning.
Over 70 per cent of banking and financial markets firms say that information and analytics is creating a competitive advantage for their organizations. Are you falling behind in leveraging data to improve customer experience and revenue growth? Download now to understand why.
Find out if your competitors are facing the same challenges as you? This infographic highlights 6 key challenges faced by Data, Analytics, Underwriting and Business Leaders in the Insurance Sector. Some, maybe all, may sound familiar. The infographic highlights such challenges as how to transform a conservative risk adverse culture to become data driven and how to understand exactly what your customer’s wants. It also shows how the Insight and Analytics in Insurance Summit will help address these challenges.
Ahead of the 2017 Big Data Analytics for Insurance Conference, we speak to a selection of experts to uncover the 9 ways to use data to aid competitive advantage in the insurance industry.
With around six months to prepare for GDPR, this article explores how insurers should now be looking not only at how to ensure compliance, but also leverage GDPR to advance their business and meet the rising demands of the consumer.
In an increasingly competitive industry, insurance firms have to operate more efficiently, provide exceptional customer service and utilise the latest technologies. Leveraging data analytics offers insurers the ability to refine these processes and meet growing customer demands and regulatory requirements. CX Network spoke exclusively with Javier Rodriguez, Head of Data Science and Dani Sola, Head of Data Engineering, Simply Business about the 6 key ways that data is transforming the insurance industry.
The insurance sector has traditionally been fairly risk averse when it comes to new technologies due to the nature of the industry. But in the race to cut through the noise, comprehend and utilise the data lakes produced by the ever advancing digital climate, many in the insurance industry are joining the trend of machine learning. In this article we will explore case studies from four individuals familiar with the technology to gain insight into the lessons learnt from their experiences with machine learning.