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Principal Financial unifies IT to lay foundation for growth

CIO

For companies whose business units have traditionally operated independently, centralizing IT operations under one strategy can reap significant benefits — especially when it comes to offering a holistic customer experience and establishing a unified data foundation for leveraging the latest emerging technologies.

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Insurance Technologies: 13 Disruptive Ideas to Change Insurance Companies with Telematics, Blockchain, Machine Learning, and APIs

Altexsoft

Have you ever tried to check your insurance claim status? While some insurance carriers have made significant modifications courtesy of disruptive digitalization (we’ve already discussed this topic in our whitepaper), most companies trail behind. Insurants are not satisfied with their service providers.

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How Machine Learning is Used in Finance and Banking

Exadel

The banking landscape is constantly changing, and the application of machine learning in banking is arguably still in its early stages. Machine learning solutions are already rooted in the finance and banking industry. Machine learning solutions are already rooted in the finance and banking industry.

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The Top 5 Major Advances in the Future of Banking, Financial Services, and Insurance (BFSI) Industry

Perficient

Perficient was honored to participate in the inaugural Banking, Financial Services, and Insurance (BFSI) event hosted by Kofax. With more than 50 financial services and insurance professionals in attendance, this event showcased the industry’s unwavering commitment to practical innovation.

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Express Cloudera POV on 2021 data trends in insurance

Cloudera

We’ve written about the changes forced on the traditionally risk-averse insurance industry by COVID-19. In 2021, with the crisis hopefully fading, insurance will have time to evaluate the changes made in 2020, assessing what worked and what didn’t, and planning a new way forward rather than reacting in real time. .

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Will Data Privacy drive an Enterprise Data Strategy?

Cloudera

The protection and controls around data become increasingly complex when used in the context of banking and insurance activities. Personal and confidential information carries heightened sensitivity in the light of financial, health and insurance activities. Machine learning is proven to help in the fight against fraud.

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Successful RPA implementation to increase productivity up to 30% in the Insurance sector

Trigent

The insurance industry is still exploring ways to leverage its capabilities to their full potential, those who have managed to make inroads are already experiencing extraordinary benefits. Considering that insurance is now an integral part of our lives, the benefits received from RPA adoption are enjoyed by insurers and customers.