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Roadmap important in the race to unlock data value for insurance companies




Insurance companies eager to become computer-driven companies need a comprehensive roadmap for the transformation journey.

Insurance providers that turn into computer-driven companies will outperform their traditional competitors. They release values ​​that are locked into their tasks by improving operational efficiency and company agility. They will also be able to create value by using data to open up a range of new sources of income.

How can insurers become data-driven companies? Investing in digital key technologies to release data value is crucial. Our research shows that the companies that get the most competitive advantage of new technology invest almost all in cloud computing, big data analysis, real-time data, datalakes and artificial intelligence (AI). These technology leaders invest much more in innovation than their less progressive counterparts. They also use new technology much faster. This allows them to quickly scale innovation across their organizations. In addition, they can adapt to sudden threats or opportunities (see the report Future Systems).

But it is not enough to increase investment in powerful cloud services and other digital technologies. Insurers who are eager to become computer-driven companies need a comprehensive roadmap for this journey. It should cover the data strategy (how to unlock value from data assets) and the data transformation process (how to build or buy capacity). Finally, it should identify the business models that drive the data-driven business (how it will deliver value). The journey to becoming a data-driven company goes beyond making money on data. It requires companies to build their operations around data (see picture).

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Each insurance company must draw up a roadmap that addresses their unique circumstances. However, there are some important steps that all carriers should consider.

Data Strategy

• Identify and categorize data assets (eg customer behavior, demographics, risk profiles and telematics).
• Assess quantity, quality, origin of data, age and availability.
• Collected data elements to rate the competitive value of the computer.
• Identify potential suppliers of supplementary data from third parties.

Data transformation

• Combine AI technology with data analysis, automated systems and human knowledge and ingenuity to create solutions to important business problems.
• Master critical data functions such as key performance indicator (KPI), fraud reporting and customer risk profiling.
• Improve organizational trust by implementing an integrated security framework. Also ensure that companies' and legislation's data security, governance and confidentiality requirements are complied with.
• Develop application programming interfaces (APIs) to link data resources to start-ups, brokerage platforms, Internet of Things (IoT) networks and other service providers in an open enterprise ecosystem.
• Change the mindset of company leaders by putting data at the heart of all decision-making.
• Explore data sharing agreements with business partners to encourage greater collaboration.
• Improve data quality and consistency to enable rapid sharing of business, consumer and market interests throughout the organization.
• Integrate data flows throughout the company to improve decision making.

In my next blog post, I discuss some of the innovative business models that insurance companies have developed to unlock values ​​captured in their data. For more information on revenue generation and data driven companies click on these links.

Otherwise send me an email.

Accenture and M6: Monetizing big data

Future Systems

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Disclaimer: This document is for general information purposes only and does not take into account the reader's specific circumstances and may not reflect recent developments. Accenture disclaims, to the extent permitted by applicable law, any responsibility for the accuracy and completeness of the information in this presentation and for any acts or omissions made based on such information. Accenture does not provide legal, regulatory, auditing or tax advice. Readers are responsible for obtaining such advice from their own legal attorneys or other licensed professionals.

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