Big data, IoT and data warehouse?

It's the age of big data and the internet of things (IoT), but how will that change things for insurance companies? Do insurers still need to consider classic data warehouse concepts based on a relational data model? Or will all relevant data be stored in big data structures and thus […]

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Don't let your data warehouse be a data labyrinth!

Auditability and data quality are two of the most important demands on a data warehouse. Why? Because reliable data processes ensure the accuracy of your analytical applications and statistical reports. Using a standard data model enhances auditability and data quality of your data warehouse implementation for business analytics. tags: auditability, […]

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Insurers beware: Fraudsters love digital!

Insurers are embracing digital to meet the demands of modern consumers. And, of course, there are obvious benefits to them from less costly, more streamlined interactions with their customers. The trouble is that digitisation comes with a major health warning: Unless insurers put suitable measures in place, they're at risk […]

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Data Governance by a Standard Data Model for Insurance

  Using a standardized data model is an essential condition to achieve data governance in an enterprise. A standard data model supports data governance processes by implementing industry standards wherever possible: standards for contract and claims representation, mapping of data content with standard definitions (glossary function), use of code attributes […]

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How social brokers is changing insurance

“All for one and one for all” is best known as the motto from “The Three Musketeers”, but this phrase could easily sum up the growing trend in social brokers. With advanced analytical techniques like generalized linear modeling insurance companies have created more granular pricing structures. But despite the assertions […]

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10 simple steps to detect more insurance fraud

Over the years I have written many blogs about insurance fraud including those on anti-money laundering, data quality in fraud, anti-fraud technology, life insurance fraud and even ghost broking.  It’s clear that insurance fraud comes in many shapes and sizes and as losses continue to grow, detecting and preventing fraud […]

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Innovation in reinsurance – no longer an oxymoron

Insurance is a tough marketplace, but in many respects reinsurance is tougher! Today, the reinsurance industry is faced with an unprecedented number of challenges especially with what appears to be an increasing frequency and severity of man-made and natural catastrophes. To combat these challenges, reinsurers are turning to technology for […]

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Advantages of a standard insurance data model

In my first blog article I explained that many insurance companies have implemented a standard data model as base for their business analytics data warehouse (DWH) solutions. But why should a standard data model be more appropriate than an individual one designed especially for a certain insurance company? tags: data […]

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Back to basics

One of my colleagues often asks me “What’s new in insurance”. For an industry that is risk adverse, change does not come easily. In the past we have discussed innovations concerning telematics, drones, wearables devices and even weather data. However when he asked me last week and I responded that […]

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Faster, easier, safer: a standard data model for insurance

Nothing works today without an efficient data management – also in insurance business. A standard data model can be an important component of it. This article explains why. “Make or Buy”? This question has been raised very often by insurance companies planning to introduce a consistent data structure – a […]

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