Tag: insurance

Analytics
Ketil Kristensen 0
How do you adapt your insurance pricing strategy in the face of increased price competition?

Many countries in Europe have in previous years experienced increased price competition for general insurance products. Especially in Southern Europe, the competition has been very fierce, fueled by online price comparison websites. In Spain, Portugal and Greece, there has been a substantial drop in average premiums for products like motor,

Analytics | Fraud & Security Intelligence | SAS Events
Ilkay Aydogdu 0
Eureko Sigorta Data Studio Lideri Özlem Odar: “Veri ve analitik projelerin çevik yöntemlerle uygulanmasını ve hızlı sonuçlar üretilmesini amaçlıyoruz”

Sanal etkinliğimiz Beyond Tomorrow öncesinde Eureko Sigorta’nın Data Studio Lideri Özlem Odar ile görüşme imkanı buldum. Hepimizin bildiği gibi Türkiye'nin öncü sigorta firmaları arasında yer alan Eureko Sigorta, hasar yönetimi ve risk değerlendirme konusundaki uzmanlığı ile alanında lider konumda olan uluslararası bir yapıya sahip. Avrupa'nın 6 ülkesinde 22.000 çalışanıyla dünyanın

Analytics
Michael Rabin 0
„Und plötzlich steht das Aktuariat wieder im Mittelpunkt“

Versicherungen arbeiten intensiv daran, ihre Geschäftsmodelle zu erneuern. Ein modernisiertes Aktuariat spielt dabei eine Schlüsselrolle. Warum? Das habe ich meinen Kollegen und ausgebildeten Aktuar Diego Rivas gefragt. Das Versicherungsgeschäft wirkt von außen wie ein langer, ruhiger Fluss. Trügt der Schein? Heute – eindeutig ja. Der Markt ist längst gesättigt, und

Advanced Analytics | Data Management | Data Visualization
Interview 0
Gastinterview mit adesso AG Marius Gödtel " Versicherer brauchen schnelle Reportings "

Unser Interviewpartner Marius Gödtel ist Leiter des Competence Centers Business Intelligence IT-Consulting  bei der adesso AG, einem IT-Dienstleister im BI-Umfeld. Marius Gödtel ist ehemaliger Geschäftsführer der flitcon GmbH, die seit 01. Juli 2016 Teil der adesso AG ist. Herr Gödtel, wie präsentieren Sie die adesso AG auf dem SAS Forum in

Analytics | Fraud & Security Intelligence
Leendert Kollmer 0
Vermittlerbetrug erkennen und verhindern

Wirtschaftskriminelle Handlungen zu entdecken und zu verhindern, ist ein kontinuierlicher Prozess, dessen Optimierung der Versicherung finanzielle Vorteile verschafft und Reputationsschäden verhindert. Eine entscheidende Rolle spielen dabei vor allem die Prävention und eine optimierte Identifikation von Betrugsversuchen durch fortgeschrittene analytische Verfahren. Die meisten der im Betrug durch Vermittler anzutreffenden Handlungen manifestieren

Data Management
Hartmut Schroth 0
Drivers for the digitalization of insurance

The insurance industry is becoming increasingly focused on the digitalization of its business processes. There are many factors driving digitalization, but it’s clear that a reliable and meaningful database is the basic prerequisite for a successful digitalization strategy. Insurance companies are increasingly prioritizing digitalization, not because this issue is currently

Analytics | Risk Management
Carsten Krah 0
Versicherungen: Modernisierung mit Analytics

Versicherungen stehen massiv unter Druck. Negative Zinsen und ein hoher regulatorischer Druck führen auch nicht gerade zu Euphorie (versicherungswirtschaft-heute.de). Die Branche klagt, all das sei operativ gar nicht zu schaffen. Was tun? Niedrigzinsumfeld ändern? Geht nicht. Regulatorik beeinflussen? Geht nur partiell. Also bleibt nur, an Effizienz und Automatisierung von Prozessen

Hartmut Schroth 0
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

Hartmut Schroth 0
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.

David Hartley 0
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

Hartmut Schroth 0
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

Hartmut Schroth 0
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

Stuart Rose 0
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

Stuart Rose 0
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

Hartmut Schroth 0
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?

Stuart Rose 0
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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