Stuart Rose is the Global Insurance Marketing Manager for SAS. He began his career as an actuary and now has more than 25 years of experience in the insurance industry working for companies in the US, Europe and South Africa. Stuart has written many insurance-related articles and is also the co-author of Executive’s Guide to Solvency II.
“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
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
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
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
How many of us have used the phrases… It’s a piece of cake Anyone can do it It’s as easy as ABC I could do it with my eyes shut When it comes to business intelligence it should be “easy peasy” but for many organization it can still be a
In a recent blog I wrote about how big data is a game changer for the insurance industry. But the question that is often asked “What is big data”? Many people associate big data with the 4 V’s: Volume – The sheer size of data that is produced. Velocity –
A recent survey by Capgemini found that 78% of insurance executive interviewed cited big data analytics as the disruptive force that will have the biggest impact on the insurance industry. That’s the good news. The bad news is that unfortunately traditional data management strategies do not scale to effectively govern
The role of insurance is to bring some predictability, manageability and stability in what is in essence, a chaotic and uncertain world. So as we head into 2016, what are the big issues for insurers in the next 12 months? Below is just a selection of some of these issues:
Similar to claims fraud, money laundering is seen as a victimless crime, and often glamorized in movies and books. Think “The Wolf of Wall Street” and “Scarface”. But money laundering is a SERIOUS problem. According to a 2013 report, the United Nations Office on Drugs and Crime estimates that $1.6
Customer intelligence will help an insurance company deepen its customer insights, choreograph its customer interactions and continuously improve its marketing performance. Unfortunately for all the progress made in recent years on customer relationship management and getting to know customers better, insurance companies are still not focusing on customers as much
It’s rather appropriate that the rock band Europe recorded the hit “The Final Countdown”, because today, September 22nd, represents 100 days until the much anticipated (and delayed) European insurance legislation Solvency II will come into effect on January 1st 2016. Designed to introduce a harmonized, EU-wide insurance regulation, Solvency II
Big Data has become a technology buzzword. But how is Big Data changing insurance? Historically, insurance companies have used SMALL data to make BIG decisions. Today, insurers are using BIG data for SMALL decisions. What does this mean? Traditionally, insurance companies have aggregated data to group risks into broad categories
“Garbage in, garbage out” is more than a catchphrase – it’s the unfortunate reality in many analytics initiatives. For most analytical applications, the biggest problem lies not in the predictive modeling, but in gathering and preparing data for analysis. When the analytics seems to be underperforming, the problem almost invariably
Good news...an analytics survey last year found that 72% of insurance executive agreed that analytics is the biggest game-changer in the next 2 years. Bad news...compared to other industries the adoption rates of analytics in the insurance has lagged other industries. To reverse this trend and help insurers travel down the
The insurance industry is heading for a crisis. Depending on which report you read the insurance industry is facing a shortfall in job vacancy from anything from 40,000 to nearly half million in the next few years. Baby boomers in specialized jobs like underwriters and claims adjusters are retiring and insurers
If you buying or selling a house. The relator will tell the value of the property is all about location, location, location. For insurance companies location is just as important. For an underwriter assessing the risk on a property is essential that they consider the location of the property. How
Who is your best customer? The answer to this question can vary dramatically depending on your industry. A retailer’s best customer is someone who comes back to their store over and over again. A gym owner’s best customer could be considered consumer who pays their monthly on time but never
The analytical lifecycle is iterative and interactive in nature. The process is not a one and done exercise, insurance companies need to continuously evaluate and manage its growing model portfolio. In the last of four articles on the analytical lifecycle, this blog will cover the model management process. Model management
Insurance relies on the ability to predict future claims or loss exposure based on historical information and experience. However, insurers face an uncertain future due to spiraling operational costs, escalating regulatory pressures, increasing competition and greater customer expectations. More than ever, insurance companies need to optimize their business processes. But
There is no doubt that analytics is an overused and often abused term. So what does really analytics means? In part 2 of a series of articles on the analytical lifecycle, this blog will highlight some of the common and emerging techniques used to analyze data and build predictive models
In my last blog I detailed the four primary steps within the analytical lifecycle. The first and most time consuming step is data preparation. Many consider the term “Big Data” overhyped, and certainly overused. But there is no doubt that the explosion of new data is turning the insurance business
Advances in technology, evolution of the distribution channels, demographic shift, economic conditions and regulations changes. How does an insurer prioritize all these seemingly competing goals and create sustainable competitive advantage. One answer is analytics. Many insurance companies are just beginning to take steps toward becoming an “analytic insurer” – one
The old adage is that “Data is the lifeblood of the insurance industry.” However, for many insurance companies, data is like the red-headed stepchild. No one is willing to take care or have responsibility for it. In the past, insurance companies have created data governance programs, but these have often
The role of insurance is to bring some predictability, manageability and stability to a chaotic and uncertain world. In essence, it is a risk mitigation tool. The role of the Chief Risk Officer (CRO) is to manage the overall risk strategy for the insurance company. They are responsible for defining
Business analytics is about dramatically improving the way an organization makes decisions, conducts business and successfully competes in the marketplace. At the heart of business analytics is data. Historically, the philosophy of many insurers has been on collecting data, data and more data. However, even with all this data, many
According to analyst firms, consulting companies and various other research, customer experience is the primary priority for insurance companies. But is customer experience overrated? Let’s start by considering the primary interactions between an insurance company and its customers: new business, billing, renewals and claims. Ask any insurance executive, especially property
I cannot speak from experience, but predominately an Insurance CEO has three primary objectives: Grow the business Reduce expenses Ensure compliance. Let’s individually consider each of these objectives in more detail. Grow the Business How does an insurance company grow from a $2bn to a $3bn organization? Essentially, insurance has
Earlier this year, I was speaking with an insurance executive and he said something that turned out to be my favorite quote of 2014: “Premium revenue is like heroin.” While this seems like an unlikely analogy or simile?. The point this executive was trying to make an interesting argument. Insurance
What do the following have in common? A homeowner inflates the value of his home entertainment equipment stolen during a robbery. A parent states they are the primary driver for their child’s car. A doctor charges for a non-existent procedure. A construction company underreports payroll or misclassifies an employee’s duties.
Last week, I was fortunate enough to attend the Insurance Networking News Analytics Symposium. This great event had several engaging speakers. As analytics becomes more prevalent within insurance, it was refreshing to see that many organizations discuss their successes and share best practices in this essential aspect of the business.
