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 from increasingly sophisticated fraudsters and false claims (about one in every 10).

Since the turn of the millennium, ‘brochure web sites’ for insurance companies have been replaced with ecommerce platforms that can transact new business directly Fraud_digitalwith customers online. More recently we've seen the rise of the insurance aggregator, allowing customers to enter their insurance needs into a website and receive quotes from potentially hundreds of insurers in seconds. It's improved choice and made the marketplace more competitive.

Fast forward to today and insurers are digitising more of the insurance process, including mid-term policy adjustments, claims notification and claims updates through self-service web interfaces and mobile apps.

While insurers are improving their digitisation capabilities, criminals are finding new ways to bypass the law and detection measures. The Association of British Insurers estimates that fraud adds, on average, an extra £50 to the annual insurance bill for every UK policyholder.

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Three deliverables to kick off a data and analytics modernization plan

Mont EverestIf you were to climb Mt. Everest, you would face many dangers, including large crevasses in the glacier. Without best practices and a phased ascension there is a large probability that you’ll get into serious trouble and fail.

When it comes to updating your data and analytics systems, the challenges can look equally difficult. To cope with changing and growing business needs, the obsolescence of incumbent technologies, and the pressure to reduce costs, IT has no choice but to evolve and change its underlying architecture for analytics. The process could be like a journey to the top of the world, or it could bring many pitfalls.

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How can you know what’s best for more than 20,000 students?

When your job involves making decisions that affect thousands of college students, making the right decisions can have a large impact on the future. Giving college administrators easy access to reliable analytics can help improve enrollment and graduation rates – and find answers to complex questions that cut across many facets of the university.

“Too often, good-hearted people make decisions based on what they think will be good for students, but in the end, these decisions aren’t good for them,” explains Tuesdi Helbig, Director of Institutional Research at Western Kentucky University (WKU).

Helbig and her colleagues at WKU maintain an enterprise reporting system and use SAS Visual Analytics to empower their constituents – regardless of whether they are on or off campus – to access data and insights about students, faculty, staff, revenues and more. I recently had the opportunity to interview Helbig and Gina Huff, a Senior Applications Programmer Analyst at WKU, to learn more. Read More »

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Correlations, forecasts, and making sense of it all with visualization

"Correlation does not imply causation.” Does that bring back memories from your college statistics class? If you cringe when you hear those words, don’t worry. This phrase is still relevant today, but is now more approachable and easier to understand.

Here at SAS, we use SAS® Visual Analytics to make sense of it. We can use a correlation matrix to explore relationships between variables, and forecasting to figure out which variables explain a response or target variable.

Before we take a look at that, let’s first dig into how forecasting works in SAS Visual Analytics. Although the business user may not necessarily know this, SAS Visual Analytics runs both Exponential Smoothing Models (ESM) and Auto Regressive Integrated Moving Average models – ARIMA, for short.

If those sound scary, all you really have to know is that they predict future data as a function of the historical data values. Time series models aren’t the same as simply extending a linear trend. Recent data points are weighed more heavily when calculating the future data points. Makes sense, right?

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The real deal in fraud and financial crimes

Financial institutions evaluating fraud management solutions face a crowded vendor landscape. Dozens of vendors claim to offer various pieces of the puzzle. With so many choices available, how will you sort through the marketing rhetoric to find the best fit for your organization?

You could assemble a team of analysts and advisors from the risk management and financial services industries to serve as independent advisors. Give them several months to gather and review vendor submission forms, administer user surveys, interview customers and users of each solution, conduct briefings with vendors, attend conferences, host roundtable discussions, collaborate with industry consultants, and review academic and regulatory studies.

You could, or you could be thankful that research firms have already done it. Read More »

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Using SAS and open source: a hybrid approach

The automotive industry will face a huge challenge for several years. With the Paris Agreement made during the United Nations conference on climate change last year, world leaders agreed to hold the increase in average temperature to well below 2°C by placing restrictions on carbon emissions.

How can automakers design a new engine using less fossil energy, reducing carbon emission and yet still offering the same level of performance, autonomy and practicality as the petrol engine?

electriccarA few years ago, the immediate answer from automakers was to shift to electric vehicles with no carbon emissions. However, the performance of electric cars hasn’t yet been equal, and to date the market promise hasn’t yet been fulfilled – relatively few electric cars have been sold.

In the world of analytics software, we may have a similar situation. The digitization of business in a context of sluggish growth along with the rise of mobile activity, and the Internet of things, to name a few, will increase the demand for scalable, effective and low cost analytics.

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Lifelong learning and analytics

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Doris (Simpson) Sadovy, a teenager in Atlantic City, half a dozen years before me

I sometimes feel bad about being born. Not so much the actual event, mind you, just the timing. I was born during what should have been my mother’s last year of college.

At many colleges in those days, when a woman got married, she was forced to move out of the daytime program and into night school. You know what a bad influence those married women can be. And if she got pregnant?  Well, that was evidently just too much for the delicate sensibilities of college administrators of the time.

My mom and dad got married in between her junior and senior years of college. I was born in March the following spring. Although she wasn’t showing when the fall semester started, she knew she couldn’t hide it until Christmas.

Since this was a teacher’s college, and she’d be practice teaching in real schools, she risked being arrested for contributing to the delinquency of a minor if she didn’t fess up right from the start. So, because of me, she had to drop out just two semesters short of her degree.

I was trouble before I was even born. Read More »

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And the weather yesterday was …

200362007And the weather yesterday was a sunny 18oC with warm spells in the south and showers in the north. This is similar to the pattern we saw last Thursday.”

Imagine if the weather forecast only restated what happened in the past -- would we bother waiting until the end of the news each night to watch? Compare this to organisations -- how much of an organisation’s business intelligence is a historic view of what happened? And when organisations do use forecasts, they’re often a rehash of previous numbers with an aspirational target added to improve sales performance.

In the UK, weather forecasting benefits industry to the tune of over £1bn per annum, for an annual spend of £120m (see Public Weather Service Value for Money Review, March 2015 for details). It’s the predictive nature of the weather forecast that makes it so valuable to so many sectors of industry, from aviation to civil planners to retailers.

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New study confirms: SAS most valuable career skill

young man at laptop in libraryIf you're looking for higher pay and better opportunities, what career skills should you seek to acquire? You might think leadership or communication skills would top the list, but a recent study says otherwise.

According to a massive study from MONEY and Payscale.com, SAS Analytics skills are the most valuable skills to have in today's job market.

The study “analyzed 54 million employee profiles, across 350 industries, with 15,000 job titles—from entry-level workers to top execs."

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Gearing up for pharma’s big change

sas.com_MedResearch_84A4033The pharmaceutical industry will undergo significant changes this summer. A set of standards for the identification of medicinal products (IDMP) from the European Medicines Agency (EMA) will take effect in July, requiring the whole industry to apply the terminologies released by EMA. The changes have raised many concerns regarding how data is managed across the industry.

While pharmaceutical companies recognise the urgent need to take action to meet the EMA deadline, the real challenge is applying a speedy, mechanised process to limit resources needed to achieve compliance. Companies face the challenge of organising huge amounts of unstructured data, which resides in silos across the business, with no formalised cataloguing method. Read More »

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