Anyone who has spent a large portion of their career in the insurance<\/a> industry has likely experienced a very strange occurrence.<\/p>\n We work in a business that sells its ability to predict risks by analyzing vast amounts of complex information. The data comes from a variety of disparate internal and external sources and has driven profits for decades.<\/p>\n Knowing this, newcomers might naturally expect that data is robust, widely available, and extremely reliable.<\/p>\n If you\u2019re passionate about data and analytics<\/a>, you might even gravitate toward the career path given that expectation. Unfortunately, you will quickly find yourself experiencing the painful irony of insurance and data:<\/strong><\/p>\n Finding yourself in this situation, it\u2019s tempting to assume you just picked the wrong company and that the grass is greener at another carrier. As data professionals who have worked with dozens of insurance carriers over several decades, we can tell you, it isn\u2019t.<\/p>\n Now you\u2019re probably wondering \u201cIs our industry ever going to keep up?\u201d or \u201cWill we be able to attract new talent?\u201d<\/p>\n The simple answer: it doesn\u2019t have to be this way, and we\u2019re working to make sure it won\u2019t be for much longer. The longer answer will be covered in this blog series.<\/strong><\/p>\n No problem worth solving is ever simple, fast, or easy. And this is a problem worth solving. If you need to explain the importance to a layperson, suggest they ask themselves a question or two:<\/p>\n Improving the efficiency, flexibility and predictive power of the insurance industry helps us all.<\/strong><\/p>\n When the idea of accident insurance was first implemented almost 170 years ago, it was extremely narrow in scope. It was intended to cover injury in the event of an accident while traveling on a train. Losses were predicted based on the quality of the cabin you traveled in.<\/p>\n Now, consider the modern-day auto insurance policy. It covers multiple parties, risks, and loss types all driven by a list of different variables that keep growing with every passing year.<\/p>\n In short, the problem keeps getting more complex and the technology available to handle it has been changing just as quickly.<\/strong><\/p>\n Let\u2019s not forget, the smartphone in your pocket is more powerful than the average supercomputer of just thirty years ago and costs between $500 and $1,000, not tens of millions of dollars<\/a>. As you add this all up, the current situation was inevitable.<\/p>\n With only so much money to invest, carriers spent wisely and focused on core business: improving pricing, billing, and claims modernization.<\/strong><\/p>\n Unfortunately, with all the technological advancements that made that smartphone in your pocket possible, the industry now has a lot of catching up to do. Just ten years ago, catching up meant an investment of tens of millions of dollars and a high likelihood of failing before you reaped any benefits, assuming you succeeded at all.<\/p>\n Today, we know more, have more options, and the price tag is a fraction of what it used to be.<\/strong><\/p>\n Insurance Data: Where Did That Number Come From?<\/span><\/a> — Dealing with insurance data? Apply these four concepts for a single version of the facts, a single interpretation into truth and confidence in your conclusions.<\/span>\u00a0<\/span><\/p>\n Insurance Business Intelligence: How To Spend More Time on Value-Added Analytics<\/span><\/a> — There is no one-size-fits-all solution for insurance business intelligence needs. But, there\u2019s a four-part approach and set of technologies that can help.<\/span>\u00a0<\/span><\/p>\n Data in Insurance: How Real is the Need for Real Time?<\/span><\/a> — Learn how you can provide\u00a0real-time status updates on insurance policies and\u00a0claims as well as\u00a0personalized reports and statistics\u00a0for in-field adjustors and agents.<\/span>\u00a0<\/span><\/p>\n Data Governance in Insurance: All Pain, No Gain?<\/span><\/a> — There is no way to eliminate all the pain in data governance. It is hard work. But with a good plan, you can minimize the pain and maximize the gain.<\/span>\u00a0<\/span><\/p>\n A Modern Insurance Analytics Platform is Better, Faster, Stronger and Cheaper<\/span><\/a> — Modern technology, along with industry knowledge and experience, means an analytics project can be delivered better, faster, stronger and cheaper.<\/span>\u00a0<\/span><\/p>\n Enriched and Raw Data in Insurance: Can\u2019t They Just Get Along?<\/span><\/a> — Raw data in insurance\u00a0needs\u00a0processing,\u00a0cleaning, and\u00a0polishing.\u00a0Only then can it be packaged.\u00a0This is what we call data\u00a0enrichment.<\/span>\u00a0<\/span><\/p>\n Recasting IT Leaders as Strategy Partners for Growth at P&C Insurers<\/span><\/a> — To remain competitive in a disruptive market and drive growth, insurance companies must recast IT leaders as strategy partners.<\/span>\u00a0<\/span><\/p>\n\n
What’s the answer?<\/h2>\n
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How did we get here?<\/h2>\n
Read the Blog Series<\/h2>\n