Part of a blog series.<\/a><\/em><\/p>\n As we noted in the\u00a0<\/span>first post<\/span>\u00a0in this series<\/span>, the Insurance industry has some catching up to do when it comes to implementing modern analytics<\/a> platforms. <\/span><\/p>\n You may remember the heady days of a decade ago when \u201canalytics\u201d and \u201cbig data\u201d were not only the most used words at every conference you attended but even had national advertising campaigns devoted to them.<\/span>\u00a0It seemed that everyone in the business world was focused on analytics already by that time.<\/span>\u00a0<\/span><\/p>\n Well, almost everyone. Those early analytics projects were<\/span>\u00a0<\/span>difficult and very expensive, as\u00a0<\/span>cutting-edge<\/span>\u00a0technologies often are.\u00a0<\/span>The Property & Casualty Insurance<\/a> industry found itself at a crossroads: Pursue one of these exciting (if costly) projects, or focus on modernizing core business functions? While there were certainly\u00a0<\/span>many\u00a0<\/span>P&C Insurance<\/a> companies that were early adopters of analytics technologies, the\u00a0<\/span>priority of the industry as a whole was on those functions that, \u201ckeep the lights on.\u201d<\/span>\u00a0<\/span><\/p>\n Many of the people we have spoken with about those early insurance analytics projects don\u2019t feel like they got the most out of their investment.\u00a0<\/strong>But the field of analytics has continued to evolve to the point that now is a great time to change the focus from platform modernization to analytics maturity.<\/p>\n Imagine you are a distribution manager for a mid-sized Property & Casualty Insurance firm. You have focused for the last few years on modernizing your platforms<\/a>\u00a0<\/span>and ensuring<\/span>\u00a0you have maximum exposure on all the channels you find relevant. <\/span><\/p>\n You have worked with marketing to ensure your social media presence is dynamic and engaging. You have worked with IT to create and maintain your online and mobile quoting portals. You work with actuarial to make sure your rates are appropriately competitive.\u00a0<\/span>But you still feel there\u2019s something more you can do to get an edge.\u00a0<\/span>There\u2019s a data warehouse that you maintain for monthly reports, but is there something more you\u00a0should<\/i>\u00a0<\/i>be doing with all this data you have to take your business to new heights?\u00a0<\/strong><\/p>\n You tried an analytics project a few years ago after learning about a success story at a conference, but it did not yield the results you (or your management) desired. You wonder: What is the state of the art now? Can we find new insights with new technology?<\/p>\n Even today, it is possible to find source systems in the insurance industry, among others, that discard transactions on a monthly or otherwise regular basis. These legacy systems are maintained to run off business that was established in those systems.<\/span>\u00a0<\/span>Those among us who have worked in this industry for some time can remember working on projects to capture that data regularly and move it to a more permanent store for further operations<\/span>\u00a0and reporting.<\/span>\u00a0<\/span>As insurance analytics platforms<\/a> modernized, our ability to capture real-time data improved. <\/strong><\/p>\n We went from easily automated monthly snapshots to daily overnight snapshots, and then to real-time replication, where every transaction in a source system at any time of day can be instantly replicated to a database in any location we desire for whatever purpose we need.<\/p>\n Even better: This data can be captured regardless of the system in which it resides. The modern enterprise relies on several systems to capture and maintain data.\u00a0<\/span>Current technology allows for the real-time capture of\u00a0<\/span>this data regardless of the source system. Mainframe, VSAM, DB2 and other older, but still used, data structures are all on the table for modern analytics projects.<\/span>\u00a0<\/span><\/p>\n The current state of affairs allows for true and truly painless change data capture (CDC). <\/strong>For the Distribution Manager mentioned above, this is fantastic news.<\/span>\u00a0<\/span>Each day, the Distribution Manager\u2019s company quotes hundreds or thousands of policies. Whether they are working with\u00a0<\/span>an\u00a0<\/span>Agent<\/span>\u00a0<\/span>or automated underwriting through an online portal, each potential customer may go through several iterations of quotes before finally deciding on a coverage\u00a0<\/span>level\u00a0<\/span>and policy, or ultimately walking away.\u00a0<\/span>\u00a0<\/span><\/p>\n What if we could have access to all that data, replicating it in real time for analysis later? <\/span>\u00a0<\/span>If we had all the versions of all the quotes, we could understand, in real-time:\u00a0<\/strong><\/p>\n These and other insights await the Distribution Manager. But what about the rest of the enterprise?<\/span>\u00a0<\/span>Imagine if we could understand IBNR in real-time as a major storm approaches the coast and adjust reserves accordingly. Or what if we could identify high-risk claims the moment they are reported, and route them to the people\u00a0with the best experience\u00a0to handle them?\u00a0\u00a0<\/strong><\/p>\n The potential benefits are abundant and tantalizing.\u00a0<\/span>So,<\/span>\u00a0what are we waiting for?<\/span>\u00a0<\/span><\/p>\n There\u2019s just that one sticky point about these projects: They have the reputation of being costly, even compared with the typical IT project for the enterprise.<\/span>\u00a0<\/span>In the early stages, it was common for an analytics project to cost in the tens of millions on the low end. Today, storage and processing power are relatively cheap and widely available.<\/span><\/p>\n We no longer need to spec out a server, order it, and wait 30 or more days for it to arrive, and then wait for even more for it to be installed in the data center before we can start to configure it for use on a project. Virtual machines and cloud servers have helped remove the last barrier to pursuing a modern analytics platform.<\/span>\u00a0<\/span><\/p>\nA Distribution Manager\u2019s Dream<\/h2>\n
Better, Stronger, Faster<\/h2>\n
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Cheaper\u00a0<\/span><\/h2>\n