{"id":26557,"date":"2019-04-03T16:41:48","date_gmt":"2019-04-03T21:41:48","guid":{"rendered":"https:\/\/centricconsulting.com\/?p=26557"},"modified":"2022-08-30T11:11:52","modified_gmt":"2022-08-30T15:11:52","slug":"data-in-insurance-how-real-is-the-need-for-real-time","status":"publish","type":"post","link":"https:\/\/centricconsulting.com\/blog\/data-in-insurance-how-real-is-the-need-for-real-time\/","title":{"rendered":"Data in Insurance: How Real is the Need for Real Time?"},"content":{"rendered":"

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.<\/h2>\n
\n

Part of a blog series.<\/em><\/a><\/p>\n

Doing things better and faster has been a human quest since the beginning of our intellect. This quest gave us our first stone tool and wheel and led us to develop supersonic jets<\/span>.\u00a0<\/span>\u00a0<\/span><\/p>\n

The same is true for our eagerness to understand and u<\/span>se<\/span>\u00a0data instantaneously and convert it into actionable information. <\/span>With \u202faccess to large processing and storage resources, our ability to act on information in real time has become the new frontier of innovation<\/a>.<\/strong><\/p>\n

What is Real-Time,\u00a0Really?<\/h2>\n

First,\u00a0<\/span>let’s<\/span> clarify how real<\/em> real time truly is<\/span>.<\/span>\u00a0<\/span><\/p>\n

That depends on the context you want to use it for. Similar to the fact that there is truly no <\/span>\u2018unstructured data\u2019 (not \u2018yet\u2019 structurally understood data), <\/span>there is no true \u2018real-time\u2019 data either. It\u2019s just near real-time. <\/span>When we talk about real-time data or real-time systems, we are essentially talking about systems\u00a0<\/span>that allow<\/span>\u00a0you to \u2018work\u2019 or\u00a0<\/span>use data before actually\u00a0<\/span>storing\u00a0<\/span>it.\u00a0<\/span>In other words, real time denotes our ability to use data as soon as it arrives, rather than storing it first and analyzing it in the future.<\/strong> This is the primary significance of the term real-time, using data in the present rather than in the future.<\/p>\n

Real-Time Data in Insurance<\/h2>\n

If we look at this through the lens of the insurance industry, we see a need for data to be available a lot faster for us to use it, but as with any other industry, this need is not equal for all use cases. <\/strong>For example,\u00a0<\/span>financial and statistical reporting are\u00a0<\/span>more like snapshots in time<\/span>. S<\/span>o, their timeliness needs ar<\/span>en\u2019t necessarily real-time. They\u2019re more<\/span>\u00a0like\u00a0<\/span>e<\/span>nd-of-<\/span>day<\/span>,<\/span>\u00a0<\/span>week<\/span>\u00a0or\u00a0<\/span>month<\/span>.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

Whereas agents and adjusters in the field need a timelier turnaround \u2013 within seconds or minutes \u2013 on the status and feedback of a claim.<\/p>\n

That’s not happening today. Here’s how you solve this dilemma:<\/h3>\n

Historically speaking<\/span>,<\/span>\u00a0aggregate reporting use cases became the bread and butter for BI and data professionals\u00a0<\/span>as\u00a0<\/span>the application development<\/a> world\u00a0<\/span>tackled\u00a0<\/span>more \u2018real-time\u2019 challenge<\/span>s<\/span>. This seamless distinction caused solutions to become more siloed, which over time caused an inherent latency in the reporting world and aggregation limitation in the application world. <\/span>T<\/span>his should not happen.<\/span>\u00a0<\/span><\/p>\n

Until recently, whenever we talked about moving data in real-time, we inevitably talked about using some version of service bus or message queues. These systems provided us low latency and high availability, but the main drawback of these ecosystems are extensive development lifecycles and a somewhat flaky<\/span>\u00a0nature<\/span> to accommodate for changes that need to be coordinated throughout the downstream pipeline.\u00a0<\/span>\u00a0<\/span><\/p>\n

Not to mention, we end up changing the shape of the data multiple times. But as data replication technologies become more robust, it opens an opportunity for us to maintain relational databases in sync- in a \u2018<\/span>r<\/span>eal-time\u2019 manner, without encountering huge development or maintenance cost<\/span>s<\/span>. These\u00a0<\/strong><\/span>technologies also allow us to retain the \u2018shape\u2019 of the data and implement\u00a0or\u00a0account for changes without much hassle\u00a0\u2013\u00a0and in a decoupled manner. \u202f\u00a0<\/strong><\/p>\n

With these mechanisms, we can maintain multiple copies of an application database, a live one for the online application and another one for data solutions. This allows us to design solutions that require<\/span>\u00a0<\/span>\u2018atomic\u2019 data<\/span>\u00a0without waiting for additional processing to occur.<\/span> T<\/span>his, too, comes with an architectural problem as application databases are much more normalized by design<\/span>.<\/span>\u00a0T<\/span>hey are not easy to use for analytical purposes.\u00a0<\/span>\u00a0<\/span><\/p>\n

Therefore, we still need to modify<\/span>\u00a0and\u00a0<\/span>reorganize these structures to be conducive for analytical usage<\/span>. B<\/span>ut since we have a true separate physical copy, we can query it as frequently as we need without worrying about adversely affecting the application performance.\u00a0<\/span>\u00a0<\/span><\/p>\n

This\u00a0<\/span><\/b>helps\u00a0<\/span><\/b>us\u00a0<\/span><\/b>start looking into designing micro-batch jobs and trickle-down data feeds that can keep analytic-friendly structures up to date with hourly<\/span><\/b>\u00a0and\u00a0<\/span><\/b>semi-daily loads<\/span><\/b>. <\/span><\/b>All of this leads to daily, multiple dashboard refreshes and mid-day financial reporting.<\/p>\n

Beyond this, we can now create solutions for real-time use cases and not just for \u2018atomic\u2019 data. We can link this to other aggregated sources and enhance the results to provide more actionable insights.<\/p>\n\n

\n
\n Learn how to take a modern analytics approach that aligns your data strategy with your business strategy.\n <\/div>\n
\n \n\n Download Our Ebook\n <\/a>\n <\/div>\n <\/div>\n

Final Thoughts<\/h2>\n

By using\u00a0<\/span>these\u00a0<\/span>technolog<\/span>ies<\/span>\u00a0and design\u00a0<\/span>paradigms<\/span>, you can provide\u00a0<\/span>the status of <\/span>policies and\u00a0<\/span>claim<\/span>s<\/span>\u00a0in \u2018real-time.’ You can also<\/span>\u00a0<\/span>couple it with\u00a0<\/span>detailed personalized reports and statistics\u00a0<\/span>for in<\/span>-field adjustors and agents<\/span>. <\/span>How do you accomplish this? With a fraction of infrastructure, development cost and simplified architecture.<\/p>\n

I am sure that as we move forward with these solutions, bringing newer capabilities to light, the silos I\u00a0<\/span>mentioned<\/span>\u00a0earlier\u00a0<\/span>will become a thing of the past and the data will be available for all use cases in near real-time.\u00a0<\/span>The questions we will be asking then are \u201cwhat is the time context of your use case\u201d and \u201chow soon do you need it.\u201d<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

Learn how you can provide\u00a0real-time status updates on insurance policies and\u00a0claims as well as\u00a0personalized reports and statistics\u00a0for adjustors and agents.<\/p>\n","protected":false},"author":234,"featured_media":32259,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_oasis_is_in_workflow":0,"_oasis_original":0,"_oasis_task_priority":"","_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","footnotes":""},"categories":[1],"tags":[18616,3759],"coauthors":[15610],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2024-07-22 10:26:13","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category"},"_links":{"self":[{"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/posts\/26557"}],"collection":[{"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/users\/234"}],"replies":[{"embeddable":true,"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/comments?post=26557"}],"version-history":[{"count":0,"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/posts\/26557\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/media\/32259"}],"wp:attachment":[{"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/media?parent=26557"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/categories?post=26557"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/tags?post=26557"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/centricconsulting.com\/wp-json\/wp\/v2\/coauthors?post=26557"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}