If you work in claims, chances are you’re intimately familiar with the value of data.
While actuarial tables and the analysis of historical data for the purpose of setting premiums have long been a major part of the insurance industry, some larger companies now have analytics departments focused on using past claims data to build predictive models, usually on an ad-hoc basis.
Structura is an analytics platform that lets you build historical and predictive models which combine your internal claims data with external third party data. What’s more, Structura lets you do this within hours, unlike the months or years it would take using other BI tools or custom development. With Structura at the centre of your organization, you’ve got a complete solution for your most common claims and litigation-related needs.
Structura Can Help.
What Solution Are you Looking For Today?
Disputed claims take up valuable time and resources to defend, so you try to head off litigation risk wherever possible. Putting experienced adjusters on the most complex claims is the best way to do this, but since claims are often assigned based on limited data, you can’t always tell from the outset which claims are going to require a more experienced hand.
- High reassignment rates dragging out claim duration
- Skyrocketing overhead
- Inconsistent settlement amounts due to inexperienced handling
- Worsening customer relationships leading to increased litigation risk
- Claim disputes accounting for a huge portion of loss adjustment expenses
What can Structura Do?
Structura’s data mining techniques cluster and group loss characteristics to determine claim difficulty and assign a litigation propensity score, helping you predict which claims are most likely to drag on or result in litigation. From there, Structura can help you assign the most appropriate adjustor for a new claim based on claim type and adjustor experience. In some cases, claims can even be automatically adjudicated and settled. Your claims process becomes smoother, more efficient, and consistent across the board.
Settle Claims Better, Faster, Smarter.
Accurately predicting time to closure is crucial to ensuring accurate loss reserving. But with limited data available when a claim first comes in, predicting the duration of open claims can seem nearly impossible. And if your data isn’t dynamic and seamlessly integrated into your actuarial modelling workflow, reassessments in response to new information might be slow in coming, meaning your latest loss reserving calculations are inaccurate.
- Loss reserve assessments quickly becoming out of date
- Over and underestimation of necessary loss reserves wreaking havoc on your budget
And in the worst case scenario:
- Failure to meet regulatory requirements for loss reserving
- Inability to fulfill financial obligations putting you in danger of bankruptcy
What can Structura Do?
By analyzing the variables in similar losses, Structura’s analytics modelling helps you accurately estimate time to closure of new claims and calculate loss reserve on an ongoing basis. Since Structura’s calculations update dynamically in response to new information—whether that’s new accounts, new claims, or updates to ongoing claims—you’re never caught unprepared. Structura ensures that your loss reserves are carried appropriately from week to week, month to month, year to year.
Be Prepared for Anything.
Fast-track claims processes can be an invaluable tool. Not only do they keep your costs low, but they also ensure consistency across claims, which is particularly helpful when you’re inundated with claims arising out of a single event. But instant payouts can also lead to overpay and leave you vulnerable to fraudulent claims.
- Fraudulent claims going unnoticed
- Compounding of overpayments resulting in big hits to your bottom line
What Can Structura Do?
As an all-in one solution for claims processing, Structura can help you put an efficient fast-track process in place, without sacrificing revenue to overpayments. Structura’s analytics tools use past claims data to determine appropriate limits for instant payouts and pinpoint the moment a claim requires more direct oversight. You can also use historic data to build fraud detection models, flagging claims that have the markers of past fraudulent claims for closer inspection. That way, your labour goes where it’s most needed, without any fear of overpayments slipping through the cracks.
Settle Claims Efficiently and without Overpay
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