The module itself is covered on the claims management software page. This page is about the analytics layer that sits on it.
claims dashboard
Who it is for
- Carriers (all business lines)
- Managing General Agents (MGAs)
- Third-party administrators (TPAs)
- Carriers running a captive or alternative-risk book
- Finance and reinsurance teams that need loss and reserve visibility
Who it is not for
It is not the right fit if you need a claims system rather than analytics, if your claims sit in a platform whose data cannot be moved, or if you want analytics across underwriting and policy as well as claims. The first belongs to claims management, the last to the insurance data warehouse.
Does your claims team recognize these problems?
Claims data is in disconnected systems
Adjusters monitor FNOL and reserve changes via spreadsheets, emails, or chats.
Executives get the numbers late
Loss ratio, reserve, and paid totals get assembled manually; executives get reports with outdated data.
No built-in view of claims statuses
No single place showing which claims breach SLA, are unassigned, or aging past target cycle time.
Adjuster performance is unclear
You don’t have a comparable view of cycle time, reserve accuracy, and reopen rate per adjuster.
Leakage is only visible after the fact
Overpayments, settlements above reserve, and missed recoveries show up in aggregate at quarter end, when it is too late to act on the individual claim.
Core capabilities
Example of insurance data analytics implemented by DICEUS
insurance data analytics
Need claims analytics?
Workflow: how claims data reaches the dashboards
A claim moves through four stages inside the Claims Management module, and the analytics layer reads from all of them without a separate reporting step. Every event on a claim is recorded once in the module, and the dashboards read it from there.
Analytics components
Integrations
Claims analytics is part of the DICEUS Claims Management Module, and the dashboards read the claims data from the module. No separate data feed is needed. We can integrate data from your existing systems, such as a core platform, billing and payment system, CRM, or external sources, with the scope confirmed during discovery.
If claims are managed in another system today, we scope moving the claims register into the module during implementation.
For analysis that reaches beyond claims into underwriting, policy, and premium, the same data can feed an insurance data warehouse.
Implementation overview
- Discovery. We review your current lines of business, claim segments, insurance program structure, and the systems that need to provide data to analytics.
- Configuration. Dashboards, KPIs, filters, and reimbursement views are set up to match what you confirmed in discovery.
- Data migration. Historical claims data is mapped and loaded, so trend views (FNOL, reserve development, loss ratio history) aren’t starting from blank pages.
- Training and rollout. The DICEUS team will onboard your adjusters, claims leadership, and finance on the views relevant to their role.
- Launch and adjust. Dashboards, segments, and rules are adjusted as your program structure or reporting needs change.
Implementation of DICEUS insurance software products depends on the number of functionalities you need. It may take from 4 weeks to 6–9 months. Exact timelines are fully agreed upon upfront.
Data types that can be analyzed by claim analytics systems
Our claim analytics can collect and analyze various types of data to predict risks, identify and prevent fraud, speed up claim resolution time, and reduce operational costs. To set up the right analytics, we start with a deep analysis of what data you currently use and what data you would like to leverage, and which systems need to be integrated.
- Claim data
- Policyholder and customer data
- Product and policy data
- Operational data
- Documents and media
- External data (credit reports, vehicle history, medical history, etc.)
Why choose DICEUS claims analytics software
DICEUS has been building and providing software and technology solutions for insurance businesses since 2011, with direct experience in claims management, underwriting, and policy administration. Our teams have delivered software for insurers and brokers, including The Baldwin Group, Vienna Insurance Group, UNIQA, WTW, and Fairfax Group.
All dashboard on this page are real examples of analytics implemented by DICEUS. Want to see how it works?
How DICEUS claims analytics software differs from other solutions
| Capabilities | DICEUS claims analytics | Spreadsheets / manual exports | Generic BI tool on top of claims data | Core system’s built-in reports |
| Real-time view of open claims, reserves, paid | Live, reads the claims register directly | Manual refresh, stale as soon as it’s shared | Depends on refresh schedule | Often available for totals only |
| Ad-hoc filter builder on any claim field | Built in | Manual filtering each time | Needs BI-team setup per request | Rarely available |
| Adjuster performance benchmarking | Built in, side-by-side comparison and score | Possible, but manually compiled | Possible if adjuster data is modeled separately | Rarely available |
| Captive/reimbursement program analytics | Built in, tied to the same claims register | Usually a separate spreadsheet | Needs custom modeling of program data | Not typically supported |
| Configurable LOB and segment structure | Configured during implementation | Fully manual | Configurable, requires BI development time | Fixed to the vendor’s data model |
| Separate reporting stack to maintain | Not needed, analytics reads operational data directly | Not applicable | A separate BI layer | Limited to what the core system reports |
Examples of dashboards
Wealth management dashboard
Customer data dashboard
Reports dashboard
Stock history executive dashboard
Homerun auto-insights dashboard
Insurtech dashboard
Arrest incidents dashboard
Our partners
Our ready-made software products for insurance
Along with custom software development services, our company offers ready-made solutions for insurers, brokers, MGAs, and TPAs.
Testimonials
Elena Markova
Board Member, UNIQA Ukraine
We were impressed by the depth of the UX analysis they did in terms of our customer’s research, buyer persona creation, user journey mapping, etc. All the information like research findings, for instance, was presented in a clear form (presentations, Miro boards, clear infographics) so it was quite easy to understand what we need to build and why.
Antoaneta Karagyozova
CPSO, Fadata
We are happy with DICEUS’ software implementation services. The team’s workflow is highly effective and professional in all aspects of the engagement. All clearly understand what goals we’d like to reach and do their best to do that as efficiently as possible. Overall, the partnership has been successful.
Phil Reynolds
CEO, BriteCore
The DICEUS team has consistently supported the BriteCore team for many years. Their engineers are well-educated and highly invested in the ongoing quality of the BriteCore platform with sustained relationships that extend over four years. We appreciate everything the DICEUS team brings to the table as a development partner.
Our case studies
See your claims data on a live dashboard.
FAQ
We already run claims through another system. Can this analytics module sit on top of it?
The dashboards are built on the claims data inside our Claims Management module. If claims are managed elsewhere today, moving the register or, at minimum, reproducing the fields shown here, such as FNOL, reserves, adjuster assignment, and reimbursement, is what we scope during implementation.
We’re a small company with a limited number of claims a year. Is this overbuilt for us?
No. The dashboards and filter builder work the same at low claim volumes; only the configuration changes. A program with a handful of open claims still benefits from seeing reserves, SLA status, and reimbursement in one register instead of a spreadsheet.
We built our own claims tracking spreadsheet or BI report. Why move off it?
A spreadsheet or a BI report built on an export is accurate on the day it’s built and starts drifting the moment someone edits the source file outside it. These dashboards read the same register adjusters and TPAs update directly, so dashboards stay current without a separate refresh step.
Our claims are handled by a TPA. Does the analytics still work for us?
Yes. Reimbursement Claims and Reimbursement Analytics were built for exactly this structure – tracking deductible reimbursement and underlying insurer recoveries by program, separate from the primary claim record, which is how most companies run through a TPA.
We only need one or two dashboards, not the whole set. Can we start there?
Yes. Each dashboard reads from the same register, so it’s possible to configure and roll out one view first and add the others later without rebuilding the data model.
Does this replace our BI tool?
No, and it is not meant to. Your BI tool reports across the business; this reports on the claims register, from inside the system the register lives in. Teams that keep both use these dashboards for day-to-day claims decisions and send the same data onward for company-wide reporting.
How do these dashboards help with claims leakage?
Leakage appears as settlements above reserve, recoveries identified but never collected, and payments outside the segment’s normal range. The views put all of those in the same place as the claim they belong to, so they are displayed while the claim is open rather than at quarter end.
Which lines of business does it cover?
All of them, because the structure is configured. Lines of business, claim segments, and KPI thresholds are set up during implementation, which is why a motor book and a medical stop-loss programme can run the same dashboards with different definitions underneath.
