Data Analytics Skills for Insurance Claims Professionals
Using data to improve claims accuracy, operational speed, and fraud detection. Build practical, repeatable analytical models to scrutinise claims velocity, eliminate systemic leakage, unmask complex fraud clusters, and reinforce defensible adjudication decisions.
Claims Generate Constant Data.
Your Team Must Know What It Means.
Traditional intuition and manual file reviews are no longer sufficient to govern complex modern loss portfolios. Unlocking empirical patterns across settlement data protects loss reserves.
Claims Performance
Systematically monitor settlement volume, claim frequency, loss severity variations, and cycle velocity to expose operational roadblocks.
Leakage Control
Uncover systemic overpayments, duplicate disbursements, forgotten salvage salvage-credits, and arbitrary garage labor markup inflations.
Fraud Awareness
Identify suspicious collision staging clusters, unbundled medical provider billing, repetitive policyholder address networks, and abnormal repair timings.
Defensible Determinations
Equip front-line claims assessors and team leads with bulletproof empirical figures to defend legitimate repudiations and settlement offers.
You Do Not Need to Be a Programmer or Data Scientist
This MasterClass is engineered specifically for non-technical insurance leaders. We focus on master-level business spreadsheet analytics, structured Power Query pipelines, exception pivots, and visual Power BI executive cockpits that any claims professional can master.
What You Will Learn & Execute
10 tangible operational competencies every participant will take back to their underwriting organisation.
Analyse Claims Data
Identify micro-trends, seasonal surge patterns, operational velocity deficits, and emerging underwriting loss threats across lines.
Clean & Organise Claims Records
Establish rigorous data validation procedures to resolve duplicate entries, missing attributes, and messy unstructured claim logs.
Excel & Power BI Dashboards
Author responsive executive dashboards measuring loss ratio developments, open claim reserves, and SLA turnaround benchmarks.
Recognise Fraud Indicators
Spot atypical loss timing sequences, suspect loss-frequency anomalies, phantom passenger claims, and provider over-servicing red flags.
Detection & Risk Scoring
Construct weighted rule-based triage scorecards to classify high-risk files for manual SIU triage prior to claims disbursement.
Data-Driven Investigations
Equip special investigations units with structured digital audit trails, social link associations, and digital timeline evidence.
Assess Fraud Exposure
Calculate financial downside vulnerability by assessing unmonitored channel exposures across high-turnover insurance books.
Proactive Prevention Controls
Formulate hard operational controls and pre-approval approval thresholds to choke off systemic leakage before files enter settlement.
Claims Analytics Reporting
Translate messy operational statistics into crisp board-level summaries that clearly substantiate reserving shifts and operational KPIs.
Drive Operational Performance
Transform isolated analytical findings into daily departmental workstreams that curtail loss adjustment expenses and speed customer service.
8 Claims-Focused Course Modules
Module 01
Foundations
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Fundamentals of Claims Data Analytics
Role of data analytics in claims management; operational efficiency, loss ratios, and turnaround time; key metrics: frequency, severity, average cost per claim; moving from gut feeling to evidence-based claims settlement.
Module 02
Data Engineering
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Claims Data Preparation, Management & Quality
Claims data collection and structuring; identifying messy, duplicate, and missing records; segmenting claims data by line of business, cause of loss, geography, and claimant profile; ethical handling and data privacy governance.
Module 03
Tool Mastery
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Claims Analysis Using Excel & Power BI
Descriptive vs. diagnostic claims analytics; using PivotTables, complex formulas, and lookup tools to expose trends; building interactive dashboards for claims volume, paid vs. outstanding reserves, and aging analysis.
Module 04
Fraud Analytics
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Insurance Fraud Analytics & Indicators
Understanding common fraud schemes across Motor, Health, and Property; outlier analysis, frequency-severity spikes, and red-flag frameworks; detecting service provider collusion and inflated repair cost distributions.
Module 05
Predictive Triage
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Advanced Detection & Predictive Risk Scoring
Predictive analytics in fraud detection; rule-based scoring models vs. automated exception reporting; network and link analysis for identifying repeated claims rings; the role of machine learning balanced with human adjuster discretion.
Module 06
Investigation
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Data-Driven Claims Investigation & SIU Support
Using data to triage and prioritize high-exposure claims for physical investigation; digital evidence compilation and claims auditing trails; integrating fraud analytics into daily adjuster and SIU workflows.
Module 07
Internal Controls
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Fraud Prevention, Claims Controls & Mitigation
Spotting control gaps in claims authorization and settlement processes; designing early warning alerts and approval thresholds; measuring the financial ROI and leakage savings of analytics-driven controls.
Module 08
Executive Reporting
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Analytics Reporting & Operational Action Plans
Authoring claims intelligence reports for underwriting, board risk committees, and operational teams; communicating analytical findings clearly; creating an immediate 30-60-90 day claims analytics roadmap for your organisation.
Real-Life Insurance Claims Laboratories
Work with genuine, anonymised claims logs replicating actual operational challenges.
Commercial Fleet Repair Inflation & Parts Leakage
In this hands-on lab, delegates interrogate an actual 3,420-claim dataset from an urban motor portfolio. You will apply outlier formulas to match repair garage bills against OEM master parts pricing tariffs to identify anomalous systematic charges.
Engineered for Key Insurance Disciplines
Claims Officers & Adjusters
Looking to expedite routine verification, benchmark repair assessments, and transition toward senior analytical responsibility.
Claims Supervisors & Managers
Needing defensible loss performance tracking, adjuster productivity telemetry, and rigorous reserve governance dashboards.
Fraud & SIU Officers
Focused on establishing early predictive screening triggers, syndication identification, and empirical evidence chains for litigation.
Internal Audit & Risk Teams
Tasked with evaluating operational control effectiveness, leakage compliance, authorization limit auditing, and solvency integrity.
Technical Underwriters
Aiming to correlate historical claims cost distributions with risk rating classes to continuously refine product underwriting terms.
Heads of Claims & COOs
Seeking to modernize the institutional capability of their department through repeatable data standards and high retention.
“Designed for insurance professionals who work daily with claims records and want to extract decisive, bottom-line value from the data already sitting in their systems.”
Turn Claims Data Into Better Decisions.
Reserve your seat for the October session at the Fiesta Royale Hotel. Individual seats are confirmed upon corporate invoice clearance.
Organisations registering 3 or more participants receive priority group invoicing and tailored departmental simulation datasets.