Process mining to expose insurance claims bottlenecks

Claims delays rarely come from one slow task. They accumulate when notifications go unread, assessors wait for repair quotes, and payments return for missing details. Using process mining to identify bottlenecks in insurance claims operations turns those fragments of experience into a replay of how cases actually move.

The method connects timestamps, case identifiers and activities across claims, policy, customer and finance systems. It exposes normal paths, detours and exceptions, giving executives and operational teams a shared view of cycle time, workload and handoffs. The priority then rests on evidence rather than whichever queue is loudest.

Turning claims records into process evidence

A process mining event log needs consistent meaning rather than elaborate presentation. Each row records a case, an activity, when it happened and, where available, the person or system involved. A useful log follows a file from first notice of loss through triage, assessment, repair or replacement, settlement and payment. Recording the event, instead of only a status update, preserves the sequence behind the delay.

Logs often combine claims administration, CRM, estimating and accounting platforms with communication records and external assessor data. Teams should reconcile milestone names, preserve original timestamps and distinguish event time from recording time. A backdated note must not make a long queue resemble a short task. Privacy controls belong at extraction, before sensitive case details are copied into spreadsheets.

Geography shapes both the log and the interpretation. Claims hubs in Sydney, Melbourne and Brisbane coordinate work across metropolitan and regional areas, while travel and remoteness affect property assessments. Location, channel and severity help teams distinguish a metropolitan motor claim from a complex property loss. The Australian mix of motor, home and general insurance adds further variation in documents, repairs and referrals.

Finding the queues that consume capacity

Discovery searches the event log for common process variants. One claim may move directly from notification to assessment; another may be reopened twice because photographs, estimates or customer details arrived in the wrong format. Averages can hide these detours, so conformance checking compares actual behaviour with the approved workflow and identifies where reality departs from the intended procedure.

The longest activity is not necessarily the largest constraint. Waiting before assessment can greatly exceed hands-on assessment time, while rework, duplicate entry and unresolved handoffs consume capacity without appearing in a conventional backlog. Useful measures include median and upper-percentile cycle time, touch versus waiting time, queue length, first-time-right rate, rework frequency and assessor throughput. Segment results by product, severity, location and channel so that a useful signal is not buried in a blended average.

Resource-based analysis can show whether one escalation team holds too many decisions, whether assessors receive incomplete briefs, or whether finance staff repeatedly check the same fields. These findings are hypotheses, not proof of cause. Interviews with handlers and service staff can explain why a queue forms; workload and system evidence can then test that explanation.

Matching controls to Australian claim conditions

Improvements must survive Australian operating conditions. Bushfires, hail, flooding and storms can push claims volumes far beyond a steady-state pilot, creating a different constraint from routine work. A process that relies on one triage desk may cope on an ordinary day and fail when thousands of notifications arrive within days. Scenarios should therefore include catastrophe claims, backlog clearance and reduced staffing.

Claims files can contain health, financial and identity information, so event-log design should follow the Privacy Act 1988 and the Australian Privacy Principles. Purpose limitation, access controls and secure retention apply to process analytics as much as customer servicing. Personal information should not appear in a presentation because a case identifier is visible elsewhere. A privacy impact assessment and agreed masking rules should precede broad analyst access.

Complaint handling adds another control point. Relevant general insurance complaints should follow the internal dispute resolution pathway set out in the Australian Securities and Investments Commission’s Regulatory Guide 274, and unresolved matters may proceed to the Australian Financial Complaints Authority. Better workflow should reduce avoidable dispute triggers, such as unexplained assessments and missed status updates, without removing legitimate review. Measures can monitor complaint causes alongside queue age and rework.

Customer communications belong within the same process. A missed document request can create weeks of waiting, while an unclear status message can generate another contact and handling step. The lesson in transactional email psychology is that specific, relevant messages outperform generic outreach, although claims communication should focus on progress and required action rather than premature selling. Australian marketing messages must also meet the Spam Act 2003, including consent, sender identification and unsubscribe requirements where applicable.

A practical pilot for claims teams

A focused pilot offers a stronger result than an insurer-wide search for efficiency. Select one queue with meaningful customer impact, such as assessment referrals, complex property notifications or settlement corrections. Establish a baseline from several months of event logs, define the desired result and record the constraints to improvement. Claims operations, finance, data, technology, customer service and risk should share ownership of the response.

The pilot should test operational changes as well as reveal analytical patterns. A faster workflow click does not help when handlers still await the same information. Each change needs an owner, an acceptance test and a review date. These measures and tests keep the work tied to customer, staff and financial outcomes.

• Cycle time: Track median and 85th-percentile elapsed time, plus the longest waits between milestones, by product and severity.
• First-time-right completion: Measure the share of claims approved, settled or paid without reopening, correction or duplicate entry.
• Queue age and work in progress: Record waiting time for assessment, documents, repair authorisation and payment.
• Rework and failed handoffs: Count returned files, incomplete briefs, duplicate tasks and approvals that move backwards.
• Service and cost outcomes: Relate cycle time to complaints, contact volumes, abandonment and claims handling cost, without weakening quality checks.
• Standardised intake: Test whether consistent first-notice data reduces clarification contacts and assessment referrals.
• Pre-validated submissions: Test checks for estimates, invoices and supporting documents before human review.
• Capacity rules by severity: Test dynamic queues and escalation thresholds instead of one sequence for every claim.
• Clear ownership at handoffs: Test named decision rights and service expectations between claims, assessors and finance.
• Controlled comparison: Use a matched branch, team or before-and-after cohort to separate process effects from seasonal changes.

Turning findings into sustained performance

Event logs create a baseline, but sustained gains depend on governance. Assign an owner to every significant variant and review exceptions rather than treating the longest step as the permanent target. Put queue measures into the routine claims meeting, link them to the risk register and test whether capacity changes genuinely reduce waiting. A revised dashboard without changed decision rights will soon become another report nobody uses.

Technology should follow the redesigned process, not substitute for it. Configurable workflow rules may remove duplicate entry, while better case summaries can reduce handoffs between claims and finance. The business case should include implementation effort, licence costs, training, data maintenance and the capacity released. Reserving teams can use timely claims data to reassess exposure; as real-time claims reserving explains, faster evidence can improve the accuracy of estimates without forcing claims teams to wait on finance.

Change also requires a control against gaming. If handlers optimise only for speed, they may defer difficult work or omit evidence. Pair elapsed-time measures with quality, complaint and rework indicators, then examine outliers with experienced staff. Publish the measures, invite teams to challenge misleading classifications and revise the log when the process changes. A living model remains more useful than a one-off efficiency diagnosis.

The immediate action is to choose one expensive queue, secure a clean slice of event-log data and appoint an accountable pilot lead. Within 90 days, the team can establish a baseline, test a focused change and quantify both capacity released and customer impact. That evidence will determine whether to extend the work, revise it or stop.

Bring the pilot’s process questions and early evidence to IASA Conference, where insurance executives, finance professionals, operations teams and emerging leaders can exchange practical approaches with technology vendors, consultants and software providers. Explore the programme sessions on claims operations, technology and risk, then build a cross-functional team around one measurable result. Start with the queue that is costing the most waiting time, not the one with the easiest dashboard.