Key Takeaway: Insurers who treat eDiscovery as strictly a cost miss out on transforming eDiscovery into an advantage. New strategies, especially those that use AI, create opportunities to lower risk and increase return on eDiscovery spend. eDiscovery becomes a predictable and value-driven endeavor when teams address the hidden drivers of discovery expense head-on, apply analytics early, and standardize workflows.

Too often, insurance companies have a limited view of eDiscovery, seeing it as simply a cost to minimize. This approach drives poor and risky decisions because decision-makers, caught between rising eDiscovery costs and stagnant budgets, are focused on narrowing the scope of eDiscovery as a way out of this bind. But this can easily backfire. Areas of risk may remain hidden, and insurers lack visibility into data that more comprehensive eDiscovery uncovers.

Insurers who take a targeted approach to addressing cost drivers, particularly those often overlooked, and use analytics intelligently, control costs and optimize operations while obtaining a strategic and business advantage.

When Expanding Demands Meet Fixed Budgets

When it comes to eDiscovery, the gap between insurers’ needs and their resources is growing. The former is relentlessly rising due to the combination of expanding discovery obligations beyond litigation (e.g., claims disputes, regulatory inquiries, cyber incidents, and internal investigations) and exploding data volumes. Meanwhile, resources (both budgets and headcount) remain flat, as evidenced by the Thomson Reuters Institute’s 2025 Legal Department Operations Index, which found that, across more than 125 legal departments, 55% face frozen or shrinking budgets, with 51% reporting no change in their legal technology budgets.

But the challenge for insurers goes beyond costs, expanding needs, or limited resources. Those challenges are compounded by the combination of wide swings in eDiscovery needs and hidden, indirect, and poorly tracked work that accumulates across matters.

Why Discovery Costs Escalate in Insurance

Discovery in insurance often begins with claims disputes, particularly where policy language is ambiguous, as may be the case with property, cyber, and specialty lines. 

Ambiguous language is only one of many drivers of discovery expenses. Others include claims file reconstruction, underwriting file pulls, and cross system searches. However, even though the work mirrors first pass discovery collection, the associated costs (e.g., legal holds, mailbox preservation, and system exports) are frequently categorized as claims support or analysis. IT or compliance budgets absorb such expenses, masking their true cost.

As a result, insurers may fail to systematically account for “hidden” discovery expenses like employee hours spent on eDiscovery duties, business disruption during regulatory inspections, and infrastructure costs for storing and processing data. With those expenses often absorbed into general operational budgets, insurers cannot appropriately account for them. 

The biggest invoice surprises are rarely a single line item. They are small per gigabyte charges, duplicate data processing, and review populations that grow incrementally until budgets are exceeded. This makes it critical to drill down and stay alert to four sources of “budget creep.”

Four Cost Drivers Insurers Often Miss

When cost drivers are readily apparent, addressing them is usually straightforward. But in the insurance content, four non-obvious patterns emerge as consistently inflating discovery spend:

• Overcollection and Redundancy: “Just in case” collections pull in every possible custodian and overly broad date range, often defaulting to policy inception through present.
• Late Stage Data Reduction: When culling and analytics are deferred at the outset, irrelevant data flows directly into review, the most expensive phase.
• Rework and Misalignment: Lack of clarity around ownership of discovery decisions leads to delays, revisited assumptions, and duplicated effort.
• Limited Early Insight: Without early case assessment (ECA), teams lack visibility into scope, risk, and likely exposure.

Limiting the impact of these four cost drivers requires both policy and process. Insurers must create, implement, and enforce explicit guidelines that dictate the scope of collections. Likewise, they must develop and adhere to well-defined workflows concerning ECA and the use of culling and analytics at the outset. Both guidelines and workflows must make clear who is responsible for what and with whom decision-making authority resides. These are the pillars of a cost-controlled discovery model.

Building a Cost Controlled Discovery Model

In establishing these pillars, insurers must treat discovery as an operational system rather than a series of one off projects. The most effective models share four elements: early scoping and assessment, automation first workflows, analytics driven review strategies, and centralized governance. The fastest gains come from fixing intake, minimizing data early, and applying advanced analytics where they reduce volume, not just speed. Note that technology, although important, is not among the four foundational factors. In fact, modernization efforts fail when teams start with tools rather than workflows.

The most reliable indicators of a successful approach are those focused on outcomes, not activity: lower per-document cost, a reduced percentage of spend devoted to review, and surface relevant documents with fewer reviews. Automation and analytics are especially impactful.

Automation as a Cost Control Mechanism

Automation is not a silver bullet, but applied early and consistently, it is one of the most effective ways to contain discovery costs. The strongest results come from automating repeatable, rules based tasks where consistency matters.

Legal hold management, standard data collection, and processing steps such as deduplication and metadata extraction are already well suited for automation. When these controls are applied upstream, they flatten downstream cost curves. Review becomes targeted rather than linear, and hosting, review, and production costs fall together.

When automation is applied too late or inconsistently across matters, insurers face compounding risk: irrecoverable overspend, inconsistent review outcomes, privilege issues, and defensibility concerns.

Using Analytics To Reduce Review Populations

Analytics can directly and substantially mitigate expense by reducing the number of documents that require human review. Deduplication, near duplicate grouping, email threading, and relevance ranking remove or deprioritize low value documents before reviewers see them. In fact, greater risk comes with manual review at scale as inconsistency and error rates increase.

Where Managed Services Deliver Financial Impact

Insurers often overlook the turnkey benefits of engaging a managed discovery services provider. The greatest cost control gains come when a provider replaces fragmented, ad hoc workflows with standardized operations. This is especially true for insurers handling repeat litigation, large electronically stored information (ESI) matters, or frequent scope changes. Whatever the particulars, a provider supports every crucial component of discovery, from early scoping and assessment to automation first workflows, analytics based review strategies, and centralized governance.

Those, along with standardized intake, consistent scoping, centralized data environments, and reuse of prior work reduce matter-to-matter variations in discovery costs. Over time, this shifts discovery spend from volatile and reactive to stable and forecastable. Finance teams often value this far more than abstract efficiency gains.

From Cost Center to Controlled Process

Discovery overruns are not inevitable. They are usually the predictable result of unmanaged inputs. For insurance portfolios, most matters are highly repeatable. A thoughtful approach to synergizing guidelines and workflows pays huge dividends, with maximum benefits achieved through automation, analytics, and managed services. 

Taken together, they enable carriers to avoid cost overruns at the outset, promptly contain those that arise, and ensure unanticipated costs are justifiable. This transforms discovery from an unpredictable expense with inconsistent results and myriad tradeoffs into a controlled, defensible activity with resources aligned to business needs. That level of control is what allows insurers to move from reactive cost management to predictable, scalable discovery operations. 

Learn more about Epiq eDiscovery for Insurance.

 
Mandy Pierre-Blanks, Senior Director, Client Services, Insurance Practice Group
Mandy Pierre-Blanks enables insurance and financial services clients to improve their matter outcomes by aligning workflows, applying proven litigation support practices, and ensuring consistent, cost-controlled delivery. 

At Epiq, she supports complex matters for enterprise clients and coordinates cross-functional resources to meet case objectives.