Building Strong Controls for Insurtech Partnerships
Insurtech partnerships can help insurers modernize underwriting, claims, billing, customer service, payments, and regulatory reporting. They can also introduce unfamiliar vendors, cloud environments, application programming interfaces, data flows, and revenue models into established operating processes. The speed that makes a technology partnership attractive can make control weaknesses difficult to detect.
A robust internal control framework gives insurers a disciplined way to manage these relationships without blocking innovation. It connects third-party risk management with finance, information security, compliance, actuarial oversight, operations, and executive accountability. The objective is not to eliminate every technology risk. It is to identify material exposures, assign ownership, establish evidence, and respond before a weakness affects policyholders or financial statements.
For insurance leaders attending an event such as IASA Conference, this topic sits at the intersection of accounting, technology, risk management, tax, customer administration, and professional development. A practical control model helps those functions use a shared language when evaluating insurtech providers and monitoring performance after implementation.
Define The Partnership Risk Profile
The control environment should begin with a clear description of what the insurtech partner does and what the insurer remains responsible for. A vendor that supplies a customer communication platform creates a different risk profile from one that calculates premiums, makes claims recommendations, holds personal data, or posts transactions directly to the general ledger.
Document the services, systems, data categories, jurisdictions, transaction volumes, access privileges, and dependencies involved. Identify whether the provider supports a critical business process, influences a regulated decision, or can affect reported financial results. This information allows the insurer to apply proportional due diligence instead of using the same checklist for every supplier.
Risk classification should also account for concentration. Several products may depend on the same cloud provider, identity service, payment processor, or data broker. A disruption at one underlying provider could therefore affect multiple insurance operations at once. Enterprise risk teams should map these common dependencies and include them in scenario analysis.
Establish Governance And Accountability
A partnership needs a named business owner with authority to make decisions, monitor controls, and escalate concerns. That owner should work with procurement, legal, compliance, cybersecurity, finance, internal audit, and the relevant operational leaders. Responsibilities should be recorded in a RACI matrix or equivalent governance document so that control gaps cannot be attributed vaguely to “the vendor.”
The board or a delegated risk committee should approve relationships that meet defined materiality or criticality thresholds. Approval criteria may include access to sensitive information, influence over claims or underwriting, impact on statutory reporting, and inability to replace the provider within an acceptable period. Senior oversight is especially important when a new technology introduces automated decisions or machine learning models.
Contracts should reinforce this governance structure. They need clear service levels, audit rights, data ownership terms, breach notification periods, subcontractor disclosure, business continuity obligations, regulatory cooperation, and secure termination procedures. The agreement should also specify what evidence the provider must supply, such as independent assurance reports, penetration-test summaries, control certifications, or remediation updates.
Design Controls Across The Partnership Lifecycle
Controls should operate before onboarding, during implementation, throughout service delivery, and at termination. Pre-contract due diligence can assess the provider’s financial stability, security program, privacy practices, regulatory history, control reports, insurance coverage, and experience with comparable insurers. The review should evaluate actual risks rather than treating a certification as a complete substitute for judgment.
Implementation controls should include segregated duties, approved configuration changes, data validation, interface testing, user acceptance testing, and reconciliation to authoritative systems. If an insurtech platform sends transactions into a policy administration or accounting system, the insurer should test completeness, accuracy, timing, duplicate prevention, and exception handling. Manual workarounds should be documented and reviewed, especially during a transition period.
Once the service is live, monitoring should combine operational metrics with control evidence. Useful indicators include failed interfaces, unresolved exceptions, downtime, access violations, delayed claims activity, unexplained ledger variances, data-quality defects, and missed service levels. A recurring review calendar ensures that monitoring continues after the partnership has moved beyond its launch team.
Termination controls deserve equal attention. The insurer should be able to retrieve data in a usable format, revoke credentials, disable integrations, settle outstanding transactions, preserve required records, and confirm deletion where appropriate. A documented exit plan reduces dependence on a provider and tests whether continuity assumptions are realistic.
Connect Technology Controls To Financial Reporting
Insurtech arrangements often affect financial reporting indirectly. A platform may determine premium classifications, calculate commissions, support claims reserves, process refunds, allocate expenses, or generate information used in tax filings. Finance and accounting teams therefore need visibility into system logic, data lineage, interfaces, and manual adjustments.
A useful approach is to map each significant financial statement assertion to the technology and business controls that support it. Completeness may depend on interface reconciliations. Accuracy may depend on approved rate tables and configuration controls. Cutoff may depend on timestamp synchronization and period-close procedures. Authorization may depend on role-based access and documented approval workflows.
Service organization control reports can provide valuable evidence, but their scope and testing period must be examined carefully. Determine whether the report covers the relevant application, hosting environment, interfaces, subservice organizations, and control objectives. Complementary user entity controls should be assigned internally and tested as part of the insurer’s own control program.
| Control area | Typical partnership exposure | Evidence to retain | Responsible functions |
|---|---|---|---|
| Access management | Excessive vendor or employee privileges | Access reviews, approval records, termination logs | Information security, operations |
| Data integrity | Incomplete, duplicated, or altered records | Interface reconciliations, validation results, exception reports | Operations, finance, data governance |
| Financial reporting | Incorrect postings or unsupported calculations | Configuration approvals, control reports, journal reconciliations | Finance, accounting, vendor owner |
| Privacy and security | Unauthorized disclosure or weak protection | Security assessments, incident logs, encryption evidence | Privacy, cybersecurity, legal |
| Service continuity | Outage or provider failure | Recovery tests, continuity plans, recovery metrics | Business continuity, operations |
| Model governance | Unexplained or biased automated decisions | Model inventory, validation, change records | Risk, actuarial, compliance |
Govern Data, Models, And Automated Decisions
Data governance must cover collection, use, transfer, retention, and deletion. Insurers should know which information enters the partner’s environment, where it is processed, who can access it, and whether it is used to train or improve a product. Contract terms should prevent unauthorized secondary use and establish practical controls for data subject requests, correction, retention, and disposal.
Machine learning and automated decision tools require additional oversight. A model used for fraud detection, underwriting support, claims triage, or customer segmentation should have a defined purpose, accountable owner, approved input data, documented assumptions, and performance thresholds. Validation should consider accuracy, drift, explainability, disparate outcomes, and the consequences of false positives or false negatives.
Human review needs to be meaningful rather than symbolic. Employees should understand when they can challenge an automated recommendation, override it, or refer a case for specialist assessment. The insurer should retain enough decision history to reconstruct how an outcome was reached, particularly when customers, regulators, auditors, or courts may request an explanation.
Partner evaluations can be strengthened through direct conversations with technology providers and consultants. An exhibit hall such as the exhibitor resources available through IASA Conference can help industry professionals compare solution capabilities, ask about control evidence, and explore how vendors support auditability and integration.
Monitor Performance And Test Effectiveness
A framework becomes credible when it produces evidence that controls work over time. Monitoring should distinguish between design effectiveness and operating effectiveness. A policy may require quarterly access reviews, for example, but testing must establish whether the reviews occurred, covered the right users, identified inappropriate access, and resulted in timely remediation.
Internal audit can use a risk-based testing plan that prioritizes critical processes, high-impact data, material financial interfaces, and providers with unresolved findings. Testing may include walkthroughs, sample-based reviews, configuration inspection, reconciliations, control self-assessments, and review of independent assurance reports. Findings should have an accountable owner, due date, severity rating, and documented closure evidence.
Incident management should be integrated with third-party oversight. A failed claims interface, privacy event, unexplained payment, or model anomaly may require notification to several internal functions and external authorities. Playbooks should define escalation thresholds, communications responsibilities, evidence preservation, customer impact assessment, and post-incident review.
Performance dashboards can make governance more useful to executives. Instead of reporting only whether a vendor submitted a monthly report, dashboards should show trends, control exceptions, overdue remediation, material incidents, concentration exposure, and the status of continuity tests. This turns vendor oversight into a decision-support process rather than a compliance archive.
Practical Priorities For Implementation
A phased rollout helps an insurer improve control maturity without waiting for a complete enterprise redesign. Begin with partnerships that have the greatest effect on policyholders, regulated activities, financial reporting, or sensitive information. Use those relationships to test the framework, refine evidence standards, and establish realistic reporting routines.
The following priorities can guide the first implementation cycle:
- Create a complete inventory of insurtech partners, services, data exchanges, subcontractors, and critical dependencies.
- Assign an accountable executive and operational control owner to every material partnership.
- Map key processes from customer or policy activity through technology interfaces and financial reporting.
- Standardize minimum contract terms for audit rights, incident response, continuity, data use, and termination.
- Establish a recurring testing calendar with risk-based monitoring, documented findings, and executive reporting.
Training should accompany each control change. Procurement teams need to recognize technology and concentration risks. Finance professionals need to understand system-generated data and interface reconciliations. Operations teams need clear exception procedures. Executives need concise information about residual risk, remediation progress, and decisions requiring approval.
The framework should be reviewed whenever the partner changes its architecture, introduces a new model, adds a subcontractor, expands into a new jurisdiction, or materially changes how data is used. Annual review alone may be inadequate for fast-moving technology arrangements. Change-triggered reassessment keeps controls aligned with the service actually being delivered.
Insurers that bring these disciplines together can pursue digital partnerships with greater confidence. Begin by selecting one critical relationship, documenting its risk profile, assigning ownership, and testing the controls that protect customers, operations, and financial reporting. Then use the results to strengthen the broader program and make control assurance a normal part of every technology partnership.