Compliance
Assurtech AI delivers operational compliance for insurance brokers: audit trail, access control, data governance, evidence retention, logging and support for GDPR and AML/CFT requirements.
Compliance and security are not added after development. They shape the functional and technical architecture from the start.
The platform is designed to: produce evidence, limit operational risks, trace decisions, control access and structure responsibilities. Compliance becomes a property of the system.
Every significant action performed in the platform is:
This includes in particular the creation or modification of a policy, validation of a document, modification of a configuration item, interaction with AI and validation of a recommendation.
The objective is twofold: protect internal decisions and support clear reporting during audit, review or dispute.
Logging covers:
Logs are centralised, protected against alteration and retained according to a defined retention policy.
Retention complies with applicable regulatory requirements, periods appropriate to the relevant business objects and obligations related to internal controls.
The platform makes it possible to demonstrate:
This auditability capability is essential for internal controls, external audits and any request for regulatory justification.
The platform is designed to limit data collection to what is strictly necessary. Forms and processes avoid unjustified fields, distinguish mandatory data from optional data and structure information according to its purpose. Minimization is not merely declarative. It is built into the design of screens and flows.
Personal data protection relies in particular on encrypted communications, role-based access control, separation of environments, centralised secret management and monitoring of sensitive access. Access rights are granted according to the principle of least privilege. A user may access only the data necessary for their function.
The structuring of data makes it possible to identify data linked to an individual, correct information, export data when necessary and anonymize or delete according to applicable rules. Sensitive operations are traced, attributed and documented.
Each structured processing activity in the platform corresponds to an identified purpose, relies on a legal basis and can be documented. Significant changes may give rise to an impact assessment where necessary. Regulation (EU) 2016/679 (GDPR) compliance relies on the articulation between technical architecture, business rules and internal governance.
Anti-money laundering and counter-terrorist financing (the EU AML/CFT framework, with EU-level AML/CFT responsibilities now carried by the Anti-Money Laundering Authority (AMLA)) relies on identifying parties, collecting supporting documents, tracing checks and retaining evidence. The platform makes it possible to associate identification elements, collected documents, control dates and the identity of the reviewer with a file.
The due diligence performed is recorded, time-stamped and linked to a specific file. In the event of internal or external review, it is possible to demonstrate: the steps followed, the documents reviewed and the validations performed. The platform does not replace human analysis. It structures the evidence of that analysis.
In insurance brokerage, compliance cannot be limited to internal policies or principle documents. It must be embodied in the tools, processes and evidence produced day after day.
When a firm relies on fragmented systems, compliance becomes difficult to demonstrate: dispersed validations, unstructured documents, incomplete histories and poor visibility of responsibilities.
A properly designed business platform makes it possible to link significant actions to a user, a date, a documentary context and an identified file.
Compliance then becomes more demonstrable, more auditable and more integrated into the firm’s operational reality.
The goal is not only to comply with a rule. The goal is to be able to evidence, explain and retrieve what was done.
Taking Regulation (EU) 2016/679 (GDPR) into account in insurance brokerage software is not a matter of legal posturing. It requires a concrete structuring of processing activities and access rights.
Data protection becomes more robust when the functional architecture genuinely supports regulatory requirements.
The requirements of the EU AML/CFT framework, with EU-level AML/CFT responsibilities now carried by the Anti-Money Laundering Authority (AMLA) imply a rigorous organisation of identification, controls, supporting documents and validations.
A suitable business system must make it possible to associate collected elements, verification dates, the identity of the reviewer and the supporting documents used with a file.
This structuring reduces blind spots and facilitates both internal reviews and external controls.
It also makes it easier to distinguish what was verified, by whom, when and on the basis of which documentary evidence.
The value of a control does not lie only in its existence. It also lies in the firm’s ability to retain usable evidence of it.
The compliance of an insurance platform also depends on its ability to control who may do what, within which scope and with which level of traceability.
Logging and access controls are not accessory mechanisms. They form a foundation of operational and regulatory control.
In a regulated sector, it is not enough to execute an operation correctly. It must also be possible to document its reality, its context and its chronology.
A suitable platform retains the elements needed to justify a validation, a control, a file modification or a structuring decision.
This auditability facilitates internal controls, external audits, quality reviews and the handling of sensitive situations.
It also improves operational discipline, because important actions become more readable, more attributable and easier to verify.
Credible compliance rests on a lasting ability to justify actions, not on fragile organisational memory.
The Insurance Distribution Directive (IDD) requires intermediaries to structure the distribution relationship, formalize certain due diligence steps and retain evidence of the elements relevant to advice, information and client follow-up.
The platform does not replace regulatory analysis or the firm’s obligations. It provides a more structured framework for documenting the journey, retaining evidence and reducing operational blind spots in distribution.
The platform helps the firm structure evidence of the distribution journey, retain significant elements of advice and improve the readability of the due diligence carried out.
The platform relies on a structured cloud infrastructure. The principles applied include separation of environments (development, testing, production), centralised identity management, role-based access control (RBAC) and logging of critical events. The architecture is designed to limit unauthorised access, untracked changes and fragile technical dependencies.
Access is individual, authenticated, subject to reinforced security rules and periodically reviewed. Roles are defined according to business functions, responsibilities and the principle of segregation of duties where relevant. Sensitive access may be subject to enhanced controls and specific validations.
Sensitive elements (keys, secrets, technical identifiers) are not stored in code. They are centralised, protected and subject to rotation rules. This organisation limits the risk of accidental exposure.
The platform implements regular backups, a defined retention policy and periodic restoration tests. The objective is to guarantee data availability, recovery capability and operational continuity.
AI operates as assistance. Certain categories of use may impose mandatory human validation, confidence thresholds and limitations on documentary scope. The rules are defined and documented.
The following are versioned: models used, documentary corpus, generation rules and instructions addressed to the model. Each important interaction keeps the query, the context used, the response produced, the user and the date.
AI: cites its sources, indicates the scope used, does not make autonomous decisions and does not rely on an indeterminate corpus. Final decision-making remains with the user.
The regulatory environment evolves. The platform is designed to:
The technical modularity makes it possible to integrate changes without calling the overall architecture into question.