Explainability of compliance alerts

Introduction

Explainability of compliance alerts refers to the ability of an organisation to clearly explain why an automated system has generated an alert indicating a possible legal, regulatory, ethical or policy violation. Compliance alerts are commonly used in biotechnology, healthcare, financial services, environmental monitoring and data protection. These systems analyse information and identify activities that may require investigation, such as unauthorised access to genetic data, failure to obtain informed consent, irregular clinical-trial reporting or non-compliance with environmental standards.

An alert should not merely state that a violation has occurred. It should identify the relevant information, the rule or standard involved, the reason for the alert and the steps required for verification. Explainability is particularly important because automated alerts may contain errors, incomplete information or misleading conclusions.

Meaning and importance of explainability

Compliance alerts may be generated through rule-based software, artificial intelligence, machine learning or automated monitoring tools. Explainability ensures that the people receiving an alert can understand the basis of the system's decision.

For example, a biotechnology research institution may receive an alert because a researcher accessed confidential genetic information without the required authorisation. An explainable alert should identify the access event, the applicable access-control requirement and the reason the activity was considered suspicious.

Its main objectives include:

Transparency: Making the basis of an alert understandable.

Accountability: Identifying the department or individual responsible for reviewing it.

Accuracy: Allowing errors and false positives to be detected.

Fairness: Preventing individuals from being unfairly penalised by automated conclusions.

Auditability: Maintaining records of alerts, investigations and corrective actions.

Explainability also helps distinguish between a suspected violation and an established violation. An automated alert should generally initiate human review rather than automatically establish legal liability.

Legal framework in India

India does not have one comprehensive statute exclusively governing explainability of compliance alerts. However, several legal provisions support transparency, accountability and reasoned decision-making.

1. Digital Personal Data Protection Act, 2023

The Act establishes obligations concerning the processing of digital personal data, including responsibilities of Data Fiduciaries and safeguards for personal information. Where compliance alerts involve personal data, organisations must consider the applicable statutory duties, security requirements and lawful processing obligations. Its provisions must be applied subject to their commencement and applicable rules.

2. Information Technology Act, 2000

Sections 43A and 72A have historically addressed compensation for failure to protect sensitive personal data and disclosure of information in breach of lawful contractual obligations. Their present applicability must be considered alongside subsequent amendments and the commencement of the DPDP framework. The Act remains relevant to electronic records, cybersecurity and unauthorised access issues.

3. Information Technology (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, 2011

These Rules historically prescribed requirements relating to sensitive personal data, privacy policies and reasonable security practices. Their applicability should be assessed in light of the current statutory framework.

4. Bharatiya Sakshya Adhiniyam, 2023

The Act governs the admissibility and evidentiary treatment of electronic and digital records. Compliance-alert logs, system reports and audit trails may become relevant evidence in legal proceedings. Their reliability, authenticity and supporting technical records may therefore require examination.

Application in biotechnology and healthcare

Explainability becomes particularly important when automated systems monitor clinical trials, genetic research, laboratory activities and medical-device operations.

For example, an automated system may generate an alert because a clinical investigator has failed to upload a required safety report. The institution should be able to identify:

The particular reporting obligation involved.

The relevant deadline and reporting record.

The information that triggered the alert.

Whether the alert resulted from missing data or an actual procedural failure.

The person responsible for reviewing and resolving the issue.

In genetic research, explainability is also important when systems flag unusual access to genomic databases. Organisations should maintain access logs, explain the applicable permissions and provide an appropriate review mechanism.

Important judicial decisions

Although Indian courts have not established a comprehensive doctrine specifically dealing with explainability of automated compliance alerts, several judgments provide relevant principles.

1. State of Punjab v. Bhag Singh (2004)

The Supreme Court emphasised the importance of reasoned judicial decision-making. The judgment supports the broader principle that decisions affecting legal rights should be supported by understandable reasons. This principle is relevant when automated compliance findings influence disciplinary or regulatory decisions.

2. Kranti Associates Pvt. Ltd. v. Masood Ahmed Khan (2010)

The Supreme Court explained that recording reasons is an important component of fairness and transparency in administrative and quasi-judicial decisions. This principle supports the requirement that authorities should not rely solely on unexplained automated alerts when making consequential decisions.

3. Maneka Gandhi v. Union of India (1978)

The Supreme Court established that procedures affecting personal liberty must be fair, just and reasonable. The judgment provides a constitutional foundation for procedural fairness when automated compliance findings lead to serious consequences.

4. Justice K.S. Puttaswamy (Retd.) v. Union of India (2017)

The Supreme Court recognised privacy as a fundamental right under Article 21. This decision is important where compliance systems process sensitive personal, medical or genetic information. Explainability must therefore be balanced with privacy and confidentiality.

5. Shreya Singhal v. Union of India (2015)

The Supreme Court invalidated Section 66A of the Information Technology Act because of its vague and overbroad nature. Although the case did not concern compliance alerts, it demonstrates the importance of clear legal standards and safeguards against arbitrary enforcement.

Challenges and safeguards

Explainability may be difficult when organisations use complex machine-learning systems or commercially confidential software. However, commercial confidentiality should not automatically prevent regulators, auditors or affected individuals from receiving legally necessary explanations.

Organisations should adopt the following safeguards:

Maintain a written record of the rule or model responsible for generating each alert.

Preserve relevant input data, timestamps and audit trails.

Distinguish between preliminary alerts and confirmed violations.

Provide human review before imposing significant penalties.

Periodically test systems for bias, errors and false positives.

Establish procedures for correcting inaccurate alerts and recording the final outcome.

Conclusion

Explainability of compliance alerts is an essential element of transparent and accountable regulatory governance. It enables organisations to understand automated warnings, identify errors and demonstrate compliance with applicable legal obligations. Indian judicial principles concerning reasoned decisions, privacy and procedural fairness provide an important foundation for this area. As automated monitoring becomes more common in biotechnology and healthcare, organisations should ensure that every significant compliance alert has an understandable basis, supporting evidence and an appropriate human-review mechanism.