Modernising Timecard Review With GenAI-Powered OTL Anomaly Detection

Public sector environments operate under complex rules for time reporting. Factors like union agreements, varying pay scales, overtime rules, and compliance requirements mean that each timecard can carry dozens of variables that must be validated.

In traditional workflows, payroll teams spend hours reviewing thousands of entries, comparing them against schedules, contracts, and policy rules. Even with automated OTL validation rules in Oracle ERP, some anomalies slip through — either because they are too subtle for rule-based detection or because the rules cannot account for all exceptions.

The result is a double challenge: inaccurate timecards lead to payroll disputes and compliance risks, while the time spent on manual reviews strains already limited resources.

Generative AI offers a new way to manage OTL data. Instead of relying solely on static rules, GenAI models can learn from historical timecard data, recognise patterns, and identify deviations that might indicate an error.

The process starts by feeding AI with validated historical OTL records, payroll results, and exception reports. The model learns what “normal” looks like for different job roles, departments, and time periods. When new timecard data is submitted, the AI compares it against expected patterns and flags anomalies — even if they don’t violate a specific system rule.

This approach doesn’t replace Oracle ERP’s built-in validation rules; it enhances them. AI acts as an intelligent layer that finds potential issues human reviewers might miss, allowing payroll teams to focus only on flagged entries instead of reviewing everything.

In the public sector, the implications are significant. Local governments can process payroll for thousands of employees faster, universities can ensure academic staff time is accurately allocated across teaching, research, and administrative duties, and healthcare providers can ensure complex shift-based schedules are reflected accurately.

The impact is felt in three major areas:

• Time savings — Payroll teams can focus review efforts where they are needed most.
• Accuracy — Subtle anomalies, such as repeated underreported overtime, are caught early.
• Compliance — Reduces risk of non-compliance with labour laws and union agreements.

Public sector payroll accuracy isn’t just about paying employees correctly — it’s about maintaining trust, ensuring compliance, and optimising budgets. Every payroll dispute or compliance breach costs time and money, and the reputational risk is significant.

In both the UK and the US, public sector bodies are under increasing pressure to modernise operations and improve efficiency. Workforce data accuracy is a key component of this push, and OTL anomaly detection powered by AI is a direct enabler of these goals.

One of the strengths of the Firstcron approach is that it works seamlessly with Oracle HCM Cloud’s OTL module. AI models can be deployed alongside existing validation frameworks without replacing them. The anomaly detection process fits naturally into the payroll cycle:

1.Time Entry Submission — Employees enter their time into Oracle ERP OTL.

2.Standard Validation — Built-in OTL rules check for standard compliance.

3.AI Analysis — GenAI reviews the time data for pattern deviations.

4.Flagging and Review — Only timecards flagged by AI are reviewed by payroll teams.

5.Approval and Payroll Processing — Once anomalies are resolved, payroll runs as normal.

This dual-layer approach ensures that no single method is solely responsible for quality control, dramatically increasing reliability.

Public sector organisations operate in highly regulated environments. When introducing AI into payroll processes, data security is paramount. Firstcron ensures:

• AI processing occurs in secure, compliant environments.
• Data handling aligns with UK GDPR, US FedRAMP, and HIPAA (for healthcare).
• Access controls and audit trails are maintained to meet internal and external audit requirements.

By building these safeguards into the AI framework, organisations can adopt GenAI without compromising their compliance posture.

The success of AI-driven OTL anomaly detection depends on more than just the technology. Payroll and HR teams must be trained to interpret AI results, understand why certain anomalies are flagged, and take corrective action efficiently.

Firstcron supports clients with structured change management plans, including:

• Documentation on AI logic and interpretation.
• Gradual rollout phases to build confidence in the system.
• Training sessions for payroll and HR staff.

While private sector companies are already moving quickly toward AI-assisted payroll processes, the public sector has been slower to adopt. By integrating GenAI-powered OTL anomaly detection now, public sector agencies can leapfrog traditional limitations and position themselves as leaders in operational efficiency.

For local government, this means fewer payroll disputes and better use of taxpayer funds. In higher education, it enables more transparent and accurate time allocation for academic workloads. For healthcare, it reduces compliance risks and ensures staff are paid accurately for their often complex shifts.

What sets Firstcron apart is deep expertise in Oracle ERP Cloud implementations for public sector organisations. The GenAI-powered OTL anomaly detection solution isn’t just a tech add-on — it’s embedded into the client’s operational context.

From initial configuration to AI model training, Firstcron ensures that the system reflects the unique policies, contracts, and compliance needs of each client. This tailored approach maximises ROI and ensures a smooth transition.

Timecard review doesn’t have to be the slow, error-prone process it has always been. By combining Oracle ERP’s powerful OTL module with Firstcron’s GenAI-powered anomaly detection, public sector organisations can move from reactive correction to proactive prevention.

The benefits are clear: faster reviews, greater accuracy, reduced compliance risks, and better use of staff time. For the UK and US public sectors — where every pound or dollar counts and public trust is essential — this is more than an efficiency upgrade; it’s a step toward modern, intelligent workforce management.nnTo explore how Firstcron can transform your timecard review process, visit Firstcron.