When a U.S. federal government agency needed to bring consistency, speed and defensibility to oversight work spanning financial statement audits, program audits, investigations and day-to-day operations, it turned to Diligent's ACL Analytics, ACL Robots and ACL’s R/Python integrations as a central platform for data integration, automation, sampling and advanced analysis.
The agency operates across multiple legacy systems, a departmental data lake, and external data sources, an environment that makes consistent, repeatable analysis difficult without the right tooling. By building automated, parameter-driven tools on top of ACL, they have:
Here's a look at four ways they put that platform to work.
The challenge: Every year, the agency must confirm unpaid principal balances across a loan portfolio surpassing $100 billion, spanning multiple programs and ranging into hundreds of thousands to millions of individual loans. Previously, staff manually pulled samples from legacy systems, compiled them into a single file, and then verified both the sample and the underlying data's reliability. That process took up to three weeks and involved multiple handoffs and timing risks.
The solution: Using ACL, an end-to-end automated task was built that ingests and standardizes roughly 20 separate program files into a single harmonized universe. The task parameterizes sampling, including confidence levels and optional seeds for reproducible samples, and runs monetary unit sampling across the consolidated data.
The result: The process now runs in roughly three to five minutes on a single ACL node, producing a clean, fully documented sample for audit and contractor teams, with methodological details captured automatically in logs and scripts. What used to take three weeks and multiple handoffs now finishes the same day and stays fully defensible.
The challenge: Modernizing sampling was only useful to a small technical team unless the agency could extend that same rigor to front-line auditors and investigators who don't write code.
The solution: Parameter-driven toolkits were built that let non-technical staff run sophisticated tests without writing code. These toolkits automatically:
Analysts simply drag and drop input files or key in subject identifiers, specify field names and desired outputs, and receive results by email with full parameter documentation for traceability.
The result: Consistent, sophisticated checks are now available to any analyst, not just specialists. This reduces variability and training needs, frees analytics staff to focus on higher-value work, improves documentation, and lowers manual error risk.
The challenge: Tracking and reporting costs for major conferences and training events involved manual comparison of travel options and reformatting data into required federal reporting formats, time-consuming work that had to be repeated for every event.
The solution: A reusable travel optimization tool was built using ACL. Users provide a simple input CSV with attendee names, dates, departure ZIP codes and preferred airports, along with policy parameters such as maximum driving distance and one-way travel thresholds. ACL then combines public and policy data, including per diem and lodging rates, airfare estimates, and mileage and driving costs, to estimate total travel cost for candidate host cities.
The result: The tool generates a ranked list of host cities from least to most expensive, plus detailed attendee-level breakdowns. Outputs are formatted to mirror required federal Standard Forms, which significantly reduces rework for event planning teams.
The challenge: To perform operational analyses, target mission work and monitor emerging risks, the agency often needs to combine human resources and budget data with program data. These data sets are typically fragmented across departmental sources and legacy systems with complex access and format constraints.
The solution: Using ACL, direct connections directly to departmental sources were built to pull operational and program data into controlled environments to perform the transformations, filters and joins needed to make the data analytics-ready.
The result: Staff can now support both ad hoc and recurring analyses while reducing dependency on external teams for data preparation, giving program and operations leaders faster access to the insights they need.
Across audits, investigations and internal operations, the common thread is the same: Diligent ACL is the one platform that both technical staff and front-line personnel can use, with consistency and documentation built in by default.
It's a pattern that holds across large, complex organizations more broadly: full-population analysis instead of sampling, fewer disconnected tools and manual handoffs, and analytics that extend beyond a small technical team, all connected through the wider Diligent One Platform's data integrations and reporting.
Interested in what a similarly automated, parameter-driven approach could do for your agency's audit, compliance or operational workflows?
Request a demo to see ACL Analytics in action.
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