Big 4 audit network

For an audit firm, knowing what happens at the companies it audits is part of the job. A sanctions designation, an enforcement action or a fraud allegation at a client can affect client acceptance, the audit approach and the firm’s independence assessment. For a global network that audits thousands of companies, keeping that picture current is a structural challenge.

This case study describes how the global audit and assurance risk function of one of the Big 4 networks has worked with Business Radar since 2022: from a jointly designed monitoring platform for risk sensing teams in its member firms, to a daily data feed into its own systems.

Le défi du client

Audit teams in a Big 4 network work for clients in dozens of countries. Information about those clients appears in local media, in many languages, and often under the name of a subsidiary rather than the listed parent. Manual searches and periodic checks miss part of it, and they do not scale across a network of member firms that each serve their own clients.

The network also has a specific structure. Each member firm is a separate legal entity, while risk policies and tooling are coordinated globally. A solution has to work for a central risk team and for local risk sensing teams in very different markets at the same time.

Le contexte du secteur

Regulators and audit oversight bodies expect firms to know their clients, not only at acceptance but throughout the engagement. At the same time, the volume of relevant information keeps growing, and much of it never reaches the financial statements. Audit firms are therefore moving from periodic background checks towards continuous monitoring of the companies they audit.

The solution: one monitoring environment for the whole network

In 2022, the network’s global audit and assurance function selected Business Radar to support risk sensing in its member firms. Business Radar set up a dedicated environment with single sign-on, pre-loaded with all public interest entities audited across the network, plus companies going through the client acceptance process. Member firms can add other entities they want to follow.

News is matched to the right entity and linked through the corporate group structure, so an article about a subsidiary reaches the team that audits the parent. Risk sensing teams in Europe, Asia, Africa and North America use the platform for adverse media monitoring and for compliance checks against sanctions lists and enforcement actions. Some teams rely mainly on the news monitoring, others mainly on the compliance checks, which give them access to sanctions and enforcement data they do not have elsewhere.

Designed together with the users

From the start, the platform was developed together with the people who use it. In design workshops with the network’s risk sensing specialists, the two teams went through the dashboard, company pages and analytics screen by screen and agreed what auditors need to see first. Feedback from member firms was collected in a shared list with priorities and reviewed in regular sessions. Close to a hundred points were logged this way, and most of them have been implemented.

Several features came out of that work. Subsidiaries are included automatically when a group is added. Binders let users collect articles and notes on a client and share them with colleagues on the same engagement. Compliance matches can be marked as positive, false positive or no risk, with a note for the file. Companies that are not yet in the database are investigated automatically through Dun & Bradstreet. The interface is available in several languages for member firms outside the English-speaking world, and the network’s ideas for event timelines, which group all coverage of one developing story, are feeding the next steps on the roadmap.

Measured in a shared feedback loop

To see whether the data was good enough for their research, the network’s research teams recorded for every client they worked on whether Business Radar contained everything they needed, and if not, what was missing. The results were tracked per month against agreed targets. Between July 2023 and April 2024, coverage improved in every area:

Each missed item went back into the product: sources were added or excluded, classifiers were retrained, and missing group structures were corrected with Dun & Bradstreet.

From platform to data feed

Over time, the way the network uses Business Radar has shifted. Part of the data now flows directly into the firm’s own AI-driven audit platform. Every day, the network downloads Business Radar’s news data in bulk through the API, including article summaries, and processes it in its own systems. In a test of its own risk classification, grounding the classification in related Business Radar articles made it 25% more accurate.

This reflects a broader shift: large organisations increasingly want the data in their own systems rather than in one more platform, with a single source of truth for every team that needs it.

Mise en œuvre et collaboration

Working with a Big 4 network brings requirements that go beyond the product. Auditor independence rules mean the firm reviews every service provider, including the AI models used behind the service. Business Radar documents which models are used for which part of the service, so the firm can complete that review.

The licence structure was aligned with the network’s structure, so member firms can use the data under one global agreement. Business Radar’s developers have worked directly with the firm’s technology teams to make the data easy to ingest, and sessions with end users in different countries continue to feed into the product roadmap.

Un enjeu plus large

For audit firms, adverse media monitoring is becoming an ongoing input for risk decisions on audit clients rather than a one-off check. That raises the bar for the data itself: correct entity matching, complete group structures, clear sourcing and documented use of AI. Those are the same requirements Business Radar sees at banks and insurers, and they increasingly decide whether external data can be used in internal systems at all.