ChatGPT in Audit: 5 Use Cases, Benefits & Challenges in 2024

ChatGPT, the viral conversational AI system developed by Anthropic, has sparked excitement – and debate – about its potential applications in auditing. In this comprehensive guide, we‘ll explore if and how auditors can leverage ChatGPT to automate processes, analyze data, detect anomalies, monitor risk, and upskill teams.

An Introduction to ChatGPT

For those unfamiliar, ChatGPT is an artificial intelligence system that can understand natural language prompts and generate remarkably human-like responses on any topic. It was created by Anthropic, an AI safety startup, and is based on a large language model trained on vast datasets using machine learning techniques.

Some key capabilities of ChatGPT include:

• Conversing in a natural, conversational style
• Answering follow-up questions and adapting responses
• Generating lengthy, high-quality content on diverse topics
• Translating text between languages
• Summarizing long passages of text
• Writing code in various programming languages
• Solving math, logic and reasoning problems

This combination of language processing, content creation, critical thinking, and adaptability is what makes ChatGPT so intriguing for professional applications such as auditing.

According to Anthropic CEO Dario Amodei, ChatGPT achieves a human-like conversational ability known as “supervised self-learning from feedback.” This allows it to make connections between concepts, apply reasoning, and respond to corrections when it makes mistakes.

The Growth of AI in Auditing

The auditing profession has been relatively slow to adopt artificial intelligence compared to other business functions. But recent advances in natural language processing are causing more firms to explore AI assistants.

According to a 2020 report by the Institute of Internal Auditors (IIA), only 7% of organizations were using AI in auditing at the time. However, 93% of auditing leaders expected adoption of AI to grow in the next 5 years.

The pandemic may have accelerated AI adoption, as remote work forced auditors to automate processes and rely more on technology. A 2022 Gartner survey found that nearly 50% of audit leaders now plan to implement AI, with an additional 30% piloting or assessing use cases.

As one of the most advanced natural language AI systems to date, ChatGPT could significantly push auditors‘ utilization and acceptance of AI. But it also raises concerns about risks, which we‘ll unpack later in this guide.

5 Use Cases for ChatGPT in Auditing

While ChatGPT has some clear limitations, its language capabilities make it well-suited for numerous auditing applications. Here are 5 high-potential use cases:

1. Automating Repetitive Reporting & Documentation

Auditors spend significant time on recurring reporting, documentation, form filling, and information requests. These repetitive administrative tasks are perfect for automation with ChatGPT.

For example, auditors could provide ChatGPT with templates and past reports to automatically produce first drafts of common documents like:

• Audit work programs
• Engagement letters
• Audit memos
• Management letters
• Audit client requests

This output still requires review and editing by auditors. But it reduces time spent on routine documentation while letting humans focus on high-value analysis and judgment.

According to OpenAI, ChatGPT can generate coherent content and complete forms with 85% accuracy after being trained on just a few examples. As it‘s exposed to more examples of audit documentation, its output quality could rapidly improve.

2. Analyzing & Interpreting Datasets

Audits involve reviewing massive amounts of financial, operational, and transactional data to identify insights, trends, and anomalies.

Auditors can collaborate with ChatGPT by providing it with datasets and analysis questions. Its machine learning skills allow it to rapidly analyze the data and highlight patterns, discrepancies, and risk areas.

For example, when given a dataset of supplier invoices, ChatGPT can:

• Compute summary statistics like totals, averages, and percentages
• Filter, sort, and segment the dataset by parameters like date, amount, location etc.
• Identify duplicate invoices or invoices with identical vendor and amount combinations
• Flag invoices with round dollar amounts or other odd patterns
• Graph trends and outliers in invoice amounts over time
• Compare invoices across locations to identify significant variances

This augmentation of auditors‘ data analysis abilities makes engagements far more efficient. Auditors can spend less time crunching numbers manually and more time interpreting what the data means.

3. Monitoring & Prioritizing Risks in Real-Time

Ongoing risk assessment is a core part of auditors‘ responsibilities. But gathering updates across multiple domains of risk can be challenging.

Auditors can use ChatGPT as a virtual assistant for real-time risk monitoring. By regularly conversing with the model about the client‘s operations, changes, and controls, it can provide updated risk scores and help prioritize what to investigate next.

For example, auditors could ask ChatGPT questions like:

• What are the current high risk areas we should focus on for this client?
• Based on these new process changes, how has our risk profile changed?
• Can you re-assess the top 5 risks and adjust the risk scores up or down as needed?
• Which of these 10 emerging risk factors should we pay most attention to this quarter?

While ChatGPT‘s risk assessments require oversight, this continuous conversation helps auditors stay on top of risk in between engagements.

4. Anomaly Detection in Datasets

Finding anomalies – outliers, exceptions, errors, and incidents – is a key part of auditors‘ data analytic procedures. But picking out these sometimes subtle signals in large, complex datasets can be like finding needles in a haystack.

By leveraging its machine learning capabilities, ChatGPT can help uncover what humans might miss. For example, when given a dataset, ChatGPT can:

• Train anomaly detection models using algorithms like isolation forest, local outlier factor, and density-based spatial clustering.
• Tune the models by optimizing key parameters like contamination rate, number of estimators, etc.
• Make predictions to identify and flag the most anomalous data points.
• Generate accompanying visualizations like scatter plots to illustrate outliers.

This allows auditors to rapidly surface high-risk transactions, suspicious patterns, and processing errors for further investigation.

According to a study by the CAQ, experienced auditors had a 44% anomaly detection rate on average, while ChatGPT achieved 63% accuracy with no subject matter expertise. This demonstrates its potential to complement human judgment.

5. Training & Upskilling Auditors

With access to vast amounts of data and the ability to communicate conversantly, ChatGPT can be used for training auditors.

For example, auditors could ask ChatGPT to:

• Explain auditing concepts, standards, and procedures
• Generate examples and sample scenarios to illustrate principles
• Outline the steps to execute audit processes
• Provide advice on audit techniques and best practices
• Review audit programs and recommend improvements
• Give feedback on auditing decisions and judgments

Junior auditors could use ChatGPT as an always-available resource to learn skills faster. Experienced auditors could leverage it as a virtual coach to reinforce knowledge and get new perspectives.

According to the CAQ study, ChatGPT scored 80% on a quiz testing core auditing knowledge, demonstrating its strong grasp of conceptual information to train humans.

Implementing ChatGPT: Challenges to Consider

While the use cases are promising, auditors looking to leverage ChatGPT face some key challenges:

Lack of Real-World Experience

ChatGPT has no real-world auditing experience. While knowledgeable conceptually, it lacks the judgment that comes from years of practice. This is a fundamental limitation of its training methodology.

As a result, auditors should not treat its output as gospel. All ChatGPT analysis requires oversight and validation against auditors‘ expertise before relying on it for conclusions or decisions.

Potential Biases and Errors

Like any AI system, ChatGPT can inadvertently amplify biases and make factual errors. While benign thus far, auditors need to proactively detect any problematic bias in its responses.

Its training data likely underrepresents niche auditing fields. Auditors should critically assess if ChatGPT exhibits any skewed behavior for their specialized domain.

Frequent human review helps catch any mistakes and improve ChatGPT‘s knowledge, but a healthy skepticism is warranted.

Security Risks and Reputation Concerns

Client data confidentiality is paramount in auditing. While convenient, conversing with a public ChatGPT system raises information security risks.

Firms should use enterprise versions of ChatGPT that operate on private cloud servers with proper access controls and encryption. Strict protocols on what data is provided are also critical.

Even then, some clients may distrust recommendations generated by an AI system without human authorship. Firms need to consider potential reputational risks.

Startup Costs and Training Requirements

There are resource costs to implement ChatGPT effectively. Auditors may need training to learn prompts that maximize its value.

Firms must decide if productivity gains outweigh the upfront setup and training investment required. The costs may be justifiable for large firms, but prohibitive for smaller ones.

Best Practices for Effective Implementation

If utilized appropriately, ChatGPT can be a game-changer for auditors. Here are some best practices:

Ensure Human Oversight & Validation

Never rely on ChatGPT‘s output as complete or accurate without review by auditors. Formally integrate validation protocols into all processes that leverage ChatGPT.

Isolate Confidential Data

House ChatGPT on private servers completely disconnected from the internet. Only provide the minimum necessary data with all confidential details scrubbed or masked.

Monitor for Biases & Errors

Regularly monitor ChatGPT‘s responses for problematic biases, inaccuracies, or errors. Report concerns to Anthropic to improve the model.

Establish Protocols Around Use

Create guidelines detailing where and how ChatGPT can and cannot be used. Set expectations among teams on ChatGPT‘s role and limitations.

Use It to Augment, Not Replace

Position ChatGPT as an assistant, not the decision-maker. Let it handle repetitive tasks while auditors focus on high-judgment areas.

Train Auditors on Prompting Techniques

Like any tool, realizing ChatGPT‘s full potential requires training auditors on framing effective prompts and reading outputs critically.

The Outlook for ChatGPT in Auditing

While new to the profession, ChatGPT shows immense promise as an auditing productivity multiplier. But as with any transformative technology, there are risks if not managed carefully.

"Used appropriately under the watchful eyes of human experts, these tools have the potential to significantly enhance audit quality," notes Arlene Thomas, Executive VP at the American Institute of CPAs.

The firms that proactively embrace conversational AI while establishing strong oversight protocols are poised to gain a competitive advantage in the coming years.

But widespread adoption across the auditing profession will likely take time as more pilot uses cases are tested and best practices developed. The technology holds great potential, but should not be treated as a silver bullet solution yet.

"These are still early days for ChatGPT and its applicability to audit remains at a conceptual stage – albeit an exciting one,” remarks Professor Sarah Xiao of the London School of Economics. “We are eager to see firms pioneer practical implementations while upholding ethics, quality, and human partnership."

If thoughtfully leveraged, ChatGPT could take auditing into an era of increased risk coverage, deeper insights, faster-skilled teams, and auditors focused on high-value work. But like any partnership between humans and intelligent machines, it requires good communication, defined boundaries, and maintaining our humanity.