AI-powered risk management: The future of internal audit
Risk. It's a word that permeates every aspect of an organization’s GRC practices. It's the language that unites internal auditors, compliance officers and business leaders in a common pursuit: safeguarding the organization.
But how we assess and manage risk is rapidly evolving, and artificial intelligence (AI) is emerging as a powerful tool, enabling a more efficient and insightful approach to risk assessment in internal audits.
At the recent Great Audit Minds Conference, hosted by the Institute of Internal Auditors, Kunal Agrawal, Director, Customer Success at Diligent, led an insightful session titled “AI-Powered Insights: Revolutionizing Risk Assessments in Internal Audits” that explored how AI is reshaping risk assessment methodologies. Let’s dive into the key takeaways.
Risk: A universal language, translated by AI
Risk transcends industries, sectors and organizational boundaries. It’s the common thread that weaves through financial institutions, healthcare providers, manufacturing companies and government agencies alike.
But how do we effectively communicate and manage risk across diverse contexts? Enter AI—the universal translator for risk management. By harnessing the power of AI tools, organizations can bridge gaps, break down silos and foster a shared understanding of risk.
As Agrawal said, "Risk is a common language across GRC, and AI is the translator.”
Traditional vs. intelligent risk assessment
Here are just a few of the ways that AI-powered risk assessments differ from traditional assessments.
Enhancing efficiency across the organization
Traditional risk assessments often involve manual processes, spreadsheets and subjective judgment.
These methods, while valuable, can be time-consuming and prone to bias. Intelligent risk assessment, powered by AI, streamlines the process — automating data collection, analysis and reporting to free up auditors’ time for more strategic decision-making.
Promoting coordination across risk functions
Silos hinder effective risk management. AI breaks down these barriers by integrating risk data from various functions—finance, compliance, operations and IT.
This allows for a more holistic view of risk, which promotes better coordination and alignment of risk mitigation efforts.
Consistent risk language
Imagine a scenario where every department speaks a different risk language. Chaos ensues. AI standardizes risk terminology, ensuring that everyone — from the boardroom to the frontlines — speaks the same risk dialect.
This consistency in language fosters clarity, alignment and informed decision-making.
Applying AI in risk assessments
AI can be used to improve risk assessments in a variety of ways:
Risk surveys: Beyond checkbox responses
Traditional risk surveys collect checkbox responses. AI-enhanced surveys go beyond a checkbox approach. They:
- Augment surveys with workflow automation: Real-time reporting becomes seamless as AI automates survey workflows.
- Provide text analysis: AI analyzes open-ended survey responses, extracting valuable insights from unstructured data.
- Identify custom risk factors: Based on survey responses, AI identifies custom risk factors unique to each organization.
- Trigger instant visuals: Predefined thresholds and weights trigger instant visualizations, making risk trends visible at a glance.
AI-powered interviews: Unleashing unstructured data
AI can standardize interview processes to consistently capture unstructured data, while natural language processing (NLP) makes it easy to sift through interview transcripts and uncover hidden patterns and trends.
And because AI can group and summarize frequently used words and phrases, critical insights and trends can quickly be surfaced for more informed decision-making.
“AI-powered Interviews will help dramatically reduce the time needed to gather information from executives,” explained Agrawal. “This helps standardize the process to capture unstructured data that previously took days to review and normalize, while also removing any bias.”
Automatic risk detection: The AI sentry
AI can automate the identification and categorization of risks by analyzing vast datasets from various sources, including financial records, operational data, transactional information, and even unstructured data from interviews and open-ended survey responses.
With the automatic identification and categorization of those risks, auditors can focus more on high-priority areas.
Data analysis and pattern recognition
One of the most powerful capabilities of AI lies in its ability to analyze massive amounts of data. This allows internal auditors to:
- Identify emerging threats: AI can analyze data to uncover patterns, anomalies and trends that may indicate potential risks.
- Perform predictive risk assessments: Machine learning models can learn from historical data to predict future risks and flag areas that require further investigation. This is particularly valuable for analyzing highly repetitive and frequent transactions or events.
Scenario analysis: Bridging the gap between data and reality
AI tools can rapidly analyze data from across the organization, synthesizing information from sales, operations, finance, HR and other departments.
This allows for the creation of realistic scenarios that reflect the actual workings of the business.
Communication and collaboration: The power of AI-driven insights
Effective risk communication is just as important as risk identification. AI can play a crucial role in:
- Enhancing communication impact: NLP techniques can help choose the right words to increase the impact of risk communication, ensuring clarity and communicating urgency.
- Mitigating language barriers: AI can help translate communication across different functions and languages, fostering consistent messaging across the organization.
- Facilitating continuous risk management: AI supports the philosophy of continuous risk management by enabling real-time risk identification and analysis.
AI also has the potential to democratize data and analytics within organizations. This means:
- Increased accessibility: Empowering everyone to query data using everyday language, fostering a data-driven culture.
- Self-service insights: AI-powered analytics can provide individuals with the tools they need to conduct their own risk assessments, fostering ownership and accountability.
- Enhanced collaboration: By streamlining the sharing of data and insights across departments and teams, AI can enhance collaboration and break down silos within GRC functions.
Risk managers driving change as AI champions
AI empowers internal auditors to become champions of change within their organizations, freeing up valuable time previously spent on tedious data collection and analysis. This newfound efficiency allows auditors to shift their focus towards strategic initiatives, such as proactive risk mitigation strategies and in-depth assessments of high-impact risks.
“As an independent function within the organization, internal auditors are positioned to provide direction on AI adoption,” said Agrawal.
Ultimately, AI equips internal auditors with data-driven insights and predictive capabilities. This empowers them to make more informed and effective risk-based decisions, safeguarding the organization's future and contributing to its long-term success.
Ready to become a champion for change within your own internal audit team? Learn how the Diligent One Platform can help you elevate your internal audit practices with AI-powered risk data and analytics.
