Unleash the power of compliance analytics with GenAI

In today's rapidly evolving digital landscape, organizations are harnessing the potential of data analytics and AI techniques to thrive amidst complexity. These capabilities have proven especially useful in third-party health checks to assess the risks and compliance of external partners and retrospective data analysis to review historical data. Here, learn more about the ins and outs of third-party health checks and how advanced technology is revolutionizing the field. 

Understanding third-party health checks  

Third-party health assessments are crucial for businesses to understand both operations and market dynamics, yet they've grown increasingly difficult to conduct. The process is time-consuming, requiring thorough internal and external data compilation, data accuracy and quality challenges, and legal and regulatory complexities. But the results can help with various essential business needs: identifying and addressing risk, enabling compliance, improving operations and maintaining secure interactions with external business partners. 

Retrospective analyses, which typically assess two-to five-year periods, can be an especially valuable component of third-party health checks. They allow you to identify long-term trends, patterns and anomalies that may not be visible in shorter time frames.  

As an example, let's look at a hypothetical manufacturing company, ABC Co., and how it might benefit from a retrospective analysis: After conducting a five-year performance analysis, ABC Co. discovered a recurring pattern of suspicious transactions and irregularities in supplier and vendor dealings, suggesting potential fraud and corruption.

This prompted ABC Co. to strengthen its internal controls, enhance vendor vetting procedures, revise contracts to include anti-fraud clauses, implement rigorous monitoring systems and, ultimately, transition to new business partners. As a result, the manufacturing company mitigated the risk of fraud and corruption, safeguarded its financial integrity, and fostered a more transparent and accountable operational environment, thanks to a retrospective analysis.  

And yet, retrospective analyses aren't as widely practiced as general third-party health checks. The reasons why are understandable: All the challenges of conducting third-party health checks are multiplied with retrospective analyses, which spans more time and requires more data.

Risk and compliance data sources in analytics

Make no mistake, the amount of data needed for third-party health checks is often vast. Effective risk and compliance analytics require many data types and sources to build a proper foundation. Data useful for health checks include: 

• Financial data, such as invoices, receipts, purchase orders, and payment records or bank statements related to third-party transactions to identify any unusual or suspicious financial activities 

• Contracts and agreements with third parties, including terms, conditions and clauses related to fraud and corruption prevention, along with contract amendments or modifications to indicate potential risks or changes in business arrangements. 

• Compliance data, such as records of third-party due diligence, certifications, audits or assessments related to anti-fraud and anti-corruption measures. 

• Employee records associated with third-party interactions, including roles, responsibilities and access privileges. 

• Publicly available information, such as media reports or subscription-based intelligence sources for insights into the reputation and ethical conduct of third parties. 

• Internal audit reports, monitoring logs or exception reports that highlight unusual activities or breaches related to third-party interactions.   

Essentially, the more data variety you have, the more information you have, providing you with a more holistic picture and actionable insights.  

Traditional approaches to compliance and risk analysis 

In the past, compliance and risk analysis was very manual. This made data review, often managed with spreadsheets, time-consuming and prone to human error. The process lacked scalability, and analytical insights now can be easily supplied by algorithms. In addition, siloed systems and data sources resulted in a fragmented understanding of the issues and less cross-functional risk identification. The result was limited real-time visibility, which led to a reactive approach to compliance monitoring rather than proactively detecting and addressing emerging risks. 

Certainly, as technology has improved, many organizations have turned to software to improve risk analysis. Yet, some have done so in a piecemeal or haphazard manner, automating aspects of the process, while maintaining historical approaches for others. The results are hardly seamless.  

A more modern approach to compliance and risk analysis 

To overcome such limitations, organizations are increasingly seeking more streamlined, effective solutions. Risk Detect, a PwC Product, offers advanced analytics and automation to help enhance compliance and risk analysis. It can help organizations overcome inefficient manual processes, gain a holistic view of risks and proactively identify compliance issues. 

Some key components of the web-based Risk Detect include:  

Key Risk Indicators (KRIs): KRIs serve as early warning signs of potential issues or risks within an organization, allowing organizations to proactively monitor their performance and identify areas that require attention.  

Data visualization: These techniques can present complex information in a visually appealing and easily understandable format to identify patterns, trends and anomalies that may not be apparent through traditional analysis methods. They’re especially useful to effectively communicate findings to stakeholders.  

Generative AI (GenAI): Many consider GenAI, which includes machine learning and natural language processing, a game-changing technology for risk analysis. It can more accurately and efficiently analyze large volumes of both structured and unstructured data, such as unformatted notes, to help uncover hidden insights, detect complex relationships and forecast future outcomes. 

Risk Detect can help empower organizations to improve decision-making and stay ahead of evolving risks, ultimately leading to more effective risk mitigation and compliance management. 

Benefits of investing in compliance analytics for ongoing monitoring 

Investing in advanced compliance analytics tools and techniques is practically essential to remain competitive in today’s market. Spotting and addressing legal and compliance risks early helps give organizations an edge that can protect their interests in the short and long term. Additionally, ongoing data analysis enables organizations to stay on top of evolving compliance and fraud regulations, adapt their strategies accordingly, and maintain a secure and trustworthy environment for their stakeholders. 

However, to leverage the advantages of advanced analytics, it is essential to maintain a flexible and adaptive approach. Compliance teams often start with large monitoring projects that have broad scopes but eventually find their desired value in specific areas. Luckily, thorough third-party assessments can be just as adept at handling focused efforts requiring detailed insights into financial transactions, supply chain data and business processes to help you drill down to the information you need.  

Regardless of what form your risk program takes, Risk Detect can provide the advanced analytics and automation needed to help you now and in the future. If you want to improve decision-making and proactively manage risk and compliance, then contact us to see how advanced compliance analytics can help your organization achieve. 

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Risk Detect: This digital platform helps identify and flag high risk activity with our digital risk detection and monitoring solution. Utilize advanced analytic algorithms and machine learning to get to key data points quickly and efficiently.