How will Technology Impact the FMCG Sector in 2024?
19-Sep-24
Dun & Bradstreet, the leading global provider of B2B data, insights and AI-driven platforms, helps organizations around the world grow and thrive. Dun & Bradstreet’s Data Cloud, which comprises of 455M+ records, fuels solutions and delivers insights that empower customers to grow revenue, increase margins, build stronger relationships, and help stay compliant – even in changing times.
A glance at our wristwatch doesn’t really reveal the intricate and efficient working of the big and small gears inside it. Similarly, the product you hold in your hands doesn’t show the elaborate and complex process it has been through to reach you. This process involves a network of supply chains, each step bearing its own set of risks and challenges. Central to navigating these challenges is understanding what is credit risk assessment—something that becomes increasingly vital during supply chain disruptions.
In this analysis, we meticulously examine the critical role of credit risk assessment in mitigating risks within supply chain operations, highlighting its profound impact in the complex landscape of today’s interconnected global business environment.
Credit risk assessment is a strategic tool, essential for investors, banks, or money lenders. It involves a rigorous evaluation of the potential risks before allocating funds to either individuals or businesses. This process is akin to a comprehensive risk audit, crucial for financial decision-making and ensuring the stability and reliability of investment ventures.
Earlier, credits would be given to known people or through credible references. Over time, credit seekers increased, and financial institutions and investors faced challenges with paybacks and recovering money. Thus, the process of assessing credit risk before lending and investing existed.
There is also the ease with which investment applications can be made. In fact, there was a time when financial institutions and investors would encourage businesses to opt for lending. One reason was that they, too, would benefit from this process by charging interest.
Now, manually evaluating all these applications is time-consuming and prone to human error. Thus, manual background checks were replaced with digital credit risk assessment. Through the strategic application of automation, investors have effectively streamlined their operations, achieving cost efficiency and enhanced precision in credit risk assessment.
This approach integrates cutting-edge technology to dissect and scrutinize the creditworthiness of businesses and individuals, employing a diverse array of data sources and advanced analytics tools. This method provides a thorough and multi-dimensional view of an applicant’s financial standing, essential for informed decision-making in today’s fast-paced business environment.
Technology also offers exhaustive checks across all financial portals that an applicant may have accounts in or have a repayment overdue, defaults or any other negative remark.
While technology is a cornerstone in the credit risk assessment process, the value of human expertise cannot be denied. Professionals with years of industry experience bring critical judgment and strategic thinking to the table. Their insights, when integrated with technological data, result in a well-rounded and comprehensive risk assessment. This human touch is especially vital when assessing the implications of supply chain disruptions, where context and industry knowledge can significantly influence risk assessment outcomes.
The supply chain process has several significant steps. Each of these has a certain financial risk. A disruption in the supply chain can cause a significant breakdown in business outcomes, customer satisfaction and, therefore, lesser profits. Lesser profits may lead to delayed repayments to lenders.
Fortunately, credit risk assessment has undergone a remarkable evolution in the digital age. The use of advanced technology, such as big data and machine learning algorithms, has made credit risk assessment more efficient.
Supply chain data analytics algorithms can process vast amounts of data, especially in real time. This digitization has allowed for achieving predictions and assessments that are accurate in nature. With the help of these algorithms, investors can identify and mitigate risk while making informed decisions.
A shift towards automated credit risk assessment processes has also been witnessed. Every time a business requests funds, all their demographic details, financial health and stability and credit scores are cross-checked across time as well as other portals.
Automation of data analytics services has revolutionized how investors evaluate potential borrowers. They can make more informed decisions while improving efficiency and reducing risks associated with lending.
Any deviations or discrepancies will be highlighted, and the lender will be alerted to take necessary action.
In conclusion, credit risk assessment in the context of supply chain disruptions requires a delicate balance between advanced technology and human expertise. While digital tools provide comprehensive data analysis, human judgment is crucial in interpreting this information, especially in the complex scenarios presented by supply chain issues. Understanding this interplay is essential for businesses and financial institutions aiming to navigate the challenges of the modern economic landscape.
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