Commercial credit decisions have long been driven by data. But thanks to exciting new technologies, a whole world of greater insight is opening up to commercial lenders and helping inform their every next move.
It’s about time. Traditionally, credit analysis has been all about the customer’s history – looking backward to observe how a business, its collateral and its industry have been performing to date.
Over the past decade, however, the analytics have evolved. Rather than simply describing what has gone before, commercial lenders have started to look forward and use both current and historical data to predict what may happen in the future.
In the uncertainty of the pandemic, the resulting intelligence has proved invaluable. But as approaches to managing commercial credit data continue to mature, the insights haven't stopped there.
Once purely descriptive, then increasingly predictive, now credit analytics are going prescriptive. In other words, today’s commercial lending organizations can use data to not only foretell what might come to pass but also propose the next best action for each customer.
That’s the theory. But in practice, the data that feeds commercial credit analytics comes from a wide variety of internal and external sources, making it difficult to distill into a coherent view of customer and industry performance.
The good news is that advancements in technology are coming to the rescue. And at FIS®, we see our clients digitally transforming the management and analysis of commercial credit data in three key ways.
First, firms are taking a more proactive approach to their data and looking to drive intelligent decisions based on holistic data insights.
Fundamentally, that means being able to gather and synthesize information on customers from across the entire lending life cycle and incorporate both historic financial reports and high-frequency account data. But more and more, digital analytics are also combining this traditional, structured form of financial data with unstructured data, such as from credit memos, news feeds and sentiment analysis.
Second, the most progressive lenders are using technologies like robotic process automation, artificial intelligence and machine learning to not only collect these insights but also generate the prescriptive analytics and recommend the best follow-up action. With sophisticated workflow tools orchestrating their processes, lenders can automatically trigger the most appropriate and (artificially) intelligent responses to different credit scenarios, too.
Finally, with higher levels of automation and a ready supply of deeper, broader insight comes greater control over the commercial lending life cycle. The holy grail should be a fully automated, real-time framework for credit management that significantly reduces decision times, manual effort and, above all, risk with a complete, up-to-the-minute view of the customer, their industry and their relationship with your organization.
The time is right to get more insight from commercial credit data – and the smart digital technology is there to make it happen. Why wait to take the next best action for your lending business?