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Even with so many data sources on the market today, credit managers still struggle to find complete, relevant data.
Much of the data available is either outdated or missing key pieces that credit
managers need in order to make effective decisions.
Incomplete or Irrelevant Data
Top 3 Challenges Credit Managers Face and How to Fix Them.
Solution
Static data like demographics and SIC codes are a thing of the past. For information to work in today's market, it needs to be actionable and it needs to be predictive. Purchase behavior data has proven to be both.
Spend data tells a company nearly everything it needs to know about the businesses it works with. An increase in purchases signals that a company is growing, thus a strong candidate to receive trade credit. A decrease in spend signals the opposite; the company is struggling or downsizing, and therefore is not a good candidate to receive trade credit.
While payment data will always have its place within the B2B marketplace, it must be combined with spend data in order to be effective. This new way of thinking gives credit managers a stronger foundation on which to base the tough decisions they must make.
Invest in Actionable, Predictive Data
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Credit managers are given a high volume of work to complete with limited resources. With the expectation of doing more with less, credit managers are in need of more automation and less manual processing.
Unfortunately budgets for credit departments tend to see little to no increase year after year. In many cases, they're actually the first to get cut, making it tough for credit managers
to access additional resources.
High Work Volume vs. Budget Constraints
Solution
Unlimited plans are great - unlimited data, unlimited gym access, unlimited ice cream - you name it, and it sounds like a great deal, right? Wrong. When it comes to B2B credit, there is such thing as too much. What "unlimited" really means is that your provider has chosen some number that is so far ahead of what you're actually using, it gives off the illusion of being an endless supply. For example, company A pulled 165 business credit reports last year. This year, company A's provider bills them for 1,650 worth of reports. Now, they have an "unlimited" plan.
You also may find that you don't need all of the same products and services that other businesses in your industry do. For example, you may not need a credit and collections module or automated scoring. That's totally fine - just be sure that those products aren't worked into or "included" in your contract. In the B2B credit world, nothing is ever free. Keep this in mind when building your custom solution.
Once you have the right data in place, you can fuel the right systems. The best way to overcome the challenge of a heavy workload is automation. The most successful credit managers automate their A/R monitoring, decision scoring, and portfolio analysis with multiple solutions combined into one.
Implementing an A/R monitoring system will improve the frequency of delivery of updated data, keeping you aware of key account changes and ahead of your entire portfolio. By receiving daily alerts, notifying you of these key changes, you can act upon any signals of risk before it is too late. Automating workflow processes ensures connectivity to any information source, enabling fully customizable scoring. Automation and alerts help to proactively increase efficiency for virtually any business to take advantage of.
Cutbacks & Automation
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Sales departments are known to have a need for speed. They want their requests reviewed and approved nearly instantly in order to meet monthly quotas, putting pressure on the credit departments to get more done in less time.
Pressure from Sales Teams
Once a credit request is approved, you need to determine its limits. High work volumes can make this process extremely tedious and time consuming. By creating algorithms that will set the rules for credit decisions, you can streamline the entire process, thus minimizing risk and increasing decision hit rates. You'll have yes-or-no decisions in minutes, along with a range of recommended credit limits to choose from.
Solution: Set Rules for Decisions Through Algorithms
Increase revenue and minimize risk by addressing these common challenges head-on.
Spending trends predicted bankruptcy before traditional credit analysis.
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