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6 Ways To Boost Credit Health in Mid-sized Businesses

What you’ll learn


  • Streamlined Data Aggregation for Credit Reviews
  • Frequent Credit Checks and Blocked Order Resolution
  • Customize and Digitize Credit Processes

’Buy now, pay later’ has now become the way of life for most businesses. The lion’s share of small and mid-sized businesses buy tools and resources on credit. A credit rating defines the amount you are qualified to receive as a loan and the rate of interest on it. Higher the credit rating, the larger the loan amount you are qualified for. With a volatile economy, a lot of businesses faced trouble paying back outstanding invoices and their loan amounts. This was caused because businesses keep providing credit without a full assessment of the past credit history of customers leading to the rise in bad-debts. So, what strategies can businesses follow to ensure that their essential credit turns into cash?

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2020 saw the rise of digitalization of the financial sector. Adaptive solutions came into the picture that could help eliminate manual and time-consuming AR processes to drive focus towards more strategic tasks. Receivable automation also saw a rise as it helped organizations reduce costs, time, and improved credit decision-making. Let’s see where automation fits into the picture. Learn about the major roadblocks in credit management, how automation helped optimize those processes, and the best practices to uplift your credit health.

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Major Setbacks for Credit Management

Credit teams around the world faced a newer set of issues post-covid with a large number of customer accounts to handle with limited resources available. But before the finance industry had a digital makeover, there were issues faced by credit teams that still have a bottom-line impact on DSO and bad debt. These issues can be tackled well with automation that optimizes AR processes to minimize bad-debt.

Focusing on the issues, here are a few processes that can be optimized to improve the overall credit health:

  • Traditional customer onboarding: Customer onboarding is one of the most important tasks performed by finance teams that has a direct impact on the Days Sales Outstanding (DSO). Part of it contains collecting credit applications, gathering data from 3rd party credit agencies, and analyzing the data.

    Challenge: These traditional tasks are paper-heavy. Credit teams still spend most of their time faxing, filing, emailing, following-up, aggregating as well as analyzing the data. This makes it more prone to errors, inaccuracy, and lack of validation in the data.

    Impact: Manual, paper-based processes are time-consuming when we talk about onboarding new customers. Inaccurate and unvalidated data impacts the customer experience. Further, there is a rise in bad-debt due to the lack of visibility into customer’s credit data.

  • Manual paper-based documentation: Manual and paper-heavy documentation are still evident around some small and mid-sized businesses. Most companies manually gather data to review the creditworthiness of the customer.

    Challenge: As per Cisco’s Digital Maturity survey, a majority of operational and financial tasks in SMBs were manual in 2020. There lies a high risk of data frauds and thefts. These manual processes act as bottlenecks for A/R tasks. Searching, reviewing, and editing data gets tougher with a manual set-up at-hand. As per Investopedia, a major chunk of credit analyst’s time is spent on data gathering and analyzing it.

    Impact: With human error, blocked orders are still prone in many SMBs. Resolving blocked orders is a tedious job for the analysts. This will again cause a lousy customer experience and will delay sales for your firm affecting your DSO.

  • Absence of credit risk monitoring- Lack of credit risk monitoring can hamper businesses in having a real-time view of customer credit profiles. It is done to monitor any fluctuations in your customer’s credit health and how you can take effective measures.

    Challenge: As per CreditBenchmark, global corporate credit risk climbed by 20% in 2020. Frequent credit reviews are not cost-effective in the current economy. Credit reviews contain data aggregation from multiple sources that add to the overhead cost. This task takes up a lot of time for credit analysts.

    Impact: Increased overhead costs hamper the working capital. Data aggregation is necessary but analyzing a large amount of data is tough for a small credit team which affects customer satisfaction and aids in bad-debt as well.

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Strengthening AR with Automation

Tasks performed by credit teams can take time and are crucial in laying a sturdy foundation for your customers. Automating AR can help with credit management & skyrocket your firm’s sales. Proactive credit processes can lead to reduced bad-debts, lowered DSO, and much-improved customer onboarding.

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A lot of time and effort goes into the credit team’s day-to-day work. Here are the 6 best practices that finance teams can start adopting right away for better credit management:

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Conclusion

  • Streamlined Data Aggregation for Credit Reviews
    1. Focus on conducting periodic credit reviews for high-risk customers
    2. Gather credit data from external data providers to gain efficiency and save time
  • Frequent Credit Checks and Blocked Order Resolution
    1. Have frequent creditworthiness checks to reduce the risk of bad-debt
    2. Have a one-stop-shop information repository to resolve blocked orders faster
  • Customize and Digitize Credit Processes
    1. Onboard new customers easily through a digital credit application with valid and accurate data capture to save time
    2. Customize credit scoring of customer accounts to come up with tailor-made credit limits

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