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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?


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.


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.


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.


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:



  • 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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