Unlock Sustainable Growth: Why Your Accounts Receivable KPIs Are the Ultimate Strategic Compass

Cash flow is the undisputed lifeblood of any business, directly influencing its operational capacity, investment potential, and overall resilience. Within this critical financial ecosystem, Accounts Receivable (AR) isn’t just an accounting entry; it’s a strategic asset reflecting your company’s future liquidity and its ability to convert sales into tangible cash.

Yet, businesses frequently grapple with the pervasive challenge of overdue payments. These delays tie up working capital, creating cash flow shortages that hinder daily operations, limit strategic investments, and ultimately stifle growth. This financial friction impacts everything from payroll to product development.

Mastering Accounts Receivable Key Performance Indicators (KPIs) and strategically managing collections are paramount for transforming your company’s financial health. By moving beyond basic definitions and embracing a strategic perspective, businesses can unlock significant value and build a more resilient financial future.

Deconstructing Key Accounts Receivable Performance Indicators

Understanding core AR KPIs is crucial for gaining actionable insights into your financial health.

  • Days Sales Outstanding (DSO): This fundamental metric quantifies the average number of days it takes to collect revenue after a sale. A consistently high DSO signals inefficient collections, potential liquidity issues, and impending cash flow problems. Conversely, a low DSO indicates a highly efficient cash conversion cycle. High DSO can lead to seeking external financing, incurring interest expenses, and limiting investment in growth opportunities. It can also signal underlying issues in credit policy, invoicing accuracy, or customer relationship management.
  • Days Delinquent Outstanding (DDO): DDO offers a more granular perspective by measuring the average number of days accounts receivable are past due. Unlike DSO, DDO focuses specifically on overdue accounts. A rising DDO indicates increasing collection challenges and a heightened risk of bad debt. It functions as an early warning system for broader economic downturns or internal weaknesses in credit vetting. Mishandling delinquent accounts can lead to client relationship damage and lost revenue.

Beyond DSO and DDO, other vital KPIs offer a comprehensive view of AR health:

  • Collection Effectiveness Index (CEI): CEI measures how effective a company is at collecting its receivables over a specific period. A CEI closer to 100% signifies superior collection performance.
  • Accounts Receivable Turnover Ratio: This ratio indicates how many times a company collects its average accounts receivable balance during a given period. A higher turnover ratio generally suggests efficient credit and collection practices.
  • Bad Debt Ratio: This expresses the percentage of uncollectible accounts relative to total receivables or credit sales. A lower ratio indicates effective credit management and successful collection efforts, minimizing direct hits to the bottom line.

These KPIs are deeply interconnected. For example, a high DSO and DDO will predictably correlate with a lower CEI and A/R Turnover, and consequently, a higher Bad Debt Ratio. Analyzing these metrics holistically allows financial decision-makers to identify specific weaknesses and formulate targeted improvement strategies.

The Unseen Costs of Suboptimal Accounts Receivable Management

 

Failing to manage AR effectively extends far beyond mere lost revenue, incurring a range of profound, often unseen, costs.

  • Impact on Liquidity, Working Capital, and Investment Capacity: Unpaid invoices tie up capital, restricting a company’s ability to meet immediate financial obligations. This lack of accessible cash can lead to cash flow shortages, hindering daily operations and limiting investment in strategic growth initiatives.
  • Operational Inefficiencies and Resource Drain: Suboptimal AR management creates significant operational inefficiencies. Companies expend considerable time and effort on internal collections, diverting staff from their primary, value-generating roles. This “invisible tax” on productivity means valuable expertise is directed towards non-core, high-stress activities, hindering strategic objectives and delaying new revenue generation.
  • Erosion of Profitability and Increased Risk of Write-offs: Late payments directly erode a company’s net profit. As debts age, their collectibility diminishes, increasing the likelihood of bad debt write-offs, which are direct hits to the bottom line.
  • Potential Strain on Client Relationships: Aggressive or unprofessional internal collection tactics carry a substantial risk of alienating valuable customers. Losing a client over a collection dispute can be far more costly than the debt itself, leading to customer churn, reputational damage, and a reduction in Customer Lifetime Value (CLTV).

Strategic Pathways to AR Optimization and Enhanced Collections

 

Optimizing Accounts Receivable requires a proactive and multi-faceted approach.

  • Proactive Invoicing, Credit Policies, and Communication: Effective AR management begins with clear, accurate, and timely invoicing. Establishing robust credit vetting processes for new clients can significantly minimize default risk. Consistent and professional communication with customers regarding payment terms and reminders can dramatically improve collection rates.
  • Identifying the Inflection Point for Escalating Collection Efforts: Despite best practices, some accounts will become overdue. The crucial moment when internal efforts become less effective or too costly typically occurs when accounts move beyond 60-90 days past due. At this stage, the likelihood of collecting the debt through internal means decreases significantly, reflecting the “value decay” of the debt.
  • The Strategic Decision: When and Why to Engage External Collections Expertise: Engaging external collections expertise should be viewed as a strategic business decision, not a sign of internal failure. It’s particularly beneficial when facing a high volume of overdue accounts, dealing with complex debts, preserving valuable customer relationships, or when internal resources are stretched thin.

The Strategic Advantage of Partnering with Commercial Collections Experts

 

Partnering with professional commercial collections agencies offers a distinct strategic advantage.

  • Leveraging Specialized Expertise: Agencies possess deep expertise in debt collection laws and regulations, mitigating legal and reputational risks that internal teams might inadvertently incur. They employ trained negotiators skilled in advanced techniques and understand industry-specific payment behaviors.
  • Driving Efficiency and Allowing Internal Teams to Focus on Core Competencies: Outsourcing collections frees up valuable internal resources—finance, sales, and administrative staff—allowing them to concentrate on revenue-generating activities and strategic initiatives. This optimizes human capital allocation, contributing to long-term competitive advantage and growth.
  • Protecting and Preserving Valuable Client Relationships: Professional agencies act as a neutral third party, using tactful and diplomatic communication to maintain goodwill and the possibility of future business. This contrasts with the potential for internal teams to damage relationships through aggressive tactics. Agencies can often recover debt while preserving client relationships, transforming a potentially adversarial situation into one of mutual understanding.
  • Quantifiable Improvements in Recovery Rates and KPI Performance: Professional agencies consistently demonstrate higher success rates, often improving recovery rates by up to 30%. This enhanced recovery directly translates into improved cash flow and a stronger financial position, providing the financial fluidity necessary for reinvestment and strategic advantage.

While internal collections might seem like the default, a strategic evaluation reveals that professional agencies offer a more robust, compliant, and ultimately more profitable solution for optimizing Accounts Receivable.

Conclusion

Accounts Receivable KPIs are far more than mere accounting metrics; they are vital diagnostic tools and strategic compasses for your company’s financial health. A deep understanding and continuous monitoring of these indicators provide crucial insights into your business’s liquidity, operational efficiency, and overall profitability.

In an unpredictable economic landscape, businesses aiming for sustained financial resilience must recognize that expert collections are not merely a reactive service for bad debt. Instead, partnering with commercial collections agencies should be viewed as a proactive, strategic decision. By leveraging external expertise, companies can optimize cash flow, mitigate significant financial and reputational risks, and ensure the sustained financial agility necessary for long-term success. This strategic collaboration transforms a potential liability into a powerful asset, fostering a more resilient and growth-oriented financial future.

A/R Invoice Collectibility By Age

The average collectibility for B2B invoice receivables by age can vary widely depending on industry, customer base, economic conditions, and credit practices. However, a general trend can be observed in how the likelihood of collection changes over time. 

The time for outside, “third-party” collection agency action is when the debt may still be collectible, best from 90-120 days past due. Waiting too long is to invite a total write-off.

Here’s a typical breakdown by age of receivables:

  1. 0-30 Days Past Due:
    • Collectibility: 95% to 97%
    • Comments: Most recent invoices are usually collected without significant issues, as they are within standard payment terms.
  2. 31-60 Days Past Due:
    • Collectibility: 80% to 90%
    • Comments: These receivables might require follow-up reminders or slight collection efforts. The probability of collection remains high but begins to decrease.
  3. 61-90 Days Past Due:
    • Collectibility: 60% to 75%
    • Comments: At this stage, the collectibility decreases more noticeably. More aggressive collection actions might be required.
  4. 91-120 Days Past Due:
    • Collectibility: 30% to 40%
    • Comments: Receivables older than 90 days are increasingly difficult to collect. This often requires significant effort or third-party collection agencies.
  5. 121-180 Days Past Due:
    • Collectibility: 40% to 50%
    • Comments: The probability of collecting these receivables is low. Legal action or substantial incentives may be necessary to recover some of these debts.
  6. 181+ Days Past Due:
    • Collectibility: Less than 50%
    • Comments: Receivables in this category are often considered highly unlikely to be collected and might be written off as bad debts.
  7. 360+ Days Past Due:
    1. Collectibility: Less than 70%
    2. Comments: Receivables in this category are often considered highly unlikely to be collected and might be written off as bad debts.

These percentages can fluctuate based on specific business practices, customer relationships, and economic conditions. Maintaining good credit management and proactive collection efforts can help improve the collectibility of receivables.

 

From the practitioners at Leib Solutions LLC, a Smyyth company

Collection Agency Should be Part of Your Collection Workflow

All businesses face cash flow issues during challenging economic climates, making it especially difficult to collect customer payments within the agreed-upon terms. To optimize your collection efforts and cash flow, it is essential to reevaluate the priorities of your collection department, including the utilization of third-party collection agencies. Making timely referrals to these agencies for bad debts can significantly improve collection results while minimizing unnecessary costs.

Is Using an Agency a Collection Failure or an Integral Part of the Process?

  • Needing a collection agency does not represent your department’s collection failure, as a certain percentage of all customers are destined to fall into this category regardless of how hard to try to collect.
  • When your collector staff exhausts their efforts without yielding results, there comes the point of diminishing returns. In such cases, a timely collection referral can be a victory for your company.
  • Holding onto past-due accounts for extended periods diverts your staff’s attention from high-priority customers and balances, which are more profitable. Continuously pursuing payment from those who consistently fail to pay is an unproductive use of resources.
  • By allowing collection agencies to handle difficult cases, your internal collectors can focus on where the cash comes from rather than being tied up with long overdue unpaid balances. The longer an account remains past due, the more challenging it becomes to collect. Collectability decreases each month to the extent that after nine months, the likelihood of collection may be close to zero.

Important! Your past-due customers will seek other suppliers and you will lose business if you do not collect. Consequently, integrating timely collection agency referrals into your collection process is essential.

Considerations for Collection Agency Placements:

  1. Utilize your internal resources for accounts 10 to 90 days past due, as they contribute 95% of your cash flow and offer a high return on your time investment. Allow your staff to focus on the accounts receivable that keep your business running.
  2. Waiting beyond 90 to 120 days and hoping for collection before referring the account to a collection agency is counterproductive. Timely interventions are more likely to succeed.
  3. Assigning accounts to a collection agency immediately grabs customers’ attention as they realize that the unpaid debt could negatively affect their credit bureau scores.
  4. Collection agencies charge fees based only on the cash recovered, and a reputable agency increases the chances of successful collection.
  5. The agency can tailor their collection tactics, employing a customer service approach when you hope for future business and a more assertive approach for chronic late payers.

When is the Right Time to Refer a Debt for Collection?

Consider the following five factors before deciding to refer a customer to a collection agency:

  1. The account is 90 days late.
  2. The customer has failed to follow through, broken a promise to pay, or become difficult to reach.
  3. The customer has indicated financial difficulties.
  4. Remember that your customers prioritize their cash payments, and they pay those who have taken more aggressive actions or whose products they need. You have become a low priority and will lose future revenues if you do not collect.

What to Look for in a Collection Agency:

When selecting a collection agency, keep the following eight factors in mind:

  1. Membership in a professional organization such as the International Association of Commercial Collectors (IACC) upholds a strict code of ethics and legal compliance.
  2. Agencies specializing in either B2B or consumer collections. Collecting from businesses is more challenging and requires specialized expertise. If you have commercial debt, choose a commercial bad debt agency.
  3. A well-established track record, having been in business for many years.
  4. The ability to communicate with the agency’s management before initiating business and during the collection process. 
  5. An excellent history of collection results and adherence to market-standard contingency fees.
  6. Strong reviews, such as positive feedback from clients on platforms like Google, indicate trustworthy and quality relationships.

 

Machine Learning in Credit & Collection Scoring

Managing receivables is a crucial aspect of B2B financial management. Late or unpaid invoices and bad debts can significantly impact cash flow, causing businesses to struggle to meet their financial obligations. Companies rely on various tools, including payment and credit scoring, to prioritize their B2B collection activities to stay on top of outstanding payments.

Payment history is an essential tool for managing B2B collections. It provides insight into customer behavior and can be used to prioritize collection efforts and focus on accounts most at risk of defaulting. For example, if a customer consistently pays late, it may be necessary to send reminders or follow up more frequently than with a customer who always pays on time.

Machine Learning (ML) is a branch of artificial intelligence that involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without being explicitly programmed. In accounts receivable, machine learning is used to automate and optimize the remittance application process, the collections process, deduction validation, matching debits to credit memos, and cash forecasting.

Advanced accounts receivable management software often uses Machine Learning (ML) to analyze a wide range of data points, such as a customer’s payment history, credit score, industry, and geographic location. By combining this information with external data sources, such as economic indicators and market trends, ML algorithms can better predict a customer’s payment behavior. In addition, ML can automate many of the time-consuming and repetitive tasks involved in the AR collection process, such as sending reminders to customers, flagging overdue invoices, and prioritizing collection efforts.

6 Reasons to Use Machine Learning in AR Software

  1. Predicting Payment Behavior: ML algorithms can analyze historical data on customer payment behavior to identify patterns and predict when and how much a customer is likely to pay. This can help collections teams prioritize their efforts and focus on customers most likely to pay.
  2. Identifying High-Risk Accounts: ML algorithms can analyze a variety of factors, such as payment history, credit scores, and other financial data, to identify accounts that are at high risk of becoming delinquent. This can help collections teams proactively address potential issues before they become more serious.
  3. Customizing Collection Strategies: ML algorithms can also be used to analyze customer data and identify the most effective collection strategies for each individual customer. For example, some customers may respond better to phone calls, while others prefer email or text messages.
  4. Automating Collections Processes: ML algorithms can automate routine collection tasks, such as sending reminders or following up with customers. This can help collections teams be more efficient and effective while reducing the risk of human error.
  5. Collection Agencies: Determining when to place a past-due debtor account with a third-party collection agency to maximize the chances of recovery. The natural tendency is to delay an agency placement decision and avoid recognizing a loss. Paradoxically, the result of decision avoidance and waiting too long is the bad debt they were trying to avoid. Consequently, companies can benefit from automating placement through ML or even some simple system rules concerning what to do when a receivable reaches X age.
  6. Cash Forecasting: ML can improve financial operations by providing more accurate cash flow forecasting. Traditional AR software solutions typically rely on static assumptions about customer behavior and payment patterns, which can lead to inaccurate cash flow projections. ML algorithms can analyze historical payment data and identify trends and patterns that are likely to continue in the future. This can allow businesses to make more accurate cash flow projections and better plan for future expenses and investments.

Machine learning is a powerful tool for accounts receivable software because it can help collections teams make more informed decisions.

Using Natural Language Processing (NLP) in Accounts Receivable (AR) Software

An enhanced way that ML can improve the AR collection process is by using natural language processing (NLP) technology. NLP technology analyzes unstructured text data, such as emails, PDFs, and remittance backups, to extract meaningful insights.

In this context, NLP technology can analyze customer communications to identify issues preventing them from paying their invoices. For example, NLP algorithms can identify common complaints or issues that customers may be experiencing with the products or services provided. By addressing these issues, businesses can improve customer satisfaction and reduce the likelihood of late or missed payments.

Additionally, NLP technology can automate customer communications, such as sending payment reminders and follow-up emails. By automating these communications, businesses can reduce the time and effort required to follow up with customers manually.

In Summary

In conclusion, machine learning has the potential to revolutionize the way businesses manage their accounts receivable processes. By analyzing large amounts of data and identifying patterns and trends, ML algorithms can provide valuable insights into customer behavior, improve collections, and provide more accurate cash flow projections. As businesses continue to rely on technology to streamline their operations, machine learning in AR software will likely become increasingly common. Machine learning can potentially revolutionize B2B accounts receivable processes, including collections, dispute and deduction management, and invoice collections.

 

9 Best Collection and Accounts Receivable Metrics

Understanding DSO, DDO, and Other Accounts Receivable KPIs

A/R turnover – the credit-to-cash cycle – and working capital are critical to your business, so it is essential to monitor the Key Performance Indicators (KPIs) and other metrics that track your company’s credit, collections, and deduction management health.

In addition, businesses have become more complex, so receivable performance analytics are essential to keep track of the financial health of your receivables.

Here are the key metrics to implement.

1. For Collections, Days Sales Outstanding (DSO) and Best Possible DSO (BPDSO)

Standard DSO is the metric for tracking the effectiveness of Invoice Collection Management. That is, how long it takes to collect payments based on the invoice date, intending to reduce your DSO to as close as possible to your average terms of sale (the “Best Possible DSO” or “Best DSO”). Depending on the industry and seasonality, DSO calculations can get complicated.

However, for a simple example, suppose that your AR totals $1,600,000, and Credit Sales for the last twelve months were $10,200,000. The formula would be:

DSO = Total A/R ÷ Total Credit Sales X 365, and the answer a DSO of 57.2 days.

Best Possible DSO uses only your current (not yet past due) receivables and tells you what your best “on-time payment” turnaround could be.

Best Possible DSO = Current A/R ÷ Total Credit Sales x 365. Using the above numbers, if your Current A/R is $800,000, your Best Possible DSO comes out to 28.

In this case, you have a lot of potential for improvement between the Standard DSO of 57 Days and the Best Possible DSO of 28.

Working towards a DSO that is as close as possible to your Best Possible DSO should be the goal of your department to have a healthy cash flow and ensure your AR management is as efficient as possible.

Once you start calculating the DSO and Best DSO, create monthly targets that “move towards” the Best DSO. You’ll unlikely achieve perfection, so make strides to reduce the metric over 3-6 months.

2. Average Days Delinquent (ADD)

ADD is how many days on average payments are overdue and can be a warning sign of problems. If the number is high, you must determine whether your systems, collections, and invoice processes need improvement. ADD is calculated as the DSO minus your actual (average) terms.

For example, with the hypothetical company above in #1, the ADD would be ten days on September 30. However, say one year later, the ADD is 15 days. That may mean your processes may be falling behind.

Over time, measuring ADD and DSO will show whether you are improving, static, or falling behind.

3. Accounts Receivable Turnover Ratio (ART)

ART measures how effectively you collect your revenues as an annual broad benchmark. It is determined by taking your net credit sales and dividing it by your average accounts receivable balance. When the ratio is higher, you turn A/R into cash more quickly, thus improving your working capital, cash flow, and liquidity.

A low ratio can mean it is time to reconsider credit and collection procedures and add collection automation.

The calculation is ART = net credit sales ÷ average accounts receivable. Using an example of $15,000,000 sales per year ÷ average AR of $2,200,000 = 6.8 ART or, in another case, $15,000,000 sales ÷ average AR of $3,200,000 = 4.7 ART (worse).

4. Collection Effectiveness Index (CEI)

While ART measures how often accounts receivable turn over, CEI measures how effectively you collect all outstanding money in a specific period (usually measured over one year). CEI is calculated as CEI = (beginning A/R + monthly credit sales – ending total A/R) ÷ (all beginning receivables + monthly credit sales – ending current receivables) x 100.

5. Deduction Days Outstanding (DDO)

By dollars: Track Customer Deduction Management results separately from invoice collection, using Deduction Days Outstdanind as the KPI. Similar to how you calculate Days Sales Outstanding (DSO) for invoice collections, add the average daily deductions amounts received during a period (say 90 days), and divide the total outstanding deductions by the average per day. For example, if deductions at the end of a month total $1,000,000 and you receive an average of $25,000 per day, the DDO = 40 days.

By the number of deductions: Another way to think about DDO is to use the number of unresolved deductions since the usual DDO metric often looks better than it is because of the operational focus on large dollar items. Using this method, if deductions at month-end total 6,000 items and you receive an average of 100 deductions daily, the DDO = 60 days.

6. Deduction Effectiveness Index (DEI) New

The A/R department spends so much labor and expense (often 75% of the A/R resources) in deduction management to discover the root causes of errors, find the improper deductions, and ultimately get your money back. 

We employ what we named the DEI metric as a critical KPI to track how we are doing. To determine the DEI every month, compare the total deductions vs. those found to be incorrect vs. the collected deductions. Do this by category (returns, shortages, discounts, trade promotions, etc.) and track your company’s progress.

Unfortunately, industry-peer data is not helpful as company processes and policies differ. Hence, the best way to measure your success is to set internal baselines (where you are today) and work to improve from there.

Regular undisputed invoice receivables have an accepted metric of what percentage you should collect (i.e., 100% minus bad debts). For deductions, however, there is no objective metric for the rate you should recover.

Therefore, an excellent way to determine if you are leaving profits on the table is to have unresolved customer deductions post-audited by an outside firm before writing them off.

7. Number of Invoicing Disputes

Mistakes are costly, so you should track, by reason, how many invoices have to be revised or credits issued due to billing or process errors. If the number is trending upward, it could mean that you have systemic problems in order entry, invoicing, or fulfillment, all of which will impact DSO and company profits.

8. Bad Debts to Sales Ratio

Measure bad debts as a percentage of revenues, but always look behind the number if you can and compare the credit losses against sales (i) gained due to more lax credit risk policies or (ii) lost due to overly restrictive corporate credit policies. Most high-risk credit decisions are intentional and logically decided, calculating that the extra revenues will offset potential losses.

9. Percentage of High-Risk Accounts

Doing business with high-risk customers is part of a business strategy. Do you have an excess of depreciating inventory? Do you need extra market penetration in a territory? Many industries are inherently “high-risk,” so the credit and sales managers are aligned and have to do what they can to offset the additional risk via credit instruments and, perhaps, terms or pricing.

Final Thoughts: How do you manage accounts receivable if you don’t measure receivable performance?

Monitoring your accounts receivable metrics and KPIs is essential to running a healthy business. You’ve collected valuable statistics and need to see how you measure up.

First, of course, you’ll need to look at the historical performance within your organization, but that’s not enough. You also need to compare your performance to industry peers. With these comparisons, you can share insights with Finance, Sales, and Marketing.

You must be on top of your game in today’s global, highly competitive economy. This post was written by the consultants at the Smyyth group of companies.

Leib Receives Coveted A.M. Best “Expert” Award for the 15th Year

We are proud to announce that A.M. Best has, for the 15th straight year,  selected Leib Solutions as one of a handful of companies in the world receiving the coveted “Expert Service Provider” designation awarded for business debt collection and accounts receivable services.

Leib Solutions has been in the commercial collection industry for over 35 years and is an expert at business debt collection in the insurance, manufacturing, distribution, services, and technology industries. Leib is affiliated with the Smyyth group of companies, which specializes in advanced SaaS software and outsourcing services for accounts receivable, credit, collection, and A/R deduction management. The organizations have decades of expertise and leading-edge automation to help clients optimize cash flow and reduce losses due to A//R revenue leakage.

 

Digital Signatures in Credit and Collections – A Best Practice

A digital signature is a cryptographic technique to provide authenticity, integrity, and non-repudiation of electronic documents or data. It is essentially an electronic version of a handwritten signature that provides assurance that the document or message has not been altered and was indeed signed by the claimed sender.

A digital signature is created using a combination of public and private keys. The sender uses their private key to sign the message, and the receiver uses the sender’s public key to verify the signature. This process ensures that only the intended recipient can read the message and that the sender cannot deny signing it.

Digital signatures are commonly used in industries such as banking, healthcare, legal, and government sectors to authenticate electronic transactions, contracts, and other important documents.

Business Case for Digital Signatures in Credit and Collections

Use digital signatures to streamline and speed up credit and collection agreements. Some are still uncertain whether electronic signatures are binding in the United States and Globally,  but the use of e-signatures has become routine and is valid for most transactions. The following information is provided from U.S Government websites and our Smyyth companies’ corporate e-signature policies.

E-signatures have eliminated the hassle of completing commercial transactions, including use in Credit Applications and credit and collection agreements, to an extent that going back to faxes and emailed documents would be unthinkable for routine transactions. If your company is considering new credit risk software, collection software, or AR management software, consider including e-signatures in your processes. You should include all the standard company forms as templates within the digital signature system you decide on. Collection agencies also routinely use digital signing to confirm debt payment plans, as well as for creditor agreements.

The legality of Digital Signatures

Electronic Signatures in Global and National Commerce Act (E-Sign Act) and The Electronic Signatures in Global and National Commerce Act (E-Sign Act signed into law on June 30, 2000, provide a general rule of validity for electronic records and signatures for transactions in or affecting interstate or foreign commerce. There are four basic parts required for an electronic signature to be recognized.

  1. The parties must intend to sign, just as with any written contract.
  2. The parties must agree to do business electronically. For businesses, this can be shown by the circumstances of the interaction. Consumers, however, must affirmatively consent to use electronic records and receive related consent disclosures.
  3. The e-signature system must capture and keep the record that reflects the process by which the “signature” was created or generate a graphical or textual statement proving it was executed.
  4. The United States Laws require that the e-signature records be capable of retention and reproduction by the parties.

The E-SIGN Act solidified the use of electronic records and electronic signatures in commerce by confirming that electronic records and signatures carry the same weight and have the same legal effect as traditional paper documents and wet ink signatures. Both laws provide the following:

  • No contract, signature, or record shall be denied legal effect solely because it is electronic.
  • A contract relating to a transaction cannot be denied legal effect solely because an electronic signature or record was used in its formation.

Note: We do not provide legal advice, and we always recommend you consult with your counsel if you have any concerns. Also, many countries have specified certain types of documents or that are not appropriate for e-signatures, including wills and trusts, powers of attorney, and declarations under oath.

Credit and Collection Scoring Best Practices

There are numerous reasons to use automated credit scoring in your credit (and collection) operations, including faster and better quality decisions, enhanced customer service, more effective compliance and controls, and significantly reduced overhead. Employing credit scoring in a B2B environment is credit management  “Best Practice,” especially if you have many customers.

Using Smyyth’s Carixa cloud technology for credit-to-cash management, Leib can seamlessly incorporate Credit2B’s advanced scoring results into Carixa’s enterprise credit management workflow. Leib and Credit2b.com are Smyyth affiliates.

Here are some benefits to consider from credit scoring, which includes leveraging your own historical data,  credit bureau business information, and industry trade payments.

7  Good Reasons to Use Credit and Collection Scoring

  1. Speed of Credit Decisions. Scoring can dramatically shorten the time it takes to approve orders, a major customer service and sales benefit.
  2. Prioritized Collections.  Use blended credit risk scores to set collection priorities, ensuring the accounts with the highest risk for non-payment get collection attention first. If you focus on “risk,” not just age and value, you will have better outcomes and less bad debt.
  3. Personnel and Overhead Savings. Scoring automates the decision process, dramatically cutting down the personnel costs associated with credit approvals and letting you do more with less.
  4. Credit and Collection Policy. You can use credit and payment scores to establish corporate policies for risk and slow payment tolerance. Credit and Payment scoring ensures consistency for applying  credit policy.
  5.  Collection Agency placement based on the account age rules eliminates “decision freeze” when deciding when an account is turned over to a bad debt collection agency, reducing write-offs.
  6. Customer Advisory. The credit manager can become a partner to sales if you counsel customers on how they can improve their scores by highlighting areas of weakness.
  7. Fewer Bad Debts. You can expect reduced bad debts using a valid scoring methodology since many smaller customers would not get the same level of manual review as the larger exposures.

Data Elements Used in Automated Scoring

Financial metrics for large corporations can be predictive in the 2-5-year range, and many credit analysts still use a traditional or modified Altman-Z Score for this purpose. However, financials are often not available for smaller customers or they are often stale, unreliable, and subject to fast swings. For these smaller debtors, other data elements become more critical, including:

  1. Years in business
  2. Experience of principals
  3. Number of employees
  4. Revenue and Assets
  5. Business and Industry Trends
  6. Financial information (if available) using a dozen key metrics
  7. Public records information
  8. Supplier payment experience (including your trade credit groups)
  9. Bank and Lender Experience
  10. Credit Line Utilization
  11. Credit exposures of other industry suppliers
  12. Public filings, liens, etc.
  13. Transparency with key suppliers
  14. Derogatory comments; Reputation

Using Big Data and Machine Learning

Building truly predictive credit scoring is now significantly easier with the ability to capture “Big Data” from multiple sources and analyze it with powerful software and hardware, where the “machine” can learn from experience and adjust its conclusions; that is, make and correct its decisions based on experience, patterns and trends it sees in the data. 

This is called “Machine Learning,” where computers are taught to detect patterns in data to both predict and validate outcomes with regression testing of past events and then adjust those based on current events. Reaching this goal has gotten much easier due to the rapidly increasing power of computer processing.

W.E. Deming famously said said, “Without data, you’re just another person with an opinion.”

We would add, “if you can’t process the data to produce real insights, they’re just numbers.”

Our experience is that leveraging machine learning can significantly improve predictive credit and payment scoring. We use these techniques to build and customize automated credit scores and credit lines for large trade creditors that need to improve and accelerate credit decisions. As we are a cloud-based service,  there is no software to buy, and we integrate easily with client processes and systems.

Designing a Scoring Model

Our Credit Scoring Framework has a Simple Flow:

  1. Working with a technology provider like Carixa, decide on the outcomes you would like to predict (e.g., bankruptcy, default, severe delinquency, or X days late), and establish a model.
  2. Create a training sandbox using data attributes from multiple sources, including your own experience; for example, business standing, financials, and debtor payment histories, often as many as a dozen separate data elements, and even unstructured credit data, such as industry “attitudes.”   Sharing this in our cloud platform speeds up adjustments, saves time, and simplifies managing the data.
  3. Adjust for the outcome you are aiming for or test multiple outcomes based on “model training sets” created in your sandbox and adjust the importance or weight of certain elements.
  4. More elements do not always better produce a better outcome; what is important is to pick and test for the right elements. For very small businesses, factors such as years in business, number of employees, and social reputation are critical. Economic factors are important. If the consumer economy turns down, it is a leading indicator of problems with payments and defaults in subsequent quarters.
  5. Machine regression picks and weight-adjusts the credit attributes that are critical for the outcome you are trying to predict in real-time.
  6. Using real-time industry data ensures continuous updates to scoring attributes and weights.

    Advantages
    : The scoring model should self-adjust continuously without manual updates, pulling in more data types than traditional models, including micro and macroeconomic variables, to target the prediction of outcomes that match your company’s needs. The models adjust for specific industry or business needs based on your unique data or information, defining your preferred outcome with great precision.
    To complete a fully automated process, we provide calculated credit lines that can be integrated with any financial or ERP you use.

    Customized Calculated Credit Lines

  • By applying your corporate policies, we can calculate a Dollar Credit Line for you, adjusted to your circumstances. This takes into consideration a number of factors, including your tolerance for risk (are you in a fast growth or more risk-averse environment), lender or insurance limits, or product profit margins (a consumer good with a 60% gross margin will tolerate more risk than a service with a 17% margin).
  • Our modelers interpret your process and policy, replicating your rules in a computer model. By way of example, where no financials are available and the customer has fewer than ten employees, you may decide “do not calculate a credit line” but instead perform a manual review or adjust a CCL based on the presence or absence or magnitude of certain elements.
  • Through feedback through a regressive “fit test,” we can adjust the algorithms as required to bring your scores in line with your desired outcomes.

Advantages: Custom Calculated Credit Lines are built to your circumstances and adjusted as required by your rules, policies, and internal and external events. Machine-generated credit lines are useful for accelerated decisions and risk analysis across an entire portfolio. We can actually do this across 99% of registered businesses in North America.


Summary: By using computational power and a scientific approach to data analysis, you can produce extraordinary results with automated credit decision processing and, in doing so, improve credit decisions and customer service while streamlining credit operations.

Commercial Vs Consumer Collection Agencies

If you are in business, there will come a time when you need to enlist the services of a collection agency to help recover your past-due receivables and bad debts. So how do you find the right one?

Commercial debt usually involves significant amounts and often complex circumstances that can lead to financial issues for your business. If the money owed is business debt, Leib Solutions is a highly-rated expert who handles business-to-business bad debt collection.

What is Commercial Bad Debt?

 

Commercial or business, bad debt is the result of a company (the debtor) that buys services or products on credit terms but fails to pay what is due to the seller (the creditor). As a result, the creditor must then act by suing the debtor or assigning the account to a collection agency to avoid a loss. In the worst scenario, if the creditor does not take quick action, the creditor has to write off the sale as a bad debt. Usually, the two businesses have a binding written agreement, such as a contract or a purchase order.

Corporate Form and Owner Liability

Typically, business debts are the responsibility of the debtor corporate entity and not the liability of the entity’s owners. The corporate (corp. or inc.) and limited liability company (LLC) forms of organization are intended to protect the owners from the business’s debts. Limited partnerships (LPs) also offer protection, although the “general partner” of the LP may be liable for the LPs liabilities. In Partnerships and Sole Proprietorships, the partners or owners are generally personally responsible, so many business people shy away from these forms of organization.

Collateral and Personal Guaranty

When a corporation’s or LLC’s credit is insufficient, a creditor may request a personal guaranty or cross-corporate guarantees from affiliated companies, in which case those parties are also liable. In cases of long-term credit, the creditor will request collateral, such as property or equipment. Having collateral or a personal guaranty is a powerful inducement to pay.

What is Consumer Debt?

Consumer Debt is money owed by a natural person or persons. Consumer debt collectors usually deal with only one person – the debtor – and the debts are usually quite simple, unlike business debts, which can be much more complex. The collection of consumer debt is a very highly regulated activity. See FDCPA Below.

The Fair Debt Collection Practices Act [FDCPA]

The Fair Debt Collection Practices Act protects consumers from unscrupulous collectors looking to use any means possible to collect the debt and penalize those beyond established ethical guidelines. In addition to the FDCPA, many states have enacted versions mirroring the FDCPA, and others go far beyond with even more protection for consumers.

The FDCPA does not regulate Commercial collection agencies. The debt is still commercial if the agreement with your business customer also includes a personal guarantee. A commercial collection agency would be the appropriate entity to place this account for collection since they have special expertise in dealing with businesses and handling these complex matters.

Collection Agency Credentials

While most State and Municipal laws require licensing of consumer collection agencies for each state in which they operate, many State licenses for commercial collection agencies are reciprocal throughout the United States.

Professional commercial collection agencies also follow the ethical guidelines of trade organizations, including the International Association of Commercial Collectors, Inc. (IACC). Membership in the IACC requires compliance with high standards of practice.

Choosing the Best Commercial Debt Collection Agency

When choosing a commercial debt collection agency, you will be concerned about how long they have been in business, their capacity to act quickly and expertly to collect your money, as well as how professionally they deal with debtors since the agency is a reflection of your company.

You also want to ensure your receivables are given the most professional attention. Using an agency that only handles commercial accounts, and understands the types of disputes that occur in business transactions, will ensure the best results. Commercial collection specialization delivers better results for you.

Unlike consumer collections, the best commercial collection agencies are not “dialing for dollar” call center operations. Instead, they employ business and negotiation experts familiar with your business.

Comments on Collection Agency Fees

Never choose a collection agency because of the lowest collection rates, just as you wouldn’t choose a doctor on that criteria. It’s the expected net results -the amount of money you get back – that are important. A professional agency should always do its best, but keep in mind that the fee percentage they keep is their incentive. 

Accounts Receivable Automation Tools, AI and RPA

Advanced technologies, including robotic process automation (RPA), will forever change accounts receivable, collections, and deduction management.

Like most other back-office functions, receivables management was a manual affair as recently as twenty or thirty years ago, working off printed agings, typing reconciliations and letters and mailing or faxing. It’s hard to believe that tools MS Excel, word processing, etc. as well as the internet and email (then called “electronic mail”) were not generally available until the1990s, even in the most rudimentary forms.

Improvement of the receivables management function will not only bring down administrative (personnel) costs but importantly to manage cash flow and protect the company’s profits. It has not received a lot of attention up to now because there is generally not a lot of staff involved. For many companies, accounts receivable represent “low hanging fruit” for improvement at this point.

Today, with robotics process automation and artificial intelligence, the job of managing credit, receivables, collections, and deduction management can be incorporated into a holistic, integrated setup that manages the process from customer onboarding to payment. System workflow manages the accounts receivable operation from beginning to pay.

AR is a transformative opportunity for a relatively small investment to drive performance in one of the largest asset classes. Managing inventory turns gets a lot of attention and management time, and it should. Receivables deserve no less attention.

Consider that a $1 Billion(revenues) company may have $125 million of receivables, of which $10 million may be over 90 days and at risk, and there may also be many millions of disputes and customer deductions on top of that.

AR automation also improves the customer experience, eliminating or streamlining trading partner paperwork and reconciliation or orders-shipments-payments. Large buyers (say Wal-Mart, for example) are mandating automation, as increasingly necessary in competitive pricing environments.

For the manufacturer, a tightly integrated billing to payment process will assure a healthy cash flow and an increase in profits due to the elimination of the “revenue leakage” that results from collecting less than you billed.

We are affiliated with the Smyyth companies. The Smyyth Carixa™ Cloud Platform is an example of the type of advanced solution that can transform accounts receivable operations. Automated credit applications, system controlled collection reminder emails with customer-friendly credit card and echeck payment options built right in, computerized communications, instant deduction reconciliation, to 100% automated cash application. Using robotic process automation, even accessing customer systems, is automatic, for documentation, reconciliation, cash forecasting, etc. The software replicates (and automates) our decades of experience and best industry practices to deliver an outstanding, friction-free customer experience.

The technology to optimize credit to cash billing to payment processes is here and will continue to improve using AI and RPA. More companies need to recognize how much more successful they could be by automating these backroom operations.

“Companies can add a few points to their profits with a laser focus on managing what is often their most significant asset -accounts receivable “