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Bectran Product Team
I
December 28, 2025
7 minutes to read
For many credit managers, the daily reality involves balancing contradictory demands. The sales team wants approvals immediately. Finance leadership wants zero risk and total compliance. The credit team is often stuck in the middle, trying to satisfy both sides using tools that were built decades ago.
The challenge is rarely a lack of skill or effort on the part of the credit department. The issue is usually structural. When processes rely on manual data entry, email chains, and spreadsheets, there is a hard limit on how fast the team can move without making mistakes.
Most credit managers know they need better tools. The difficulty lies in proving it to the rest of the business. Requesting a budget for new technology requires more than just saying the current system is slow. It requires a clear business case that connects operational headaches to financial reality.
To build a business case, you must first accurately document the current state. It is easy to say things are "busy," but specific examples carry more weight.
One of the most common friction points is the pressure to approve credit applications within a specific timeframe, regardless of the volume coming in. When you combine high application volume with a strict service level agreement (SLA), manual processes break down.
Another major hurdle in building a business case is the lack of hard data. When systems are manual, tracking performance metrics becomes a manual project in itself. Consequently, many credit departments run on estimates rather than facts.
Many credit teams are operating on ERPs or legacy systems that were never designed for modern credit workflows. These systems are often rigid, difficult to integrate with, and expensive to maintain.
To convince leadership to invest, you must explain why the current problems exist. It is not enough to say the software is old. You must explain the operational impact of that age.
Most ERPs are designed for accounting and record-keeping, not for the dynamic workflow of credit risk assessment. When a credit manager tries to manage a 24-hour promise time inside a system like an IBM iSeries, they are fighting the software. These systems often require navigating multiple screens to find customer data, lack automated integration with credit bureaus, and cannot trigger automatic alerts for portfolio changes.
Some companies build proprietary software to bridge the gap. While this seems cost-effective initially, it often creates a "technical debt" trap. In-house software requires internal IT support to update. When the market changes or when new technologies like AI become standard, the proprietary software becomes a liability. It cannot adapt quickly, leaving the credit team with a tool that is "out of date" just a few years after it was built.
Manual workflows do not scale linearly. If application volume jumps from 300 to 500 per month, a manual process would require adding more headcount to keep up. In contrast, an automated workflow can handle increased volume with the same headcount. The root cause of the backlog is not a lack of people. It is a process that relies on human intervention for every single step, from data gathering to decision-making.
When presenting to the CFO or executive leadership, you need to speak their language. Avoid focusing solely on "making life easier" for the credit team. Instead, focus on risk, revenue, and ROI.
The Problem: The business wants a 24-hour turnaround (Speed), but the credit team needs to verify bank references, trade references, and financials (Due Diligence).
The Business Case: Calculate the cost of the trade-off.
The Pitch: "We are currently trading security for speed. Automation allows us to have both."
The Problem: The team is "guesstimating" a 4-5-day turnaround. This means you cannot accurately forecast cash flow or onboarding velocity.
The Business Case: Position data accuracy as a strategic asset.
The Pitch: "We cannot improve what we do not measure. Automation gives us the visibility to remove friction and accelerate revenue."
The Problem: Relying on proprietary, in-house software or legacy IBM systems isolates the department from modern advancements.
The Business Case: The market is moving toward AI-driven credit analysis.
The Pitch: "Buying a vendor solution is cheaper and safer than trying to maintain our own software in an AI-driven market."
A strong business case demonstrates that credit automation benefits the entire company, not just the credit department.
If the company plans to grow, the credit department must handle more volume without slowing down sales. If the team handles 300 apps per month and the company targets 20% growth, the volume would reach 360. Can the current manual process handle 60 more apps without delaying orders? Likely not. Automation ensures that credit is an enabler of growth, not a bottleneck.
Manual data entry is prone to error. Copying data from a PDF into a legacy ERP invites mistakes: typos in tax IDs, incorrect credit limits, or missed red flags. By automating the data capture, you reduce the operational risk of human error. This protects the company from fraud and compliance violations.
The onboarding process is the customer's first interaction with the finance back-office. A slow, paper-heavy process with a "guesstimated" timeline frustrates new customers. A digital, transparent portal experience sets a professional tone and makes it easier for customers to do business with you.
Building a business case is not about complaining about the workload. It is about presenting a mature improvement plan. The credit managers who succeed in getting a budget are those who can draw a straight line from their daily operational pains to the company's bottom line.
By answering these questions and using the frameworks above, you can shift the conversation from "we need new software" to "we need to protect the business and accelerate revenue."
Ready to build your business case for credit automation? Bectran's platform processes 1 credit application every 4 seconds, with automated reference checks, real-time tracking dashboards, and instant credit decisioning that eliminate guesswork and meet 24-hour SLAs without sacrificing due diligence. See how automation can scale your credit operations.
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