Build vs. Buy: The Right Choice for Automating Your Lending Operations
- Mike Kirkup
- Apr 15
- 6 min read
As a commercial lender, you need to move fast without introducing credit risks or compromising borrower experience. Lending automation helps you process loans faster by reducing manual work, streamlining underwriting, and removing the bottlenecks that frustrate clients.
With easier access to technologies such as artificial intelligence (AI) capable of automating lending processes, you are faced with a strategic decision: should you build your own automation system in-house or buy one from a third-party vendor?
Each path comes with trade-offs. Building gives you complete control and a potentially unique competitive advantage. Buying offers faster time to deployment, expert support, and access to features you may not have considered.
This blog helps you weigh your options and explains different approaches to take. You’ll learn what drives cost and effort, and questions that help guide your decision. We’ll also provide an example of building basic automated document collection software to help you understand the skills and effort required.
Why building lending automation in-house sounds appealing
Custom development lets you tailor the system exactly to your lending operations. You can control the borrower experience, build proprietary features, and ensure everything aligns with how your team works.
With the availability of cloud platforms and open-source AI models, it’s tempting to spin up a prototype that handles borrower intake, document uploads, or simple credit evaluation tasks.
Building in-house automation software offers distinct advantages that shouldn't be overlooked.
Competitive differentiation
You can tailor a custom-built solution to your unique lending operations and users, creating a competitive advantage. Since no competitor can purchase the same solution, your custom capabilities remain proprietary.
Strategic control
Building in-house provides complete control over the development roadmap and priorities. This autonomy is valuable for lenders with highly specialized or regulated loan requirements that may not be sufficiently addressed by standardized solutions.
Intellectual property ownership
The algorithms, workflows, and artifacts produced by an in-house solution become your intellectual property, potentially creating additional business value beyond operational improvements. For example, data from a proprietary document analysis tool could unlock unique insights about your borrower base.
Why buying lending automation software makes sense
Buying from a vendor gives you access to expertise and technologies that have been tested across different lenders and thousands of real-world borrower interactions. They’re built to prevent the problems that custom-built systems often encounter, such as failed process steps, inconsistent inputs, and missing information.
The benefits of buying lending automation software are:
Fast deployment: Go live in weeks, not months.
Proven workflows and business logic: The system is built upon lessons learned across the industry, not just your business.
Compliance: To sell within regulated industries, the vendor must comply with the applicable financial, security, and privacy regulations, meaning you worry less about them.
Ongoing updates: Vendors stay current on customer requests, technology trends, borrower best practices, and security issues so you don’t have to.
Common risks to building your own software
Developing lending automation internally has significant implications for your business strategy, resource allocation, and budgets.
AI is easy to start and hard to maintain
Many organizations underestimate the complexity of developing AI solutions for lending operations. Whether it’s document parsing, eligibility checks, or approval workflows, AI-based automation requires upfront expertise and ongoing tuning. You will need engineers, data scientists, and QA testers to ensure the system operates accurately and efficiently as inputs change and new edge cases arise.
While access to AI becomes easier every day, the initial excitement of creating a proof of concept often masks the effort required to build a reliable, production-ready system. What appears impressive in a controlled demonstration can quickly fall apart when processing the diverse and sometimes poor-quality data that borrowers submit.
You’re not just building software, you’re committing to an ongoing product.
Borrowers don’t have the patience for imperfect tools
You may have the patience to improve a system over time. Your borrowers don’t. Unlike internal users who might tolerate glitches in a developing system, clients expect flawless performance from the start.
If the tool misreads an uploaded file or fails to identify something missing, your client immediately disengages.
Once that happens, your team returns to manual workflows, and borrowers wonder why they trusted you.
When trust is lost, it’s hard to earn back.
The hidden costs of maintenance
Companies typically budget for the initial development of an automated solution and struggle to quantify how much is needed for future updates and fixes. There's a common misconception that in-house staff can work on a new feature for a few months, and then it's done. Or that a contracted development team will deliver exactly what you need for the lifetime of the software. These assumptions are unrealistic when accounting for different borrower behaviors, new staff, and changing industry needs. Each update requires investigation, analysis, and improvement, creating an endless cycle of enhancement that many organizations aren't prepared to sustain.
For example, document collection software needs regular updates to handle new document types, changing regulatory requirements, and evolving borrower patterns. Specialized vendors dedicate entire teams to this ongoing optimization – a commitment that can be difficult for lenders to justify for a single internal application.
Build vs. buy: Key evaluation criteria
Here’s how the two options compare:
Criteria | Build in-house | Buy from vendor |
Time to deploy | Prototype: 6–12+ months Production: 6–12+ months | 2–6 weeks, including proof-of-concept. Modern, LLM-based solutions can often be deployed in less than a day. |
Initial cost | High, often unpredictable (development time, infrastructure set up, testing) | Predictable subscription pricing |
Integration effort | Knowledge of internal systems eases effort | You must find a vendor that supports existing systems |
Maintenance | Ongoing feature updates, bug fixes, security patches | Included in subscription |
Security compliance | You must implement and maintain | Built-in security and compliance controls |
Borrower experience | You must research, implement, and maintain | Vendor experts develop and maintain |
Competitive Advantage | Custom features no one else has | Access to best practices across the industry, accessible to anyone using the tool |
You might consider building if:
You can afford the longer development cycle of a custom solution.
Your lending process is unique, and off-the-shelf tools won’t fit.
You have a skilled engineering team experienced with the necessary technologies.
Your IT department is ready to support a mission-critical application.
You’re prepared to invest in ongoing support and improvements.
Buying may be the better option if:
You need to improve lending operations quickly.
You want reliable features out of the box.
You want to keep your team focused on deals and credit applications, rather than building software.
You can’t afford to frustrate borrowers or slow down loan approvals.
You prefer the stability of working with a partner who updates and maintains the system for you.
Build your own example: Document collection software
To illustrate the level of effort that goes into building an in-house tool, let’s look at a basic automated document collection software project. Lenders who build their own systems often begin with the same assumptions: the feature should be simple to create, and reliably meet today’s needs.
An in-house or contracted development team must tackle various technical and workflow challenges to ensure reliable interactions with borrowers:
File handling and compatibility across various devices, browsers, and file types.
File validation to identify incomplete uploads, unreadable scans, or improperly formatted documents.
Conditional logic to dynamically generate document checklists based on loan type, borrower profile, and local regulations.
Scalable architecture to handle peak workloads without breaking down.
Security infrastructure to ensure compliance with the applicable standards and data privacy laws.
Status visibility so borrowers and internal teams can track document submission progress.
Error messaging and guided flows that help borrowers correct mistakes without contacting your team.
Implementation becomes much trickier when attempting to use AI. Even with software development expertise, these systems may fall short when borrowers upload unexpected files, skip required documents, or get lost in the process due to poor UX. When the system lacks guardrails, manual follow-up becomes necessary, undermining the entire goal of automation.
Different approaches to automation
For many lenders, the optimal approach may lie somewhere between building and buying lending operations software. Consider these strategies:
Start with vendor solutions for core automation functionality, then build custom modules for your unique lending operations around it.
Partner with vendors who offer customization options for their workflows.
Partner with a vendor who uses AI that adapts to changing borrower behaviors and loan types.
Automating lending operations is a strategic and tactical choice
The decision between building and buying a lending automation solution involves complex tradeoffs. While building in-house offers potential competitive advantages, the realities of software development and borrower expectations create compelling arguments for partnering with specialized vendors.
Arlo: AI-powered document collection in less than a day
Arlo is the document collection vendor of choice for intelligent, accelerated loan processing. Through large language models (LLMs) that adapt to different loan types and unexpected fields, Arlo fits into every business-to-borrower workflow to reduce costly follow-ups and processing delays. It’s also deployable by most firms in less than a day.
Regardless of your choice, remember that in today's lending environment, the quality of your processes and overall borrower experience ultimately determine your success. And that requires automation solutions that work flawlessly from day one.
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