Fact: 30-50% of RPA implementations in finance fail.
At Exela FAO, we’ve seen this firsthand while processing over $1Bn in financial transactions annually. The most painful part? Failures such as these are entirely preventable.
The problem isn’t RPA technology. It’s how organizations approach robotic process automation services within their finance operations. Whether it’s trying to automate unstandardized AP processes, forcing RPA into complex cash applications, or mishandling bot-human handoffs in reconciliation workflows – the root causes are surprisingly consistent.
After fixing hundreds of failed RPA implementations for global enterprises, we’ve identified the exact patterns that doom finance automation projects. More importantly, we’ve developed a proven framework to get them right.
Coming up:
– Why do RPA projects fail?
– The true cost of failed RPA in finance operations
– Process selection: Why you’re automating the wrong things
– The standardization trap: Fix your process first
– The human-bot handoff problem
– RPA governance: What your FAO partner should provide and why
– How can RPA be used in finance – a tested and practical framework
– KPIs and metrics to evaluate automation readiness
– The path forward: Action steps
Why do RPA projects fail?
Finance RPA projects fail because of three critical mistakes. These aren’t technology problems. They’re strategic errors in how organizations approach automation.
The 80-20 rule violation
Most organizations try to automate their exceptions first.
For example, they’ll target complex vendor invoice variations in AP, hoping to reduce manual effort.
This is backwards.
Start with the first 80% of standardized transactions. Automate your vanilla processes first – like simple PO-based invoices with consistent formats.
Master the basics before tackling exceptions.
The “automate now, fix later” trap
We see this constantly.
Teams rush to automate broken processes, hoping RPA will fix underlying issues.
It never does.
Example: A global manufacturer tried automating their cash application process while having 12 different remittance formats. The bots failed. First, they standardized down to 3 formats. Now, their cash application is 85% automated.
The missing control framework
Organizations deploy bots without clear ownership, monitoring, or exception protocols.
Who handles a failed automation?
When does a human step in?
What’s the escalation path?
Without this framework, bots either get shut down or create bigger problems than they solve.
Example: A Fortune 500 client tried automating intercompany reconciliations across 30 entities. The bot worked flawlessly in testing. In production, it failed because:
– Each entity had different posting rules
– No clear protocol for handling exceptions
– No defined handoff between the bot and the accounting team
The project was scrapped after 3 months. After implementing proper controls and standardization, they now have 70% of reconciliations automated.
The fix isn’t complicated. But it requires discipline. Every successful finance RPA project needs:
– Clear process standardization
– Focus on high-volume, rule-based transactions
– Detailed control frameworks
– Defined human-bot interaction protocols
The true cost of failed robotic process automation services in finance operations
When RPA projects fail in finance, the costs go far beyond wasted technology investments. Let’s break down the real impact on your organization.
Direct financial losses
Technology investments in failed RPA run deep. Not only are you paying for unused bot licenses, but you are also paying for implementation consultants, infrastructure setup, maintenance teams, and training programs. All while your original manual processes continue running in parallel.
But these visible costs are just the beginning.
Hidden operational costs
Failed RPA creates a cascade of operational inefficiencies. Teams end up doing double work – first fixing bot errors, then processing transactions manually. Workflows that should take hours stretch into days. Audit trails become fragmented between automated and manual steps. Data quality suffers as processes swing between systems and human operators.
Example: A retail client’s failed AP automation created a perfect storm. Their vendor payment cycles doubled. They needed additional staff just to fix bot errors. Vendor relationships deteriorated as payments got delayed. What started as a technology problem escalated into an executive-level crisis.
The strategy tax
Every failed RPA project makes the next digital initiative harder. Finance teams become skeptical of automation. Leadership questions technology investments. Digital transformation roadmaps stall. The organization develops immunity to change – precisely when it needs to transform.
Opportunity costs
The biggest cost isn’t what you lose – it’s what you never gain.
Successful RPA in finance operations upgrades processing speed, accuracy, and visibility. Teams shift from data processing to data analysis. Real-time insights become possible. Your finance function gains a true competitive advantage.
Process selection: Why you’re automating the wrong things
Most finance teams start their RPA journey by targeting the wrong processes.
Here’s why – they look for the most painful processes first. It’s a natural instinct, but it’s wrong.
Your complex problems aren’t bot problems
Take invoice processing. When finance leaders think automation, they immediately target complex vendor invoices with multiple formats. Or non-PO invoices requiring extensive validation. Or exceptions needing constant human judgment. This approach guarantees failure.
The right way is to start with the boring.
Successful RPA starts with standardized, rule-based processes. Take your simplest PO-based invoices from long-term vendors. They follow consistent formats. They have clear validation rules. They rarely need human decisions.
This is perfect RPA territory.
Before automating any finance process, answer these questions:
– Is the process standardized across all cases?
– Are the business rules clearly defined?
– Can decisions be made without human judgment?
– Is the process volume high enough to justify automation?
– Are the inputs consistently formatted?
Pause right now if your answer to any one of these was “no.”
Fix the process first.
Where to actually start
Here’s where RPA delivers immediate value in finance:
– Standard PO invoice processing
– Basic payment runs
– Bank statement reconciliations
– Fixed asset register updates
– Routine journal entries
– Standard management reports
The key word is “standard.” Start with processes that already work smoothly. Automation should improve efficiency, not fix broken processes.
The standardization trap: Fix your process first
A broken manual process becomes a broken automated process – just faster.
Yet organizations keep trying to automate unstandardized workflows. This approach creates more problems than it solves.
The hard truth about process standardization
We recently audited a failed AP automation project. The client had 14 different ways to process vendor invoices. Different subsidiaries followed different rules. Different teams had different approval flows. They tried forcing one RPA solution across all variations. It failed spectacularly.
Here’s what successful standardization looks like:
– One clear process flow
– One set of business rules
– One way to handle exceptions
– One chain of approvals
– One format for inputs and outputs
Example: Before automating cash application, a retail client mapped their remittance formats. They discovered 23 different formats across customers. No bot could handle that complexity. First, they standardized down to 3 core formats and worked with top customers to comply. Only then did automation succeed.
The cost of skipping standardization
When you automate without standardizing:
– Bots break when they hit process variations
– Exception volumes actually increase
– Teams lose trust in automation
– Manual intervention becomes more frequent
– Projects get abandoned mid-way
Fix these first
Before touching RPA, standardize these critical areas:
– Document formats (invoices, purchase orders, remittances)
– Approval hierarchies
– Business rules and validations
– Exception handling protocols
– Process handoffs between teams
The standardization checklist
Your process is ready for automation when:
– Every team member follows the exact same steps
– Exceptions have clear, documented handling rules
– Input formats are consistent and controlled
– Business rules are explicitly documented
– Process outcomes are predictable and measurable
This isn’t exciting work. It’s necessary work.
Standardization isn’t just about making processes consistent. It’s about making them consistently correct.
The human-bot handoff problem
The handoff between bots and humans is where most finance automation breaks down. It’s rarely about technology. Most of the time, it’s about crystal-clear ownership and responsibility.
The ownership problem
Picture this: A bot processes an invoice but can’t validate a tax code. Who handles it? The AP team says it’s IT’s problem because it’s a bot issue. IT says it’s a finance problem because it’s a tax decision. Meanwhile, the invoice sits unprocessed.
This happens daily.
Example: A global manufacturer’s intercompany reconciliation bot would flag exceptions. But there was no clear protocol for who picked up these exceptions, when, or how. Result? Exceptions piled up. Month-end close got delayed. The bot got blamed. The real problem? Poor handoff design.
What clear handoffs look like
Successful human-bot collaboration needs:
– Clear exception triggers – exactly when should a bot stop?
– Defined human pickup points – who gets notified?
– Response timeframes – how quickly must humans act?
– Resolution protocols – what steps should humans take?
– Restart procedures – how does the bot resume processing?
Designing the right alerts
Bot exceptions aren’t all equal. Create three clear tiers:
Tier 1: Immediate human action needed (payment errors, compliance issues)
Tier 2: Next-day resolution required (validation problems, missing data)
Tier 3: Weekly review sufficient (pattern anomalies, performance issues)
Build your handoff framework because your bots will hand off work to humans.
Plan for it.
Design for it.
Monitor it.
A bot that successfully hands off exceptions is better than one that fails trying to handle everything.
RPA governance: What your finance and accounting outsourcing services partner should provide and why
Your finance and accounting outsourcing services partner must do more than just deploy bots. They must govern the entire automation ecosystem.
Here’s what real RPA governance looks like – and why it matters.
Bot performance management
Performance tracking isn’t a nice-to-have. It’s essential. Your FAO partner must actively monitor process completion rates, exceptions, and system performance.
Without clear metrics, problems fester until they become crises.
Example: A client’s FAO provider deployed AP automation but provided no performance tracking. When processing times slowed, no one could pinpoint why. After implementing proper monitoring, they identified specific vendors causing 80% of the delays. The fix took one day.
Change management controls
Finance processes evolve constantly. Tax rules change. Approval flows shift. Vendors update invoice formats. Your FAO partner must have a robust system to manage these changes. This means keeping process documentation current, coordinating system updates, and ensuring teams stay trained on the latest workflows.
Compliance and control framework
In finance automation, control isn’t about restriction – it’s about protection. Your partner must maintain complete audit trails, ensure data security, and regularly test controls. When auditors ask questions, you need clear answers about how your automated processes work.
Business continuity planning
A single bot failure shouldn’t cripple your finance operations. Your FAO partner needs proven backup procedures and disaster recovery protocols. More importantly, they need to test these regularly. Theory isn’t enough – continuity plans must work in practice.
Continuous improvement program
Automation isn’t a one-time project. It’s an ongoing program. Your partner should constantly analyze performance data, identify optimization opportunities, and recommend improvements. Without this forward momentum, your automation becomes stagnant and obsolete.
Strong governance prevents small issues from becoming major problems. It protects your investment in automation.
Most importantly, it ensures your finance operations keep running smoothly, with or without bot assistance.
How can RPA be used in finance – a tested and practical framework
Let’s cut through the theory and look at exactly how to implement RPA in finance operations. We’ll break this down process by process based on real implementations that work.
Accounts payable: Start here
Begin with standard PO-based invoice processing. Here’s the proven sequence:
– First, automate invoice data extraction – pick your top 5 vendors with consistent formats
– Then add automated validation against POs and receipt documents
– Next, automate straightforward payment runs
– Finally, add exception routing to specific teams
Accounts receivable
Cash application is your starting point. Here’s how:
– Begin with electronic payments that have clear remittance data
– Introduce automation; match payments to invoices
– Add automated customer communication for discrepancies
– Build in automated cash forecasting
Record to report: Build in layers
Start with recurring journal entries:
– First, automate standard monthly accruals
– Then add prepayment amortization entries
– Next, automate basic account reconciliations
– Finally, add variance analysis reporting
Why this framework works
The key is progressive automation. Each stage builds on the last. You’re not just automating tasks – you’re building an automated finance function step by step.
For any finance process, you automate:
– Map the current process in detail
– Identify the stable, rule-based components
– Automate such components, go one at a time
– Test extensively with real data
– Roll out gradually, starting with your most standardized scenarios
Critical success factors
– Pick processes with clear rules and high volume
– Start with your most standardized workflows
– Build in clear handoffs between bots and humans
– Test with real-world scenarios, not just ideal cases
– Monitor and measure every automated component
Warning signs to watch
– If a process requires frequent human judgment, it’s not ready
– If you can’t clearly document the rules, don’t automate yet
– If exceptions are more common than standard cases, fix the process first
Specific metrics and KPIs to evaluate automation readiness
Before automating any finance process, measure its current state.
Here’s what to assess and how to interpret the numbers.
Process stability metrics
Track how consistently your process runs today. Measure:
– Process variations: If a process has more than 3 different ways of execution, it’s not ready
– Exception rates: Your standard process should handle at least 70% of cases
– Manual intervention frequency: If humans must intervene more than twice per process, standardize first
Volume and time metrics
Your automation must justify its cost. Measure:
– Transaction volume: How many times does this process run monthly?
– Processing time: How long does each transaction take?
– Peak load periods: When does volume spike?
One retail client tracked these metrics for payment processing. They found that 80% of their volume came from 20% of their vendors. They automated just these high-volume vendors first – quick wins with clear ROI.
Data quality indicators
Your automation is only as good as your data. Check:
– Input format consistency: What percentage of your inputs follow standard formats?
– Data accuracy: How often do you find errors in source data?
– System compatibility: Can your systems share data without manual conversion?
Error and rework metrics
Understand your current error patterns:
– Error rates by process step
– Time spent on corrections
– Cost of mistakes
– Recurring error patterns
Cost impact metrics
Build your business case with:
– Current processing cost per transaction
– Time spent per process step
– Overtime hours during close periods
– Error correction costs
The readiness threshold
Your process is ready for automation when:
– Standard process handles >70% of cases
– Error rates are below 5%
– Data formats are consistent
– Rules are clearly documented
– Volume justifies the investment
The path forward: Action steps
Let’s map out your next 90 days of finance automation.
Based on our experience implementing RPA across global finance operations processing over $1Bn in transactions annually, here’s your practical roadmap.
First 30 days: Assessment phase
Start with a thorough process audit. Document your current workflows. Map your automation opportunities. Most importantly, measure your process standardization levels. Having implemented automation for Fortune 100 enterprises, we’ve learned that this foundation step is non-negotiable.
Days 30-60: Preparation phase
Focus on standardizing your target processes. Begin with your most stable, high-volume workflows. Remember – successful automation comes from starting small but starting right. This is where having an experienced FAO partner can dramatically accelerate your timeline.
Days 60-90: Implementation phase
Now you’re ready to begin automation, starting with your most standardized processes. Deploy bots with proper governance frameworks and clear human-bot handoff protocols. Monitor closely. Measure constantly. Adjust as needed.
Key steps for success
– Run a detailed process assessment
– Calculate your automation ROI
– Start standardizing target processes
– Design your control framework
– Begin with pilot automation
– Scale based on results
Common pitfalls to avoid
Don’t rush to automate everything at once. Don’t skip the standardization phase. Don’t underestimate the importance of governance. These are lessons learned from hundreds of finance automation implementations.
Your next step
Consider starting with a thorough evaluation of your finance processes’ automation readiness. This assessment will:
– Identify your best automation opportunities
– Highlight standardization needs
– Calculate potential ROI
– Map your automation journey
The finance teams we work with typically find that this structured approach leads to 60-80% automation rates in their core processes within six months. But it starts with getting the foundations right.
Ready to explore your automation potential? Our finance automation experts can help assess your readiness and map out your path forward. Let’s talk about transforming your finance operations with proven automation strategies that work.
Click on the “Contact Us” button below.
DISCLAIMER: The information on this site is for general information purposes only and is not intended to serve as legal advice. Laws governing the subject matter may change quickly and Exela cannot guarantee that all the information on this site is current or correct. Should you have specific legal questions about any of the information on this site, you should consult with a licensed attorney in your area.
