Manual vs. Automated Due Diligence
A side-by-side comparison of speed, quality and auditability for grant due diligence. How automated checks save time while keeping humans in the loop.
Due diligence is the backbone of responsible grantmaking. Before funding an organisation, funders need to verify that it exists, is properly governed, is financially viable, and is capable of delivering the proposed work. The question is not whether to do due diligence -- it is how to do it efficiently, consistently, and at scale without burning out your team.
This guide compares the two approaches: manual due diligence, where staff perform each check by hand, and automated due diligence, where technology handles the routine lookups so humans can focus on interpretation and judgement. We will be honest about the strengths and limitations of both.
TL;DR
Manual due diligence takes 2 to 4 hours per applicant, is inconsistent between reviewers, and creates bottlenecks during high-volume funding rounds. Automated due diligence cross-references the Charity Commission register, Companies House, financial data, and governance indicators in minutes, with a full audit trail. The best approach is human-in-the-loop: automate the lookups, keep humans for interpretation. Plinth automates routine checks while ensuring staff make the final decisions.
What you will learn
- What manual due diligence actually involves and how long it takes
- Where manual processes break down at scale
- What automated due diligence can and cannot do
- How a human-in-the-loop model works in practice
- How Plinth's approach compares to competitors who claim AI due diligence
- When manual review remains essential and should not be automated
Who this is for
- Grants officers and programme managers who spend hours on repetitive checks
- Heads of grantmaking looking to improve consistency and reduce turnaround times
- Compliance and governance leads concerned about audit trails and regulatory risk
- Trustees and board members who want assurance that due diligence is thorough
- Operations teams evaluating grant management software with due diligence features
Time and cost comparison
| Factor | Manual Due Diligence | Automated Due Diligence (Plinth) |
|---|---|---|
| Time per applicant | 2-4 hours | Minutes for routine checks |
| Consistency between reviewers | Variable -- depends on individual rigour | Consistent -- same checks every time |
| Audit trail | Partial -- often notes in emails or spreadsheets | Complete -- every check logged automatically |
| Scalability | Linear -- more applications means more staff hours | Handles volume without proportional staff increase |
| Error rate | Higher -- human fatigue and oversight | Lower for routine lookups; flags anomalies |
| Charity Commission checks | Staff manually searches register | Automatic cross-reference |
| Companies House verification | Staff manually searches register | Automatic cross-reference |
| Financial health indicators | Staff reads accounts manually | AI analyses key ratios and flags concerns |
| Staff cost (200 applications/year) | Approximately 400-800 hours of staff time | Fraction of the time, with staff focused on judgement |
| Best suited for | Low-volume, high-complexity assessments | High-volume programmes needing consistent checks |
What manual due diligence actually involves
When a grants officer performs due diligence manually, they typically work through a checklist that includes:
- Charity Commission register check. Is the organisation registered? Is its registration current? Are there any regulatory actions or concerns noted?
- Companies House search. If the applicant is a company or CIC, are their filings up to date? Who are the directors? Are there any outstanding issues?
- Financial accounts review. Downloading and reading the most recent accounts. Checking income levels, reserves, any going concern notes from auditors.
- Governance documents. Requesting and reviewing the governing document, safeguarding policy, equality and diversity policy, and other relevant policies.
- Trustee and director checks. Reviewing the board composition. Checking for any disqualified directors or trustees.
- Previous funding history. Checking internal records for any past grants, their outcomes, and whether monitoring reports were submitted.
- External references. In some cases, contacting other funders or partners for references.
This process is thorough when done well. The problem is that it takes 2 to 4 hours per applicant, and the quality depends entirely on the individual doing the work.
Where manual processes break down
Inconsistency between reviewers
Two grants officers checking the same organisation will not necessarily look at the same things, in the same depth, or draw the same conclusions. One might spend 30 minutes on financial accounts while another spends 10. One might check Companies House filings while another skips it for registered charities. Without rigid protocols and regular calibration, manual due diligence produces inconsistent results.
Human error and fatigue
When a grants officer is processing their fifteenth application in a week, the quality of their checks inevitably declines. It is not a reflection of competence -- it is a reality of repetitive cognitive work. Fields get skimmed, anomalies get missed, and the temptation to rely on previous assessments without re-checking grows.
Bottlenecks at high volume
Most funders receive applications in waves -- often hundreds arriving before a deadline. Manual due diligence creates a bottleneck: applications cannot progress to panel until checks are complete, and checks take hours each. This either delays decisions (frustrating applicants) or pressures staff to cut corners (increasing risk).
Poor audit trails
Manual checks often produce notes scattered across emails, Word documents, and spreadsheets. If a trustee or regulator asks "what due diligence did you perform on this organisation?", reconstructing the answer from fragmentary records is difficult and time-consuming. A proper audit trail should show exactly what was checked, when, by whom, and what was found.
Staff doing lookups instead of analysis
The most valuable thing a grants officer can do is apply judgement: interpreting what the data means, assessing whether risks are manageable, and making proportionate decisions. When they spend most of their time on mechanical lookups -- typing charity numbers into registers, downloading accounts, copying data into spreadsheets -- that judgement capacity is wasted on tasks a machine could do faster and more reliably.
What automated due diligence can do
Automated due diligence, as implemented in Plinth, handles the routine lookups that consume the bulk of manual due diligence time:
- Charity Commission cross-reference. Automatically checks registration status, regulatory history, and any flags or concerns on the register.
- Companies House verification. Confirms company status, filing history, director information, and any outstanding actions.
- Financial data analysis. Reads key financial indicators from submitted or publicly available accounts, flags unusual patterns such as declining income, low reserves, or disproportionate spending.
- Governance indicators. Checks for the presence of key policies, board composition, and governance structures.
- Anomaly detection. Identifies discrepancies between what an applicant states in their application and what public records show -- for example, a claimed income that does not match filed accounts.
- Full audit trail. Every automated check is logged with a timestamp, the data source, and the result. This trail is available for review, reporting, and regulatory purposes.
The key advantage is consistency. The automated system performs exactly the same checks on every applicant, every time, without fatigue or variation. It also works at speed: checks that take a grants officer hours are completed in minutes.
The human-in-the-loop principle
Plinth's approach to automated due diligence is explicitly not about removing humans from the process. It is about removing humans from the parts of the process where they add the least value (mechanical lookups) and freeing them for the parts where they add the most value (interpretation and judgement).
In practice, this means:
- Automated checks run first. When an application is submitted, Plinth performs its routine checks and compiles the results into a clear summary.
- Staff review the results. A grants officer sees the compiled due diligence report, including any flags or anomalies, and applies their professional judgement.
- Humans make the decision. The system does not approve or reject applications. It provides the information; the human decides what it means and what to do about it.
This model is faster, more consistent, and more auditable than pure manual checking -- while preserving the human judgement that is essential for fair and proportionate grantmaking.
How competitors compare
Several grant management platforms claim to offer AI or automated due diligence, but the depth of these offerings varies significantly:
- SmartSimple references AI capabilities in its marketing but provides limited public detail about what its due diligence automation actually checks or how it works.
- Fluxx focuses on workflow automation but does not offer automated due diligence checks against public registries.
- Submittable provides form-based application management but does not include due diligence automation as a core feature.
- Blackbaud Grantmaking offers reporting and workflow tools but relies on manual processes for due diligence.
Plinth is currently one of the few platforms that performs automated cross-referencing against the Charity Commission register and Companies House as part of the due diligence workflow, with AI analysis of the results.
Where manual review remains essential
Automated due diligence is powerful for routine checks, but there are situations where human review is not just valuable but essential:
Complex governance structures
Some organisations have unusual structures -- fiscal sponsorship arrangements, unincorporated associations, partnerships between multiple entities, or overseas parent organisations. Automated systems can flag these as unusual, but interpreting whether the structure is appropriate requires human understanding of the context.
Start-up organisations
New organisations may have limited or no history on public registers. A charity registered three months ago will not have filed accounts. An unregistered community group will not appear on the Charity Commission register at all. In these cases, due diligence necessarily relies on other evidence -- references, track records of individuals, project plans -- that requires human assessment.
Sensitive assessments
Some due diligence involves judgement calls that should not be automated: assessing whether an organisation's approach to a sensitive issue is appropriate, evaluating the quality of a safeguarding framework beyond its mere existence, or considering reputational risks that are not captured in registry data.
Proportionality decisions
Good due diligence is proportionate to the level of funding and risk. A 2,000-pound grant to a well-known local charity does not need the same depth of checking as a 200,000-pound grant to a new organisation. Making proportionality decisions requires human judgement about context and risk appetite.
Building a blended approach
The most effective due diligence programmes combine automated and manual elements:
- Automate the baseline. Use automated checks for every application to ensure consistent minimum standards.
- Tier your manual review. Use the automated results to identify which applications need deeper manual investigation and which can proceed with lighter-touch review.
- Document everything. Whether checks are automated or manual, ensure the results are recorded in a single system with a clear audit trail.
- Review and calibrate. Periodically review the automated checks to ensure they are catching what matters and not generating excessive false positives.
FAQs
Is automated due diligence expensive?
No. The time savings typically outweigh the cost within the first funding round. A grants officer spending 3 hours per applicant on manual checks across 100 applications represents 300 hours of staff time. Even at modest salary levels, the cost of that time far exceeds the cost of an automated system.
Will automation reject applicants automatically?
Not in Plinth. The automated system performs checks and presents results; human staff review the findings and make all decisions. No applicant is rejected without a human reviewing their case.
Can we tune the sensitivity of automated checks?
Yes. You can configure which checks are performed, what thresholds trigger flags, and how results are weighted -- all proportionate to your programme's risk appetite and context.
What about data protection?
Automated due diligence in Plinth uses publicly available data from the Charity Commission and Companies House registers. Where applicant-submitted data is processed, it is handled in accordance with GDPR requirements, with appropriate data processing agreements in place.
Does this work for organisations outside England and Wales?
Plinth's automated checks currently cover the Charity Commission for England and Wales and Companies House. For organisations registered in Scotland (OSCR) or Northern Ireland (Charity Commission for Northern Ireland), manual checks may still be needed for some elements, though the platform continues to expand its coverage.
Recommended next pages
- Automate Due Diligence -- a practical guide to implementing automated checks
- AI Transforming Due Diligence -- broader trends in AI-powered verification
- What is a Due Diligence Check? -- fundamentals for teams new to the process
- Human-in-the-Loop Grantmaking -- the principle behind keeping humans central to AI-assisted decisions
- Fraud Prevention in Digital Grantmaking -- how due diligence fits into broader fraud risk management
Last updated: 21 February 2026. To see how Plinth's automated due diligence works with your programmes, book a demo or contact our team.