About Paul Curwell

I help businesses protect their Intellectual Property (IP), revenue and product from fraud and security threats. My content provides clear steps to protect your Trade Secrets, attract investors, and accelerate business growth from startup to commercialisation using my RTP Playbook.

How to Enhance Detection with Comparative Case Analysis

Posted on September 30, 2025 by Paul Curwell

Paul Curwell

5–7 minutes

3 Key Takeaways

Comparative Case Analysis (CCA) isn’t just theory — it’s a practical method to connect the dots between trade secrets theft, fraud, insider threats, and supply chain abuse.
You don’t need a huge internal dataset — competitor incidents and cross-industry cases provide the patterns and behaviours you need to build robust typologies.
CCA creates tangible business value — done properly, it turns messy case data into insights that protect revenue, IP, and operational continuity, making you look good to management and investors.

What is Comparative Case Analysis?

Most companies already have clues sitting in plain sight — case files, legal documents, media reports, competitor incidents, industry analyses. But they rarely connect the dots. If you don’t connect the dots, you can’t detect threats early, which means losses escalate, your IP gets compromised, and supply chain integrity suffers before anyone even notices.

Comparative Case Analysis (CCA) fixes this. It might not show up in glamorous keynote speeches, but it gives you practical leverage: more accurate detection, fewer false alarms, and stronger business protection. If revenue protection, IP protection, and supply chain integrity matter to you (spoiler: they should), then this is your toolkit.

Comparative Case Analysis means taking several instances of risk events (fraud, IP theft, insider threat, etc.), comparing them systematically, extracting patterns, signatures, and behaviours, then using those insights to write typologies which are used to build detection mechanisms. It’s the bridge between one-off incidents and repeatable defence.

Even if your organisation is small, you can pull from competitors or other industries — because threats are surprisingly consistent.

Why Comparative Case Analysis Matters for Business

When you get CCA right, two big things happen:

Earlier detection – You start recognizing threats before they inflict material damage.
Higher accuracy & efficiency – You reduce false positives and false negatives, which means fewer wasted resources and more trust in your detection systems.

That opens the door to greater automation and AI usage. If you understand which threats matter and how they appear in your data, you can lean more on rules engines, models, or anomaly detection — meaning you don’t need huge analyst teams fire‑fighting all day.

The business value isn’t theoretical: avoided losses, protected IP, preserved revenue, fewer disruptions in your supply chain. Plus, when management or investors ask, you’ll have solid proof you’re not just “winging it.”

We often overlook criminology when combating insider threats, fraud and sabotage

The Comparative Case Analysis Value Chain

Here’s the refined flow I use (and teach):

Threats → Risk Events (cases) → CCA (comparison) → Typologies (including patterns, signatures, behaviours) → Detection = Business Value

If any link is weak, the value drops. If all are strong, you build a resilient, measurable defence.

How to Actually Do It (Step‑by‑Step)

Here’s the practical method I use. If you follow this, CCA becomes repeatable, grounded, and useful:

Define your scope
Decide which type(s) of threats matter most to you: IP theft, insider risk, supply chain fraud, etc. Also decide down to the industry, product, or technology level.
Collect cases
Pull from internal cases (incidents, near misses), competitor incidents, public legal filings, academia, and media. If you don’t have five useful internal examples, don’t worry — competitor- or cross‑industry cases are totally valid.
Standardise the data
For each case, capture things like: who, what, when, how, impact, what failed controls, what signatures/behaviours were present.
Compare systematically
Lay out your cases side by side. Look for recurring behaviours, misused access, insider‑outsider collusion, process failures. Don’t assume everything is causal — test what appears consistently.
Extract typologies
From those recurring behaviours/patterns, build your typologies: the defined set of patterns, signatures and behaviours that will become your detection requirements.
Validate & test
Apply typologies to fresh data or unseen cases. Measure whether you catch real threats and don’t swamp people with false positives. Refine aggressively.
Monitor performance
Track detection speed, false positives/negatives, cost of investigation vs. savings, and measurable risk reduction. If you’re not seeing clear value, revisit your typologies.
Peer review
Get someone not involved in your collection or initial comparison to critique: did you miss patterns? Are your assumptions reasonable?
Evaluate reliability
Are your detection rules trustworthy enough to rely on with minimal oversight? If not, iterate.
Refresh regularly
Threats evolve. You should revisit your typologies and the chain every year (or more often in fast‑moving tech sectors) to stay relevant.

“Typologies” Sound Boring – But They Could Save Your Business Millions

Real Case Examples to Learn From

Comparative Case Analysis might not win design awards, but it wins business protection. It turns messy case files into sharp detection requirements. Do it right, and you get fewer losses, protected IP, stable revenue, and less headache from the security/fraud team. For example:

Trade Secret Theft in Medtech: A departing engineer at a medical device company copied proprietary 3D printing designs for a new implant. The designs appeared at a competitor two months later. Compare the methods used to extract the IP, the timing, and which controls failed — then ask yourself: could this happen in your organisation?
Supply Chain Fraud in Electronics: Danish authorities recently discovered unlisted components in circuit boards purchased from overseas, intended for use in green energy infrastructure. The parts could have been exploited to sabotage operations in the future. Compare the tactics and controls in place — quality checks, supplier audits, component verification — and assess whether your supply chain could be similarly vulnerable.
Insider Threat in Critical Infrastructure: A disgruntled employee at a water utility sabotaged Operational Technology at pumping stations so they would fail five days after he left the business. Compare the patterns and tactics used, as well as which controls worked or failed. Then use this to assess your own business: could this happen to you?

These examples demonstrate that threats are not isolated incidents but part of broader patterns that can be identified and mitigated through CCA.

Call to Action

If you’re a risk or compliance leader whose business is exposed to these sorts of threats, you need to ask whether your team is conducting Comparative Case Analysis as part of continuous improvement. Are you systematically comparing incidents to identify patterns? Are you using these insights to write typologies that inform your detection mechanisms? If not, it’s time to start.

The $25 Billion Question: How Much Are You Losing to Warranty Fraud?

Posted on September 9, 2025 by Paul Curwell

Paul Curwell

6–8 minutes

3 Key Takeaways

Warranty fraud is revenue leakage in disguise — costing manufacturers up to $25 billion a year and eating into reserves you thought were safe.
It’s not just customers gaming the system — insiders, dealers, and service providers are often behind the biggest schemes.
You can fight back — with the right contracts, transaction controls, analytics, and service network oversight, you can plug the leaks.

Introduction

A few weeks ago, I wrote about how medtech companies are bleeding millions to revenue leakage in their supply chains. Warranty fraud is another part of that same story — a silent killer of margins that rarely makes it to the executive risk register.

Here’s the uncomfortable truth: the best available global estimates of warranty fraud losses come from studies conducted between 2009 and 2015. That’s right, we’re still relying on decade-old numbers because the industry hasn’t invested in updating them. But the losses — then pegged at around 3% to 10% of total warranty expenses, or roughly $25 billion annually — haven’t magically gone away. If anything, the growth of digital service networks and globalised supply chains has probably made the problem worse.

Executives don’t need another abstract fraud risk to worry about. You need to know how this eats into your bottom line, distorts your financial planning, and ultimately undermines your ability to commercialise new technology. So let’s get practical.

MedTech Companies Are Losing Millions to Revenue Leakage Without Knowing It

The Cost of Warranty Fraud

Warranty fraud is not a rounding error — it’s a profit killer. Surveys by AGMA Global and PwC suggest that warranty and service abuse lead to 3% to 5% revenue losses for manufacturers.

In the U.S. alone, dealer and service provider fraud cost about $2.6 billion in 2018.
Automotive and electronics manufacturers typically spend 2.5% to 2.7% of product revenue on warranty claims. A chunk of that is pure fraud.
Some industries report warranty fraud accounting for up to 15% of total warranty costs.

That’s money straight out of your cash flow. And because fraudulent claims push warranty expenses beyond accrued reserves, the impact doesn’t just hurt margins — it hits your balance sheet, profitability, and valuation.

If you’re courting investors or pushing for commercialisation, warranty fraud doesn’t just look like sloppy operations. It looks like you don’t have control of your supply chain or insider threat risks.

man soldering a circuit board in an electronics warranty service centre — Photo by Quang Nguyen Vinh on Pexels.com

How Fraud Affects Manufacturer Warranty Claim Forecasts

Most manufacturers do their homework when it comes to warranty reserves. Forecasts are based on historical failure rates, reliability data, and statistical modelling. On average:

Companies set aside around 1.4% of product sales revenue to cover warranty claims.
Costs range anywhere from 0.5% to 5%, depending on industry and product complexity.
Automotive and electronics firms typically accrue closer to 2.5% of sales.

This would all work fine — if the claims data reflected reality. Fraud blows a hole in that logic. Fictitious or inflated claims distort the numbers, meaning your forecasts are wrong, your reserves are short, and your cash flow suffers.

For executives, that means warranty fraud is not just a line-item expense. It’s a forecasting and planning risk — the kind of risk that makes boards twitchy and investors cautious. So lets take a look at how it happens.

How Does Warranty Fraud Occur?

Here’s where it gets messy. Warranty fraud is not one type of scam, it’s a whole ecosystem. And unlike other types of fraud, the biggest offenders often sit inside your own supply chain or service networks.

A. Customer Fraud

False claims for non-existent failures.
Misuse or deliberate damage disguised as product defects.
Counterfeit receipts or altered purchase details.

Case Study A – Automotive OEM Dealer Fraud:
Dealers manipulated mileage reporting and double-charged customers and manufacturers for the same repairs. Fraudulent warranty claims stacked up until analytics flagged the anomalies.

B. Dealer and Service Agent Fraud (Insider Threats)

Charging both the customer and the manufacturer for the same repair (classic double-dipping).
Manipulating mileage or usage data to extend warranty coverage.
Repeatedly claiming for the same “repair” months later.

Case Study B – Computer Technology Provider:
One company estimated losing $100 million annually to warranty fraud by service providers. After implementing data-driven fraud detection, they uncovered $11 million in fraud in nine months and saved $67 million over five years.

C. EmployeeS (Insider Threats)

Approving false claims for friends, family, or colluding dealers.
Tampering with data to inflate invoices.
Steering warranty work to preferred suppliers for kickbacks.

Case Study C – Electronics Manufacturer in Australia:
Fined for misleading consumers about their warranty rights — proof that warranty issues don’t just hurt margins, they also create reputational and legal risk.

D. Warranty Provider and Administrator Fraud

Overselling coverage or denying valid claims.
Colluding with dealers or service providers to share the spoils.

Case Study D – Multi-national Manufacturer’s Pan-European Warranty Fraud Detection:
A multi-national manufacturer’s after-sales assessment revealed inconsistent warranty costs across countries attributable to service agent fraud. Fraud detection analytics quickly uncovered extensive abuse despite initial management skepticism, which was then extended to other regions like Asia, revealing similar fraudulent practices involving colluding employees and service agents.

As you can see from this warranty fraud taxonomy and these case studies, these aren’t edge cases. They’re mainstream manufacturers dealing with systemic fraud inside their own networks.

The Hidden Threat to Your Bottom Line: How Sales Fraud is Bleeding Your Business Dry

4. How Should Manufacturers Protect Their Revenue From Warranty Fraud?

The good news? You don’t have to accept warranty fraud as a cost of doing business. A comprehensive control framework works when it’s implemented with intent.

a. Contracts

Clear, standardised terms that define coverage and service entitlements. Include audit rights and anti-fraud clauses to keep dealers and providers honest.

B. Transaction Controls

Validate customer entitlement and claim legitimacy every time. Automate material returns control. Layer in analytical scoring so high-risk claims get flagged early.

C. Analytics

This is where the magic happens. Combine business rules, anomaly detection, predictive models, and even social network analysis to spot patterns of collusion. Fraudsters aren’t random — their footprints are there if you look.

D. Service Network Management

Benchmark your dealers, agents, and providers. Use performance dashboards, mystery shopping, and audits to keep them accountable. Service networks are fertile ground for fraud — manage them like the strategic assets (and risks) they are.

red stop sign highlighting that it is possible to prevent and detect revenue leakage through warranty fraud and abuse. — Photo by Pixabay on Pexels.com

Conclusion: Stop the Silent Margin Killer

Warranty fraud is more than an operational headache — it’s a direct attack on your revenue, your forecasts, and ultimately your valuation. If you wouldn’t tolerate a 5% revenue leak from your supply chain, why are you tolerating it from warranty fraud?

As executives in manufacturing and medtech, you have two choices:

Treat warranty fraud as an unavoidable cost and keep bleeding margins.
Or treat it as a strategic risk — implement controls, demand analytics, and take back control of your revenue.

Personally, I know which choice makes your next board meeting easier.

Ransomware Attacks on R&D Companies Explained

Posted on September 2, 2025 by Paul Curwell

Paul Curwell

5–8 minutes

3 Key Takeaways:

Ransomware has professionalised: today’s gangs follow an 8-step targeting cycle that looks more like a military operation than a cybercrime.
R&D-intensive companies are prime targets because weak data governance creates exploitable security gaps — and attackers know your research is the fastest route to a big payday.
The financial impact goes far beyond ransom payments — share prices fall, investors back away, and patents can be undermined.

The impact on your business

Ransomware is the digital version of kidnapping. Attackers break into your systems, lock up your data, and demand payment for its release. But unlike old-school kidnappers, they don’t just keep the hostage — they copy it too. For R&D-heavy companies, that hostage is your research pipeline: your trade secrets, trial data, and commercialisation plans.

And here’s the part too many boards miss: the ransom is only the start of the damage.

Share price impact: Public disclosures of ransomware routinely knock 3–5% off market cap. One company’s 2023 breach wiped millions in value overnight.
Investor attraction: If you can’t prove your research data is safe, investors won’t touch you. Due diligence now treats ransomware resilience like another line in your balance sheet.
Time-to-market delays: Every month of R&D delay costs millions in burn and kills first-mover advantage. In pharma, a six-month delay can add $3–6M to costs.
Commercialisation risk: Stolen formulas and trial data can create “prior art” that undermines your patents. Translation: your billion-dollar IP is now legally copyable.

Ransomware isn’t just an IT outage — it’s a strategic risk to valuation, market entry, and investor confidence.

49% of Private Equity deals fail because of undisclosed data breaches

Why R&D-intensive companies are vulnerable

Think of your R&D program as a fragile supply chain. Every stage — discovery, trials, data integrity, and commercialisation — depends on governance and control. When ransomware strikes, the weak links show.

Here’s an uncomfortable truth: in R&D intensive businesses, many ransomware vulnerabilities come not from exotic zero-day cyber exploits but from poor data governance, which flows through to your information security posture. Data governance is not a “tech” term — it’s a board-level responsibility. When governance fails, attackers thrive:

Unclear ownership and access: If no one owns the data, no one protects it. Attackers love overexposed research folders and outdated VPN access.
Failed backups: Governance blind spots mean backups aren’t tested — so the first time you discover they don’t work is during an attack.
Misapplied controls: Without proper data classification, security teams guard low-value data while leaving crown jewels exposed.
Regulatory exposure: Weak governance makes GDPR, HIPAA, or ISO non-compliance almost inevitable — and regulators don’t accept “we were hacked” as an excuse.
Slow detection: Without adequate security monitoring, attackers can sit inside your network for weeks undetected, rehearsing their attack.

Poor governance contributes to a perfect operating environment for ransomware groups. And in R&D-heavy sectors, that means your valuation is basically gift-wrapped for attackers.

governance is key to protecting your data, data integrity, and implementing fit for purpose security protocols to guard against ransomware.

The professionalisation of ransomware in 2025: the 8-step targeting cycle

Forget the old “spray and pray” model where attackers blasted out phishing emails and hoped someone clicked. That was cybercrime’s stone age, and focused on everyone and everything rather than being highly sophisticated, targeted, and selective.

Today’s ransomware gangs are professionals. They behave like organised crime syndicates, following a structured 8-step targeting cycle designed to maximise pressure and payouts:

Target Selection – Industries where data equals enterprise value, such as pharma, biotech, semiconductors, medtech, and advanced manufacturing.
Initial Surveillance – Public sources, leaked credentials, and open servers help attackers map your weak spots.
Final Target Selection – They zoom in on firms with high-value IP, fragile governance, and patchy defences.
Pre-attack Surveillance – Once inside, they quietly watch. Mapping networks, spotting backup systems, and studying user behaviours.
Planning – With insider-level intel, attackers script their playbook for maximum damage and leverage.
Rehearsal – Yes, they practice. In test environments, they run through encryption and data theft to ensure nothing goes wrong on game day.
Execution – Systems are locked, IP is exfiltrated, ransom notes drop. Victims are blindsided; attackers are already two steps ahead.
Escape & Evasion – Logs are wiped, trails covered, backdoors left behind for future profit.

Paul Curwell's 8-step targeting cycle for organised crime

This is not opportunistic crime conducted by pimply teenagers. It’s deliberate, researched, and ruthlessly commercial — closer to an IPO roadshow than a smash-and-grab.

Case studies: when ransomware hit the labs

Perhaps your one of the many people I talk to at industry events who’s sick of hearing about security. Well, if you need further convincing on the importance of this topic here are 5 real-world examples that show how professionalised ransomware plays out:

Company	Attacker Group	Success Factors	Business Impact	IP/Patent Risk
Company A (India, 2023)	ALPHV / BlackCat	Compromised VPNs & stolen credentials, extensive pre-attack surveillance.	17TB of data stolen, 3–5% share price drop, $50–62M revenue hit, $3M+ recovery costs.	Risk of patent invalidation if leaked as prior art.
Company B (Japan, 2023)	Unnamed (likely RaaS affiliate)	Supply chain intrusion, privileged access exploitation.	Multi-week disruption of R&D and manufacturing, investor concern.	Possible exposure of neuroscience research.
Company C (India, 2020)	Unnamed criminal ransomware group	Phishing & credential theft during COVID-19 trials.	4% share price drop, 2-week trial delays, $150k–$250k added burn per project.	Trial data exposure undermines exclusivity.
Company D (Germany, 2023)	Unnamed RaaS affiliates with APT links	Exploited enterprise / cloud vulnerabilities, targeted R&D repositories.	Attack contained quickly, limiting share price impact.	Potential R&D data exposure, though managed.
Company E (UK, 2024/25)	Qilin	VPN / firewall exploits (CVE-2024-21762), targeted NHS-critical systems.	£32.7M loss (~$41M), weeks of disruption, ransom ~$50M.	Diagnostic IP exposed, R&D collaborations disrupted.

The costs of an IP breach

Conclusion: the strategic picture

The uncomfortable truth: ransomware groups have professionalised faster than most boardrooms have adapted. They’re running playbooks that look like government intelligence operations, and they’re aiming squarely at industries where research is the business to make sure you’re highly incentivised to pay up.

If you’re in an R&D-intensive sector, you’re not just another target — you’re the main course. Weak governance, patchy security, and misplaced confidence in cyber insurance won’t save you.

So, next time someone in the boardroom calls ransomware an “IT problem,” remind them it’s actually a governance problem. Because in 2025, the attackers aren’t amateurs anymore — and if your business wants to survive your response can’t be either.

MedTech Companies Are Losing Millions to Revenue Leakage Without Knowing It

Posted on July 29, 2025 by Paul Curwell

Paul Curwell

6–8 minutes

3 Key Takeaways

MedTech companies lose 5-7% of gross revenue to fraud, supply chain leakage, and contract failures—most executives don’t even know it’s happening
Your supply chain integrity is under attack from unauthorised discounting, billing fraud, and channel partners who bend the rules
Revenue protection isn’t a back-office problem—it’s a strategic risk that directly impacts your bottom line and company valuation

You’re Bleeding Money and Don’t Even Know It

Here’s a sobering thought: while you’re obsessing over R&D budgets and production efficiency, your company is probably hemorrhaging 5-7% of gross revenue through fraud and supply chain leakage. That’s not a typo—it’s reality.

I discovered this harsh truth during recent work in the MedTech sector. Frankly, I was shocked. Through discussions with colleagues and clients about these estimates, I realised many executives either don’t recognise this problem or dramatically underestimate its impact.

Consider this: if your company generates $100 million annually, you’re potentially losing $5-7 million to preventable leakage.

That’s serious money—money that should be flowing straight to your bottom line instead of disappearing into the supply chain black hole.

The Billion-Dollar Problem Nobody Talks About

Revenue leakage in healthcare equipment and medical device manufacturing isn’t some theoretical concern. Industry data shows pharmaceutical companies collectively lose over $15 billion annually from rebate abuse and chargeback errors alone. Medical device companies face identical risks with even less protection.

The gross-to-net gap—the difference between what you bill and what you actually receive—reached $236 billion across healthcare in 2021. While pharma companies were forced by regulation to build revenue controls, medical device and diagnostic equipment manufacturers are still catching up, despite facing identical complexity.

Here’s why this matters to your bottom line: unlike other business costs, revenue leakage is almost entirely preventable. Every dollar you recover from leakage flows directly to profit. No additional manufacturing costs, no new R&D investment—pure margin improvement.

Where Your Money Disappears: The Top Leakage Points

Revenue vanishes at multiple stages throughout your operation. Understanding these vulnerabilities helps you plug the holes:

Manufacturing & Procurement Losses

Quality failures: Rejects and recalls from substandard components can trigger millions in losses
Supply chain fraud: Counterfeit parts compromise your supply chain integrity while creating warranty claims
Contract mismanagement: Poor supplier agreements allow pricing discrepancies to compound over time

Just last week, I heard a podcast about MedTech product packaging for air transport. The extreme temperature swings in aircraft cargo holds—from scorching tarmacs to sub-zero altitudes—can destroy highly calibrated diagnostic equipment. These “invisible” logistics failures create expensive writeoffs that directly impact revenue.

Channel stuffing fraud – a distribution problem

Distribution & Channel Partner Issues

Unauthorised discounting: Partners who exceed agreed discount limits without approval
Product diversion: Legitimate products sold outside authorised territories or channels
Contract violations: Distributors who bend pricing rules or ignore territorial restrictions
Billing errors: Complex pricing structures create opportunities for mistakes that favor customers

Product Diversion in the Healthcare Supply Chain: What’s the Problem and How Big Is It?

Sales & Service Revenue Gaps

The complexity of healthcare equipment pricing creates multiple leakage points:

Revenue Stream	Common Leakage Points
Equipment Sales	Unauthorised discounts, pricing errors
Service Contracts	Underpriced renewals, forgotten billing
Software Licenses	Unauthorised usage, poor compliance tracking
Diagnostic Consumables	Volume discrepancies, rebate abuse
Training Services	Unbilled hours, contract scope creep

The Hidden Threat to Your Bottom Line: How Sales Fraud is Bleeding Your Business Dry

MedTech is More Vulnerable Than Pharmaceuticals

Through my recent work, I’ve seen how medical device and diagnostic equipment companies face unique structural challenges that make revenue leakage worse:

Business Model Complexity: While pharma sells discrete products through standardised channels, MedTechs manage intricate bundles. A single “sale” might include equipment leasing, maintenance contracts, software licenses, training services, and ongoing consumables—each with different pricing structures and discount schedules.

Fragmented Distribution: MedTechs rely on more diverse partner networks than pharma companies. Specialised dealers, regional distributors, service providers, and system integrators all have custom contract terms and varying compliance capabilities.

Legacy Revenue Controls: The MedTech and diagnostic equipment sector has been slower to implement systematic revenue controls. While pharma companies invested heavily in rebate management and contract compliance systems under regulatory pressure, many healthcare equipment manufacturers still operate with outdated processes.

This complexity creates opportunities for revenue to slip through cracks that pharma companies sealed years ago.

Building Your Revenue Defense System

Protecting revenue requires systematic action across multiple areas. Here’s what works:

1. Implement Real-Time Monitoring

Install automated systems that flag unusual discount patterns
Set up alerts for pricing exceptions that exceed thresholds
Monitor partner sales data for territorial violations or volume discrepancies
Track service contract renewals to prevent revenue gaps

2. Strengthen Contract Controls

Automate discount approvals with clear escalation paths
Build dynamic pricing systems that adjust for market changes
Create partner scorecards that track compliance metrics
Implement regular contract audits beyond just financial reviews

3. Enhance Supply Chain Integrity

Deploy serialisation and track-and-trace technologies
Validate partner credentials and monitor their performance
Create digital twins that link physical inventory to service claims
Establish rapid response protocols for integrity breaches

4. Data-Driven Partnership Management

Cross-reference sales transactions, service logs, and rebate submissions
Use analytics to identify patterns that indicate fraud or process failures
Reward partners for validated outcomes, not just volume metrics
Conduct operational audits that assess pricing integrity and territorial compliance

Product Serialisation – a tool to help counter diversion and illicit trade

The Board-Level Questions You Need to Ask

Revenue protection belongs on your executive agenda. Start asking these questions:

What’s our independently verified leakage rate?
Can we trace our products through their entire lifecycle?
Do we have complete visibility over channel partner behavior?
Who specifically owns revenue protection accountability?
Are we prepared for regulatory scrutiny on supply chain integrity?

If you can’t answer these questions clearly, that’s where your risk lives.

Your Next Steps: Stop the Bleeding

Revenue leakage is fixable. Companies that address it proactively enjoy stronger margins, reduced risk exposure, and better competitive positioning.

Start with these immediate actions:

Week 1: Audit your last quarter’s discount exceptions and pricing variances. Calculate the financial impact of irregular patterns.

Month 1: Implement automated alerts for pricing exceptions that exceed your predetermined thresholds. Review partner compliance with territorial and discount agreements.

Quarter 1: Deploy analytics tools that cross-reference sales data, service logs, and rebate submissions to identify anomalies.

Year 1: Build comprehensive revenue protection systems with real-time monitoring, automated controls, and regular partner audits.

The companies moving first will capture disproportionate advantages while competitors struggle with eroded margins. In an industry where innovation drives growth but operational excellence determines profitability, revenue protection has become a competitive necessity.

Your money is disappearing right now. The question is: what are you going to do about it?

Ready to plug the revenue leaks in your organisation? Start by conducting a comprehensive revenue audit to identify your biggest vulnerability areas. The sooner you act, the sooner you’ll see those lost millions flowing back to your bottom line.

Why Your Brightest Minds Are Clicking on Deepfakes: The Hidden Business Cost of Phishing in Science & Tech SMBs

Posted on July 22, 2025 by Paul Curwell

Paul Curwell

7–10 minutes

Key Points

Phishing is smarter now—AI-generated, multi-channel, phishing and social engineering schemes are targeting your most trusted staff.
If you don’t own your cloud security, someone else will—probably a criminal.
Breach costs in biotech, medtech, and high-tech are among the fastest-growing, averaging $4.9M.

“We Thought We Were Too Small to Be Targeted”

If I had a dollar for every science or tech founder who told me their company was “too small to be on anyone’s radar,” I’d have my own R&D fund.

Let me be clear: attackers don’t care about your size—they care about your value. IYou’re holding proprietary data, research, or trade secrets, so you’re a target. Most science and technology businesses rely on cloud services and don’t have a full-time security team, making you vulnerable.

The methods used to breach billion-dollar multinationals are now faster, cheaper, and powered by AI. This article outlines the threat and provide tips on how to stop your business from being compromised with one fake Slack message, QR code, or deepfake video call.

The Phishing Shift: Multi-Channel, Deepfake, and Voice Fraud Are the New Norm

Phishing has evolved. It’s no longer about shady emails from fake banks. Today’s attacks are:

AI-enhanced: Customised lures generated instantly using your public data.
Multi-channel: 41% of phishing attacks now include SMS, WhatsApp, Teams, Slack, or LinkedIn, not just email. [[Verizon DBIR 2025]]
Visual and audio deepfakes: CEO voice clones. Fake investor video calls. Deepfake “compliance officers” asking for document uploads.
QR code phishing (quishing): Seen a QR code on a conference booth or flyer? It could trigger malware or credential theft. These attacks have jumped 2,000% since 2023. [Proofpoint]

This means your smartest, most senior, and most trusted employees—research leads, engineers, finance managers—are now your most likely targets.

And when they click? The attackers don’t just steal credentials—they steal access to your intellectual property, your commercialisation roadmap, your partner data.

Business Email Compromise – persistent threat or consistently mismanaged?

What’s Really at Risk? IP, Trust, and your Entire Business Model

According to the IBM Cost of a Data Breach Report (2024), the average breach in the biotech and medical devices sectors now costs $4.9M, driven by:

Lost IP and R&D delays
Regulatory investigation
Supply chain fallout
Loss of investor confidence

And let’s be blunt: in your world, IP is the value. If that gets leaked, copied, or ransomed, your growth narrative evaporates. Here’s how the damage cascades across your business:

Function	Impact
Strategy	Stolen trade secrets = lost first-mover advantage
Investment	Investors now screen for cloud security and IP protection readiness
Finance	Costs spike with downtime, legal, incident response, and insurance gaps
Operations	Phishing often leads to ransomware disrupting production or trials
Marketing	A leak of your roadmap = blown launch, brand damage, loss of trust

AI for Deeptech Startups: Balancing Speed and Security

Real Example: The Deepfake COO That Killed a Fundraise

A medtech startup was gearing up for their Series B. One of their engineers received a message on Slack from “their COO” requesting trial data to be uploaded to a new shared folder for investor review. It was convincing—same profile picture, same tone, same urgency.

Except it wasn’t their COO.

The link was spoofed. The data was stolen. Within weeks, unpublished clinical research appeared online. The raise was postponed. A competitor filed a patent within six months.

This was not a technical failure—it was a business failure rooted in poor security awareness and access control.

The Cloud Trap: “We Use Microsoft/AWS, So We’re Covered” (No, You’re Not)

There’s a dangerous myth in science and tech startups:

“We’re on Azure or AWS, so we’re secure.”
Wrong.

Cloud providers like Microsoft and Amazon only protect the infrastructure. Everything else—your apps, identities, access controls, data classification, and monitoring—is your responsibility.

Who Secures What in the Cloud?

You Secure	Provider Secures
IP, data, applications	Physical data centres
User identities, MFA	Infrastructure uptime
SaaS app permissions	Network hardware
Monitoring & alerts	Hypervisor patching
Segmentation, backups	Base platform security

Cloud platforms call this the Shared Responsibility Model, and it’s not optional. If you’re not configuring and monitoring your cloud assets regularly, you’re driving blind.

Security Awareness Training: The Key to Protecting Life Sciences from IP Threats

So What Do You Actually Do? Here’s a Business-Ready Plan

You don’t need a CISO or a 10-person security team. But you do need a plan that works for a cloud-first, IP-heavy business. Here’s mine.

1. Use the Cloud Security Tools You Already Own

You’re probably already paying for enterprise-grade security features. Turn them on.

On Microsoft Azure:

Defender for Cloud: Detect misconfigurations, malware, and risky settings.
Sentinel: Security analytics and threat detection.
DLP & Microsoft Purview: Prevent IP and research leaks across Teams, SharePoint, and email.
Defender for Cloud Apps: Track SaaS sprawl and OAuth risks.

On AWS:

GuardDuty: Real-time threat detection and alerts.
Security Hub: Centralised risk view across AWS services.
IAM + KMS: Fine-grained access control and encryption key management.
Connected App Reviews: Audit OAuth and API app integrations.

Set alerts. Monitor changes. Review configurations monthly.

2. Lock Down Identity, Access, and Data

MFA Everywhere: No exceptions, no delays.
Least Privilege: Don’t give admin rights unless absolutely necessary.
Credential Hygiene: Rotate secrets; store them in Key Vault (Azure) or Secrets Manager (AWS).
Segment R&D Environments: Separate IP-heavy workloads from finance, HR, and business ops.
Encrypt Everything: In transit and at rest. Use customer-managed keys for sensitive data.

3. Train for the Threats of 2025

Phishing isn’t just email anymore. Your staff need to be trained for:

Quishing: Fake QR codes that install malware or lead to credential harvesters.
Vishing: Calls from deepfaked executives or suppliers.
Fake video calls: Deepfakes of board members or partners requesting documents.
Business email compromise: Fake invoices, altered payment instructions.

Simulate these scenarios monthly. Keep it realistic. And build a no-blame reporting culture—you want incidents surfaced fast.

**4. Prepare for the Breach—Because It Will Happen**

Automate Cross-Region Backups: Especially for research data and regulatory submissions.
Test Disaster Recovery Quarterly: Restoring is not plug-and-play. Practice like it’s game day.
Keep R&D Snapshots Offline: Isolated storage can prevent ransomware spread and data loss.

Your IP is irreplaceable. Treat it like crown jewels, not just another folder.

5. Audit Your SaaS and Supply Chain Access

Third-party apps and vendors are often your weakest link.

Review OAuth and app permissions quarterly
On Azure, use Defender for Cloud Apps to flag unused or risky apps.
On AWS, use the Connected App list to track what’s talking to your data.
Add security clauses into vendor contracts: include breach notifications, minimum controls, and audit rights.

And always ask: Do they need access to that data? If not, revoke it.

6. Give the C-Suite Metrics That Matter

Executives focus on risk, cost, and reputation. Produce a monthly cloud security dashboard to track business-relevant metrics and identify where you need to improve:

% of staff with MFA enabled
DLP events involving research/IP
Number of connected third-party apps
Training completion rates
Number of critical misconfigurations or policy violations

Tie these to business outcomes: funding readiness, compliance status, and operational continuity.

Biotech and MedTech Investors Are Demanding Security and Resilience: Are You Ready?

Final Thoughts: Security Is Commercialisation

If you’re in science and tech, your ability to protect your research and data is part of your business model.

This isn’t paranoia, it’s about staying competitive. You are competitive when you secure your IP, prove control over your cloud environment, and train your team to spot social engineering, you don’t just reduce risk—you build credibility with investors, partners, and customers.

So let’s recap. Here are 6 actions you can take now to avoid becoming a victim of the next phishing or social engineering scheme:

Enable MFA on every account—human and machine.
Audit your Azure or AWS environment with Security Hub or Defender.
Run a phishing simulation that includes voice, SMS, and video threats.
Review all third-party apps and OAuth permissions.
Test your disaster recovery plan.
Start tracking metrics for the boardroom.

If you need help setting this up—or just want a quick review—I’ve worked with enough S&T startups and growth-stage firms to know what’s worth your time.

You don’t need to be unbreakable. You just need to be prepared.

And in a world of AI-enhanced fraud, that’s your real competitive edge.

Biotech and MedTech Investors Are Demanding Security and Resilience: Are You Ready?

Posted on July 15, 2025 by Paul Curwell

Paul Curwell

7–10 minutes

3 Key Takeaways

Your IP is your goldmine – For most biotech and medtech companies, intellectual property (IP) is the primary asset—often making up most of the enterprise value. Competitors, cybercriminals, and nation-state actors are targeting these assets, even in early stages.
The “security later” myth is costing you deals – Investors are increasingly seeing weak security as a deal-breaker during due diligence. Regulatory failures can cost millions to remediate.
Resilience now rivals innovation – Investors increasingly allocate capital to companies that can demonstrate not just breakthrough science, but also the security, integrity, and resilience to protect it.

Security Is a Business Decision—Not a Technical One

Security decisions often get framed as technical, complex, or something to worry about later. That mindset is dangerous—especially in life sciences, where what you don’t protect can cost you your next round, your IP rights, or your company’s future.

In reality, early-stage biotechs and medtechs face three unavoidable truths:

Your intellectual property is the business — and likely the only real asset you own.
You’re already a target — from competitors, cybercriminals, and even foreign intelligence services.
Investors are watching — and asking questions you must be ready to answer.

The risk environment has shifted. Today’s adversaries aren’t just hackers in basements. They include:

Ransomware gangs targeting IP-rich companies for extortion
Foreign actors stealing trade secrets to boost their own biotech industries through espionage and foreign interference
Contract partners and employees who, as insider risks, might mishandle, steal, or deliberately leak sensitive information

You may not stop every threat—but you can become a harder target. And that makes you a safer bet for investors.

Security Creates Value—and Investors Know It

Here’s what most founders miss: Security doesn’t just protect value. It creates it.

Early-stage companies that build in basic controls gain:

Faster fundraising – Clear controls speed due diligence.
Smoother partnerships – Big pharma won’t risk IP leaks from weak links.
Fewer regulatory delays – Secure-by-design systems reduce audit findings.

It’s not about locking everything down—it’s about stage-appropriate controls that prove you can grow responsibly.

Surveys show over 70% of life science investors now flag data integrity and IP protection as top decision factors. That’s because the risk is real: trade secret theft costs the global economy more than $1 trillion annually, and life sciences firms are prime targets.

Nation-state actors, insider risks, and ransomware gangs are no longer fringe concerns—they’re active threats. This isn’t hypothetical. It’s a competitive filter—and investors are paying attention.

The 3 SMB Risk Management frameworks you need to protect your business

When IP Protection Becomes a Business Valuation Driver

From my experience helping companies navigate security challenges, there are four critical stages where security transforms from “nice to have” to “deal or no deal.”

A. Discovery Stage:

Many founders assume they’re “too early” for security. In reality, premature public disclosure or leaks can destroy patent eligibility and future value.

Case Study: A European gene therapy startup lost patent protection after a postdoc shared results at a conference before filing. The resulting “prior art” invalidated their core IP, forcing an 18-month delay and a complete pivot.

Whilst many medtechs and biotechs fail at this conceptual hurdle, they still have valuable information and data assets with some residual value. A resonable investor might ask “How do you prevent premature disclosure of trade secrets? What’s your invention disclosure process?”

5 Tips to manage information security risks during discovery:

Enable conditional access controls and sensitivity labels for IP documents using existing tools.
Implement NDAs for everyone, including advisors and part-time collaborators.
Create invention disclosure workflows to track who invented what, when.
Run brief security inductions focused on IP protection basics.
Most early-stage companies already pay for Microsoft 365 tools like Purview through their E5 subscription (or AWS, Google equivalents). These tools are designed to manage these risks, but they’re never turned on!

Microsoft Purview Information Protection – an overview

B. Prototyping Phase:

Outsourcing and collaboration introduce new risks. Without strong IP protection clauses and access controls, your designs and data can walk out the door. Here are two examples:

Case Study 1: A Boston medtech company discovered a manufacturer had shared CAD files with competitors. Weak contracts and lack of controls cost them millions in lost advantage.

Case Study 2: A European medtech startup outsourced prototyping to an overseas partner. Within months, a similar device appeared in local patent filings. Weak contracts and open file sharing enabled the leak. Surveys indicate that over half of life science firms have experienced IP leakage during collaboration or outsourcing.

If your business is at this stage in the lifecycle, I think its perfectly reasonable that a potential investor might ask: “What IP protection clauses are in your supply chain contracts? How do you audit third-party access to sensitive data?”.

Tips to manage risks in outsourcing and prototyping

Here’s five simple actions you can do to manage your prototyping risk:

Upgrade vendor contracts with IP protection, confidentiality, and audit clauses.
Implement data loss prevention policies to prevent sensitive IP sharing via email or chat.
Use secure collaboration portals with controlled access.
Conduct regular access reviews for sensitive information.
Use a secure, timestamped invention disclosure log—this can be as simple as storing cryptographic hashes of documents with trusted timestamps to prove originality and timing.

Protecting Your R&D When Outsourcing Rapid Prototyping

C. Clinical Validation:

Data integrity and regulatory compliance become paramount. According to FDA enforcement summaries, a significant portion of warning letters cite documentation and data integrity deficiencies.

Case Study: One oncology trial faced a clinical hold after inspectors found inadequate data controls, costing $1.8 million in remediation and a 14-month delay.

As life science companies progress to clinical validation, regulatory scrutiny really steps up. Investors start asking tough questions like “Do you have FDA compliant data management systems? Can you demonstrate audit trail capabilities for trial data?”.

If you can’t satisfy a regulator, your commercialisation timeline might be set back by one to two years, and your additional cash burn could send you under.

Don’t wait until the last minute to factor in security – there’s a reason why the FDA and TGA adopted ‘secure by design’ principles.

Tips to manage security and integrity risks at the Clinical Stage:

Encrypt all clinical trial data using built-in cloud platform features.
Develop data integrity SOPs aligned with regulatory expectations.
Assess CRO security practices before signing contracts.
Prepare incident response plans for data breaches or integrity issues.

D. Scaling Phase:

At this stage, due diligence intensifies. Investors want proof you can scale—securely, not just scientifically.”

That means showing your approach to information security, data integrity, and resilience to recover from disruption or compromise is well thought out and consistently applied.

Case Study: A US-based biotech lost millions in valuation after a researcher emailed unpublished gene-editing data to a competitor before patent filings. The company lacked basic NDAs and data loss prevention controls. Industry studies suggest that premature disclosure or insider risks resulting in inadvertant publication are a leading cause of patent novelty disputes.

Potential investor questions:

“How do you manage privileged access to trade secrets and sensitive clinical data?”
“What happens if someone in your supply chain is compromised?”
“Can you detect and respond to insider threats before they damage your valuation?”

Scaling Stage Actions:

Formalize your security program with written policies and governance.
Implement privileged access management for sensitive IP and trial data.
Establish vendor risk assessment processes.
Provide regular employee security awareness training.

Actions Life Science SMBs Can Take to Reduce The High Cost of Licensing Fraud

What Investors Now Ask (And What You Need to Answer)

Today’s investors aren’t just evaluating your science—they’re evaluating your ability to protect it. Here’s what they want to know:

Are your information security controls appropriate for your risks?
Can you demonstrate good data integrity?
How do you protect global operations? What controls are in place for international CROs and suppliers?
Are you compliant with export controls?
How do you manage insider risk?
How do you protect your data and IP with contract manufacturers and research partners?

49% of Private Equity deals fail because of undisclosed data breaches

The Bottom Line: Security as a Strategic Advantage

In 2025, security isn’t just about prevention—it’s about acceleration. When you can show your IP is protected, your data integrity is sound, and your partners are secure, you’re demonstrating the kind of operational maturity that makes you investable.

Companies that invest in security early don’t just avoid disasters—they grow faster:

Faster fundraising: Mature security speeds up due diligence.
Higher valuations: Strong IP protection earns investor premiums.
Partnership acceleration: Pharma and CROs want secure collaborators.
Regulatory efficiency: Better data integrity, fewer delays.
Competitive edge: While others scramble to patch gaps, you’re moving forward.

In a world where cybercriminals, competitors, and foreign governments all want your IP, the question isn’t whether you can afford to invest in security—it’s whether you can afford not to.

References:

Deloitte, “2024 Global Life Sciences Outlook”
PwC, “Biotech and Pharma Investor Survey 2023”
FDA Warning Letters Database
World Intellectual Property Organization (WIPO) Reports
Office of the Director of National Intelligence, “Annual Threat Assessment 2024”
Ponemon Institute, “Cost of a Data Breach Report 2024”
Various industry case studies and market analyses

Actions Life Science SMBs Can Take to Reduce The High Cost of Licensing Fraud

Posted on July 8, 2025 by Paul Curwell

Paul Curwell

6–9 minutes

3 Key Takeaways

Missed royalties are more than rounding errors—for SMBs, they can cripple R&D and scare off investors.
Manual reporting is a fraud magnet—system-generated data (like from LIMS) is your best defence.
Licensing compliance isn’t legal fluff—it’s core to your commercialisation, valuation, and survival strategy.

If You’re Not Watching Your Licensees, Someone’s Losing—Probably You

Let’s cut to the chase: if you license your IP and aren’t enforcing data integrity for royalty calculations, you might as well be leaving cash in a petri dish and walking away.

In life sciences, diagnostics, and biotech, licensing isn’t just a business model—it is the business. Especially for small and mid-sized companies with 20 staff, a world-changing idea, and a bank account hanging on one cheque at a time.

As someone who’s spent years advising on IP protection, fraud, and insider threat strategies across research, life sciences, and tech, I’ve seen what happens when compliance becomes a handshake instead of a system.

Spoiler: it’s not pretty. Especially when your royalty stream turns into a trickle, and your investors start asking awkward questions.

Manual Reporting? Welcome to Fraud City

Here’s the dirty little secret of licensing in life sciences: most of the reporting isn’t automated.

Unlike software, where telemetry and keys enforce usage limits, biotech licensing often relies on spreadsheets, self-reports, and vague declarations of test counts or unit sales. It’s the business equivalent of trusting your teenager to “fill out the fuel log.”

When there’s money on the line, some licensees will game the system. Not all—but enough that you need to plan for it. Underreporting, omitted tests, unauthorized sublicensing, accident or intentional… it happens.

Now, to be clear: while there’s strong evidence that the pharmaceutical industry loses billions each year to IP theft, the scale of licensing fraud alone is harder to pin down. Licensing fraud is widely recognised in legal and business literature as a major risk – I’ve seen it myself – but precise loss values are rarely made public due to confidentiality and settlement agreements.

So while we can confidently say the combined losses from IP theft and licensing fraud are likely in the billions, the actual breakdown remains opaque. In short: there’s a lot of smoke, even if no one’s tallied the exact fire.

empty blood samples in a laboratory ready for diagnostic testing — Photo by Pavel Danilyuk on Pexels.com

Case Study: Royalty Pharma v. Boehringer Ingelheim

Still think this is just a theoretical risk? Let’s take a look at Royalty Pharma Collection Trust v. Boehringer Ingelheim GmbH—a real-world licensing dispute with millions on the line.

In this 2021 case before the English High Court, Royalty Pharma claimed that Boehringer had underpaid royalties by around €23 million under a license agreement for diabetes treatments containing linagliptin. The dispute turned on whether Boehringer owed royalties on all global sales of products manufactured in Germany—even when those products were sold in countries where the patent wasn’t in force.

The court sided with Royalty Pharma. It held that, under the amended contract terms, Boehringer was indeed required to pay royalties on all linagliptin products made in Germany—regardless of where they ended up. Why? Because that’s what the contract (arguably) said.

The case is a masterclass in why precision matters. It also shows how royalty disputes aren’t just abstract risks—they’re costly, complex, and reputationally messy. Unfortunately, they can also wreck relationships with your clients in what is often a limited market of buyers and sellers, so these matters need to be dealt with properly. And if a €23 million shortfall can happen between industry heavyweights, imagine the exposure for an SMB with less legal firepower and tighter margins.

Royalty-Pharma-Collection-Trust-v-Boehringer-Ingelheim-GmbH-1 Download

Why This Matters to Your Bottom Line

Licensing fraud and underreporting don’t just shave a few points off your revenue—they hit everything that matters:

R&D suffers: If you’re not collecting full royalties, you’re funding your innovation with Monopoly money. Sooner or later, it will dry up.
Valuation drops: Investors value predictable revenue. Fraud kills predictability. Disputes deter investors and raise questions about your business model and management team.
Operations stall: Underreporting can hide scaling problems or field-of-use breaches that sabotage your roadmap.

And in a sector staring down a $200+ billion patent cliff by 2030 (Gowling WLG, 2025), you can’t afford to guess where your money’s going.

The Simple Fix: Trust, But Verify

Here’s the good news: you don’t need to become a forensics lab to fix this. But you do need a few essentials baked into your licensing strategy:

Mandate system-generated reports. Ask for data from a LIMS or equivalent operational system. Don’t accept “manual summaries”—it’s like accepting a selfie as proof of tax compliance.
Build audit rights into licensing contracts. Spell out your right to inspect source data, not just reports. And include clauses that shift audit costs to the licensee if they’ve been underpaying.
Cross-check with public data. Use regulatory submissions, sales disclosures, or even market intelligence platforms to sanity check what you’re being told.
Include escalating remedies. Think late fees, interest, even the right to revoke exclusivity if terms are breached. It’s not petty—it’s protection.
Consider whether you want to be the bad guy. Sometimes it makes since to hire someone else to do licensing compliance on your behalf. That means they can ask the touqh questions, and allow you to sweep in to smooth over any misunderstanding with plausible deniability.
Use plain language contracts. If you need a lawyer to understand your royalty clause, you’re doing it wrong. Make the terms so clear even a VC can’t misunderstand them.

This Isn’t Legal Stuff—It’s Strategy

Still thinking licensing compliance is just something legal looks after?

Let me put it differently: enforcing licensing terms directly impacts strategy, cash flow, market positioning, and investor readiness.

A well-managed license with strong auditability and clean data boosts confidence, accelerates commercialisation, and supports IPO or acquisition discussions. A sloppy license? That’s a due diligence landmine.

In fact, one of my early jobs was licensing compliance for a biotech that sold services. I remember pouring over compliance filings for hours, validating whether they were likely reasonable and then preparing the invoice. Years later, we developed this Compliance Continuum for a review of Australia’s Medicare system to describe this (Philip, 2023):

Philip (2023). The Compliance – Fraud Continuum as it applies to IP Licensing in Life Sciences and Health Care

Call to Action: What You Need to Do Now

If you’re a licensor—especially an SMB in research, diagnostics, or biotech—here’s what I want you to do this week:

Review your license agreements. Are you requiring system-generated reports? If not, it’s time to fix that.
Talk to your licensees. Don’t assume malice—but don’t assume accuracy, either. Ask what systems they use to track usage and reporting.
Get your legal team (or external counsel) on board. If contracts are vague or weak, start drafting updates that include audit rights, remedy clauses, and clear data obligations.
Think like an investor. Would you back a company that couldn’t verify half its revenue? No? Then don’t run yours that way.

Because in life sciences, your trade secrets and licensing revenue are your business. And when you’ve only got one shot at commercialisation—you better be sure someone’s not quietly stealing it.

Building a media monitoring capability 101

References

Curwell, P. (2021). Building a media monitoring capability 101
Gibson Dunn (2025). “Life Sciences 2025 Outlook Brochure“, Gibson Dunn.
Gowling WLG (2025). “Licensing Partnerships in the Life Sciences“, Gowling WLG.
National Crime Prevention Council (2025). “IP Theft: Trends and Statistics“, NCPC.
Philip (2023). Independent Review of Medicare Integrity and Compliance, Final Report for Minister of Health and Ageing, Australia.
Royalty Pharma Collection Trust v. Boehringer Ingelheim GmbH (2021). [2021] EWHC 2690 (Pat), High Court of Justice (UK).
US Chamber of Commerce (2025). “GIPC IP Index 2025“, Global Innovation Policy Center.
U.S. Trade Representative (2025). “Special 301 Report“, Office of the U.S. Trade Representative.
ZIPDo (2025). “Intellectual Property Theft Statistics“, ZIPDo.

DISCLAIMER: All information presented on paulcurwell.com is intended for general information purposes only. The content of paulcurwell.com should not be considered legal or any other form of advice or opinion on any specific facts or circumstances. Readers should consult their own advisers experts or lawyers on any specific questions they may have. Any reliance placed upon paulcurwell.com is strictly at the reader’s own risk. The views expressed by the authors are entirely their own and do not represent the views of, nor are they endorsed by, their respective employers. Refer here for full disclaimer.

Operational Technology and Insider Threat Detection: What You Need to Know

Posted on July 1, 2025 by Paul Curwell

Paul Curwell

8–12 minutes

3 Key Takeaways

Insider threats in operational technology (OT) environments can tank production, cause safety and quality incidents, and cripple your commercialisation pathway—often without leaving a digital trace.
Most insider threat programs are built for IT, not for OT environments with legacy equipment, safety risks, and fragmented data across OT and physical systems.
A smart detection approach—still emerging and adopted by only a few leading organisations—combines behavioural, scenario-based, and contextual signals across IT, OT, and physical domains to reduce risk without disrupting operations.

Insider Threats easily go unnoticed in Operational Technology (OT) environments

A few days ago, hackers opened the valve at Lake Risevatnet dam in Norway and no-one noticed for 4 hours (Security News Weekly). If a technician sabotaged your production line or quietly walked out with sensitive process data from your R&D facility, would you know? Would your systems flag it?

In my experience advising critical infrastructure and research-intensive companies, the answer is usually no. The maturity of cybersecurity in OT environments is backed up by a recent global study commissioned by Forescout (Takepoint Research). Insider threats are one of the most under-recognised risks in OT-heavy businesses. Unlike external hacks, insider incidents are often slow, subtle, and devastating. And they don’t just compromise data—they can damage physical assets, halt operations, and put lives at risk.

Unfortunately, most businesses are still using insider threat models built for IT environments. But OT (operational technology), where physical processes are controlled and monitored, is an entirely different beast. If your business depends on production, engineering, or commercialising proprietary research, it’s time to rethink how you detect insider threats—before it’s too late.

What Is an Insider Threat Program (and why OT gets left behind)

An insider threat program is a coordinated set of processes, technologies, and cultural practices to prevent, detect, and respond to harmful actions from trusted individuals—employees, contractors, vendors, or partners.

These programs typically include:

Policy and governance
Risk and asset identification
Monitoring and detection
Incident response and recovery
Training and culture

Problem is, most insider threat programs focus on IT environments. They monitor email, file transfers, login patterns, and endpoint activity. That’s all great, but in OT settings, insider threats play by a different rulebook.

In an OT-heavy business, critical systems might be unpatchable, unmonitored, or physically exposed. A contractor could swap out a device, reprogram a controller, or sabotage a process, and you wouldn’t see it in your SIEM or Quality Management System (QMS).

Worse, many companies treat OT, IT, and physical security as separate silos. That means no one has the full picture—and malicious insiders know it.

The 3 SMB Risk Management frameworks you need to protect your business

Insider Threat Risks in OT Environments

It’s not just OT environments that are different, the trusted insider risks are different too. Here’s some examples of what plays out in real incidents:

Risk Category	Real-World Example
Sabotage	A maintenance worker disables sensors on a production line, causing costly downtime.
Data compromise	A disgruntled engineer uses a USB drive or other removable media to copy sensitive R&D data, which is subsequently leaked. In OT, USB devices are often used for legitimate tasks—making them a real risk for both data theft and malware introduction.
Theft (equipment / data)	A contractor walks off-site with control modules or exports trade secrets via USB.
Espionage	An insider working for a foreign entity records processes and measures over weeks – the ‘know how’ you build into your processes is often a Trade Secrets which you haven’t patented, so you’re exposed.
Accidental / negligent	A misconfigured PLC leads to an emissions breach and regulatory fines.
Credential compromise	A phishing victim gives attackers access to production systems. Phishing is not just an IT problem—it’s a leading cause of credential compromise in OT-heavy industries, providing a foothold for attackers into production systems.
Process disruption	A technician delays batch runs, quietly costing millions in lost output.
Physical safety risks	A bypassed safety interlock leads to a serious injury on the shop floor. Integrating physical security data (badge logs, CCTV, visitor management) is crucial for correlating physical actions with digital events.

If you’re commercialising a new technology or scaling research into production, these aren’t just operational hiccups. They’re existential threats. They compromise intellectual property (IP), slow down time-to-market, and damage investor confidence.

Mitigating risks from workplace sabotage

OT detection is hard

Think of a real-world example. An power station detects a technician repeatedly accessing a substation after hours. Alone, it looked like overtime. But cross-referenced with badge logs, config changes, and HR notes? It could match a potential workplace sabotage scenario.

Unfortunately, OT environments like this example aren’t designed for visibility. Here are the 6 main detection challenges I see:

OT Detection Challenge	Description
Legacy Systems	Many OT assets run on unsupported platforms that can’t be patched, monitored, or logged. They might also run proprietary protocols or custom integrations. Trying to install endpoint detection software? Good luck.
Mixed Connectivity	Some devices are air-gapped. Others connect via Wi-Fi or cloud APIs. You might not even know how many assets are online.
Fragmented Data	Access logs live in one system, telemetry in another, badge swipes in a third—with no correlation between them. To see the big picture, you need HR, physical security / facilities, IT and OT data in one place
Physical Access Gaps	Unlike IT assets, OT systems are often in physical spaces where people can tamper with hardware or override processes without leaving a digital trace. Many devices have no logging or remote monitoring. Integrating physical security data (badge logs, CCTV) is crucial for correlating physical actions with digital events.
Insider Familiarity	Insiders know your systems. They know the blind spots. They know when no one’s watching. If you’re only monitoring digital access or looking at corporate IT logs, you’re missing half the story. Don’t forget vendors and contractors, who often have privileged access.
Poor documentation	Most orgs can’t trace how an alarm triggers a shutdown, and documentation for legacy systems might have been lost or poorly written. You might even find there’s no-one alive who can code in that language anymore!

This complexity means malicious insiders can chain actions together: badge in, disable a sensor, reboot a system, send a USB payload, walk away. If you want to understand how an insider could compromise your operation? You need to map attack paths across IT, OT, and physical layers.

So what can you do about it? Let’s start with detection.

Insider Threat detection that fits OT

There are 3 main approaches to detection in mixed IT / OT / physical environments. Whether you can use one or all of them depends on your capability maturity, available data, and technology stack on the one hand, and your inherent risk on the other.

Basic: Pattern-of-Life / Anomaly Detection

Many businesses start here. They look for simple red flags of what shouldn’t be happening, or what looks unusual. It’s a good starting point, and it’s where many corporate insider threat detection solutions start by looking at indicators out of the box, without being configured for your business

How it works: Builds a baseline of what “normal” looks like across users and devices. Flags deviations.
Good for: Stable operations with predictable activity.
Watch out for: False positives. No context. Easy to overwhelm your team.

Intermediate Advanced: Scenario-Based and Multi-Step Detection

In my experience there’s a big step up between basic and intermediate. This requires not only tools and data, but also people with different skillsets, such as intelligence analysis and data science. Achieving this successfully is much harder than it sounds.

How it works: Looks for sequences of actions that match known attack paths (e.g., badge-in → PLC access → config change).
Good for: Catching subtle or sophisticated attacks. Lower false positives.
Watch out for: Requires upfront work. Needs good integration.

This work goes by many names, but I use the term ‘typologies’ which is what we refer to in fraud and financial crime to detect a range of complex threats in a dataset. The global financial services industry invests millions each year in this capability to avoid huge fines.

“Typologies” Sound Boring – But They Could Save Your Business Millions

Advanced: AI and Hybrid Models

Last is where AI takes us. I still see organisations using a mix of rule-based detection and AI. Also, there are some applications where you simply can’t use AI yet, such as to identify unknown unknowns or truly ‘novel’ threats. You still need a ‘human in the loop’ here:

How it works: Combines behavioural detection with scenario logic. Surfaces unknown patterns.
Good for: Dynamic environments with lots of data.
Watch out for: Over-alerting. Needs good context and tuning.

It’s worth noting many organisations are only at the start of the insider threat detection journey, so intermediate and advanced detection capabilities are still the exception, not the norm. However, a handful of advanced organisations are combining behavioural, scenario-based, and contextual analysis across IT, OT, HR and physical domains. They’re leading the way—helping develop the tools and methods to implement this at scale.

Alert management and insider risk continuous monitoring systems

Detection-Driven Best Practices

Now you understand the problem we’re trying to solve, let’s talk action. Here’s what I recommend to every business trying to catch insider threats in OT:

Map critical assets and who has access – You can’t protect what you don’t know. Prioritise systems with trade secrets, safety impact, or production value.
Integrate cross-domain data – HR, IT, physical security, OT telemetry. Break down the silos.
Use blended detection methods – Pair anomaly detection with scenario logic to balance breadth and depth.
Segment networks and enforce least privilege – Don’t let operators access systems they don’t need. Limit shared credentials.
Build OT into your incident response playbooks – Include safety, environmental, and operational contingencies.
Train staff beyond cyber basics – Teach operators, engineers, and third parties how insider threats work—and how to report them.
Continuously refine – Systems change. People change. Threats evolve. So should your models.

Continuous Control Monitoring: Your SMB Security Game Changer

Final Word: You Can’t Protect What You Don’t Watch

If your business depends on operational tech, research, or manufacturing IP, you can’t afford to run blind.

Insider threats are rising. According to Ponemon, the average insider incident costs US$15.4M per year, but OT remains a blindspot for many organisations.

So here’s the question I always ask my clients: If someone inside your business tampered with a key process, would you know? Would your systems tell you? Would your people speak up?

If you can’t confidently say yes, it’s time to rethink your detection game.

AI for Deeptech Startups: Balancing Speed and Security

Posted on June 24, 2025 by Paul Curwell

Paul Curwell

7–10 minutes

Key Takeaways

AI is already deeply embedded in how R&D startups operate—handling analysis, reporting, quality monitoring, and workflows.
But every tool and integration you use—especially if ungoverned—can expose your intellectual property (IP) or sensitive data.
Protection doesn’t mean overengineering—startups can use lean frameworks and smart defaults to stay secure without losing momentum.

You’re already using AI—but are you protecting what matters?

If you’re leading a biotech, medtech, advanced manufacturing, or deeptech startup, AI is probably already hard at work in your business. Whether you’re using your LIMS to track experimental data, automating lab tasks with tools like Zapier or N8N, or generating regulatory reports with ChatGPT, you’re benefiting from AI’s ability to deliver speed, insight, and productivity.

And it’s working. You’re innovating faster, making better decisions, and doing more with fewer resources. That’s exactly what investors and partners want to see from early-stage companies. In 2025, you don’t need a 500-person team—you need smart systems.

But the same technologies accelerating your work can also quietly undermine it. If you’re not actively managing how AI interacts with your intellectual property (IP) and sensitive data, you’re leaving the door wide open for mistakes, leaks, or compliance failures that can stall your growth—or sink your business entirely.

Protecting Your R&D When Outsourcing Rapid Prototyping

How AI Is supercharging R&D-intensive startups in 4 use cases

AI isn’t just hype for small innovators—it’s a practical tool delivering real business outcomes. And unlike larger enterprises that spend millions and deploy large teams integrating AI into legacy systems, deeptech SMBs are cloud-native and agile. That gives you a major edge.

Here’s how I see most small, research-driven teams using AI right now:

1. Data Collection and Analysis

Your scientific and engineering teams are automating the aggregation of experimental results, integrating data from sensors, lab systems, and external research. AI helps clean, normalize, and interpret it all—so decisions can be made in days, not months.

You’re also leveraging AI for literature mining and competitive analysis, giving your team a clearer picture of where to focus and how to differentiate.

2. Continuous Control and Quality Monitoring

Whether you’re a medtech firm tracking calibration drift or a materials science startup checking for outliers, AI is helping detect inconsistencies early. This kind of real-time feedback loop improves reproducibility and protects your reputation with regulators and partners.

3. Reporting and Documentation

Grant milestones, regulatory submissions, investor updates—these all take time. AI-generated summaries, charts, and reports help your team stay compliant and communicative without pulling attention away from the actual science.

4. Workflow and Service Management

Your operations are already automated. Zapier, N8N, and Power Automate are running the back office: scheduling lab time, flagging inventory shortages, tracking project milestones. AI helps orchestrate and optimize these workflows so your team stays productive.

This all adds up to serious efficiency gains. But—and it’s a big but—each of these systems and integrations touches sensitive data or protected IP. And that’s where the real risk creeps in.

Protecting Innovation: The Spectre of Trade Secrets Theft in Biotech

Four AI risks most science and tech startups overlook

These are excellent use cases, but like everything, there are pros and cons. Deeptech’s need to understand how AI tools and use cases can generate downside risk for your business:

1. Trade Secrets Floating in the Open

AI models are great at summarising documents and drafting content. But paste your prototype results or lab logs into an unsecured LLM, and you might be training someone else’s model with your trade secrets.

This isn’t a fringe issue. In 2023, employees of one global tech company accidentally leaked sensitive source code through ChatGPT. They were trying to be efficient—but exposed high-value IP instead.

Case Study 1: Global tech’s ChatGPT Blunder: IP Exposure Through Misunderstanding

In 2023, engineers pasted sensitive source code and internal meeting notes into ChatGPT while trying to solve coding problems. They didn’t realise that public AI tools could store and retain this input.

The result? Confidential trade secrets exposed. The company responded by banning the use of generative AI internally. But the damage was done.

Lesson: If your staff don’t understand how AI tools process and retain information, they may accidentally train someone else’s model with your crown jewels.

Practical actions:

Identify what qualifies as a trade secret in your business. Write it down.
Turn off chat histories in AI tools or use private models.
Avoid pasting raw R&D data or code into consumer AI platforms.

2. Data Leaks Through Automation Tools

Automation platforms like Zapier, Make, and N8N are amazing for productivity—but they’re often invisible to risk and compliance teams. If data is moving between systems without encryption or logging, that’s a blind spot.

One startup had lab results automatically emailed to a shared inbox via Zapier. Harmless? Until one of those emails ends up forwarded to the wrong contact triggering a data breach incident.

Case Study 2: Global tech company’s AI Team Accidentally Exposes 38TB of Data

In another 2023 case, another big tech’s own AI research team uploaded a GitHub repo with an incorrectly configured Azure SAS token. This gave public access to 38TB of internal data—including private research, credentials, and backups.

This wasn’t a cyberattack. It was a configuration error—just one line of code—and it put an entire research group’s IP at risk.

Lesson: Even world-class AI teams can slip up if access controls and cloud permissions aren’t managed carefully.

Practical actions:

Audit your integrations quarterly. Know where data is flowing.
Limit the exposure of sensitive data in workflows.
Apply the same scrutiny to no-code tools as you do cloud providers.

The Rising Threat of Cyber-Enabled Economic Espionage: What Business Leaders Need to Know

3. Misconfigured Cloud Environments

Being cloud-native doesn’t mean being secure. Startups often move quickly, spinning up instances, sharing buckets, and adding users without much structure. The result? Sensitive IP and research data sitting in misconfigured storage with public access enabled.

Case Study 3: Biotech’s AI Feature Abused to Extract Genetic Data

Attackers didn’t hack the biotech’s core systems. They reused leaked credentials to log into user accounts and exploited the company’s DNA Relatives feature—powered by AI—to harvest massive amounts of genealogical and genetic data.

The breach wasn’t about a flaw in the AI—it was about poor monitoring and a lack of foresight into how AI-powered features could be abused at scale.

Lesson: AI features can scale risk just as fast as they scale value. You need visibility and governance to keep both in check.

Practical actions:

Use native controls like IAM, DLP, and logging in AWS, GCP, or Azure.
Review access privileges regularly—especially after staff or contractor changes.
Don’t assume your default setup is safe—check it.

4. Regulatory Risk and Data Sovereignty

If you’re collecting personal or regulated data—think clinical trial results, biospecimens, or identifiable research participant data—you’re accountable under privacy laws. And regulators won’t accept “we’re a startup” as an excuse.

Practical actions:

Store regulated data in compliance with local data laws.
Map where your data lives and who can access it.
Delete data you no longer need—less data, less risk.

You Don’t Need an Army—You Just Need a Plan

Information security and data protection doesn’t have to be expensive or complicated. You just need to know what matters most—and build guardrails that suit your size and stage.

That’s why frameworks like SMB1001 exist. Designed for small, R&D-heavy businesses, it gives you a clear path to understanding what’s critical, setting sensible access controls, and documenting how you manage risk—all in a way that supports growth, not bureaucracy.

You don’t need ISO 27001 on day one. But you do need to show investors and partners that your IP and data aren’t flying blind through a tangle of automations and unvetted tools.

The 3 SMB Risk Management frameworks you need to protect your business

Final Thoughts: AI Is Fuel for Growth—If You Protect the Engine

AI is your multiplier. It helps small teams outperform larger competitors, serve customers faster, and bring complex products to market on a startup budget.

But if your trade secrets leak or research data ends up in the wrong hands, that advantage disappears overnight. Worse, you might not even know it’s happened until it costs you a deal, a grant, or a key staff member.

So if you’re using AI—and I know you are—take these three steps now:

Map where your IP and sensitive data live.
Review how they flow through AI and automation tools.
Use a framework like SMB1001 to set practical controls that grow with you.

The best part? Once you’ve got this in place, you’re not just secure—you’re investable, credible, and ready to scale.

Product Diversion in the Healthcare Supply Chain: What’s the Problem and How Big Is It?

Posted on June 17, 2025 by Paul Curwell

Paul Curwell

6–10 minutes

Key Takeaways:

Healthcare Product Diversion is a multi-billion-dollar problem for MedTech, Pharmaceutical, HealthTech and Consumer Healthcare manufacturers, especially Small-Medium Businesses (SMBs)
Manufacturers are most at risk, but distributors and consumers feel the pain too.
Practical solutions exist—from serialization and contract clauses to better training and audits.

Why Product Diversion is a problem for Healthcare Supply Chains?

Product diversion might sound like a minor logistics glitch, but it’s a growing form of supply chain fraud with serious consequences for manufacturers. It undermines pricing strategies, exposes patients to risk, and silently drains profit from businesses—especially in pharmaceuticals, medtech, and consumer healthcare.

Let’s ground this in reality:

Price Gouging in Grey Markets: A 2012 U.S. Senate investigation revealed that during drug shortages, grey market distributors were marking up prices by up to 650%, creating an exploitative shadow supply chain that directly impacted patient care and manufacturer pricing strategies.
IP and Brand Risk for SMBs: According to a 2013 analysis by Michigan State University’s A-CAPP Center, illicit diversion and counterfeiting in healthcare products pose major threats to brand trust, supply chain security, and IP protection—risks that are especially acute for small and mid-sized companies lacking robust controls and visibility.
Healthcare Product Diversion via Unauthorised Resellers: Unauthorised resellers obtain genuine products through bulk or discounted sales and redirect them into unapproved markets. This undermines pricing and contracts, risks product quality due to improper handling, and threatens supply chain integrity. Such diversion impacts compliance, profitability, and consumer safety.

While precise global loss figures are difficult to pin down due to the covert nature of diversion, the financial and reputational impact is consistently described by regulators, manufacturers, and law enforcement as both significant and growing.

Product diversion is a risk to consumers and HCPs, HCOs. — Photo by Anna Tarazevich on Pexels.com

How does Product Diversion happen in healthcare supply chains?

Healthcare Product Diversion schemes don’t follow a single playbook. Instead, they are creative, persistent, and often involve trusted insiders or third parties exploiting weak points in the supply chain.

Method	How It Happens	Example
Bulk purchasing	Authorised buyers order large volumes, then resell to unauthorized parties	Salon-exclusive beauty products showing up in discount e-commerce sites
Overproduction / shadow batches	Contract manufacturers produce more than authorised, sell off the surplus	Unapproved medical device units reappearing in Southeast Asian markets
Theft and leakage	Products stolen from warehouses or in transit	Fentanyl stolen from hospital stocks and sold on the black market
Geographic arbitrage	Products meant for one country sold in another to exploit pricing differences	EU-only medical device diverted to U.S. via grey market reseller
Expired or defective goods	Meant for destruction, but reintroduced into the supply chain	Expired drugs found in unregulated online pharmacies
Collusion and kickbacks	Sales reps or healthcare providers over-order and resell excess inventory	Institutional drugs diverted to retail pharmacies for profit

Understanding these methods is essential if you want to design effective prevention strategies. They often exploit gaps in oversight, compliance, and contractual clarity.

Towards a taxonomy for product diversion

Real-World Case Studies – Pharmaceuticals, Medtech, and Consumer Healthcare

Product diversion isn’t a hypothetical risk for the global healthcare sector —it’s already happening:

Pharmaceuticals: A 2013 U.S. Senate report detailed how opioids intended for healthcare providers were routinely diverted and sold illicitly, playing a direct role in the national opioid crisis¹.
Medical Devices: EU regulators have flagged instances where temperature-sensitive devices were diverted to regions without the infrastructure to store them safely, leading to degraded product quality and recall risks.
Consumer Healthcare: Brands like Redken and Olaplex have openly addressed diversion issues. Products intended for exclusive sale in salons have appeared on Amazon and eBay, undermining pricing integrity, partner relationships, and consumer trust.

These examples highlight the diverse nature of diversion threats and show that no segment of the healthcare supply chain is immune.

All manufacturers – big and small – are vulnerable to Product Diversion

Manufacturers sit at the top of the risk pyramid.

They suffer the most from product diversion, followed by authorised distributors and, finally, healthcare providers and consumers who must deal with the consequences.

Manufacturers lose direct revenue from diverted sales.

They also face brand damage when mishandled products tarnish reputation, and serious regulatory risk when expired or non-compliant items are resold.
Consumers don’t blame the grey market vendor—they blame the brand.

Small-to-medium-sized manufacturers are even more exposed.

Often, they don’t have dedicated legal or compliance teams, formal diversion programs, or tools like serialisation in place.
Their supply chains are lean and reliant on third-party relationships—relationships built on trust rather than tight oversight.

Unfortunately, this creates the perfect opportunity for diverters to exploit weak links.

The USP/APEC ‘Supply Chain Security Toolkit for Medical Products’

So what? The Business Impact

For manufacturers, the business implications of diversion go well beyond lost sales:

At a strategic level, diversion undermines pricing control, exclusivity agreements, and go-to-market models.
From a financial perspective, every diverted unit is a unit sold outside authorized channels—often at a discount or under different conditions. That distorts revenue forecasts, inflates warranty claims, and creates return headaches.
Operationally, diverted goods often re-enter your returns and recalls process, costing time and money.
From a compliance angle, unauthorized sales might breach your distribution contracts, prompt regulatory investigations, or expose your business to liability if patients are harmed.

If you’re trying to secure IP rights in a new market or negotiating an investment, diversion-related quality or compliance issues can tank your credibility quickly.

Control gaps enable Product Diversion

Understanding what makes your business vulnerable is the first step to fixing it.

Vulnerability	Description
Complex global supply chains	Multiple players and jurisdictions reduce visibility
Weak contractual oversight	Contracts without anti-diversion clauses or penalties
Limited serialization and tracking tech	No way to trace individual units across the supply chain
Insider threats and poor awareness	Employees or partners exploiting gaps in oversight
Market price differentials	High variation in pricing between regions fuels geographic diversion

When multiple vulnerabilities stack up, diverters can exploit your entire supply chain, from production to post-sale support. Fortunately, each of these can be addressed with proportionate controls.

Mitigation Strategies for Product Diversion in Healthcare Manufacturing

Now for the good news. You don’t need to spend millions to protect your supply chain from diversion. Here are six effective, scalable steps:

1. Use Serialization and Digital Tracking

Track-and-trace technology, including QR codes and unique identifiers, allows unit-level visibility. It can deter resale and help identify leak points quickly. Newer tools are cost-effective and accessible to SMBs.

2. Update Contracts

Review your contracts with manufacturers, distributors, and resellers. Include anti-diversion clauses, audit rights, and explicit consequences for unauthorised sales. Legal clarity closes loopholes.

3. Audit and Monitor the Supply Chain

Use a risk-based auditing framework. Start with high-risk partners or geographies. Look for unusual purchasing volumes, inconsistent delivery data, or unauthorised resale complaints.

4. Train Your Staff

Awareness is critical. Your internal teams—from sales to shipping—need to know how diversion happens, why it matters, and what signs to watch for. A single employee spotting something suspicious can save you a lot of pain.

5. Use Incentives and Whistleblower Programs

Encourage internal reporting by rewarding ethical behaviour. Employees and partners are more likely to speak up when they feel safe and supported.

6. Leverage External Expertise

If you don’t have in-house expertise, work with professionals who understand the complexities of IP protection, supply chain risk, and regulatory compliance. Tailored assessments can identify hidden weak points.

Integrating Security into Quality Management Systems

Call to Action: Stop Assuming Product Diversion Is Someone Else’s Problem

If you’re a manufacturer in pharmaceuticals, medtech, or consumer healthcare, it’s time to act.

You don’t need perfection—you just need proportionate protection. Start with serialisation. Tighten your contracts. Educate your teams. The earlier you build diversion awareness into your commercialisation strategy, the better positioned you’ll be to protect your research, technology, and trade secrets.

Let’s connect if you need help building a scalable product diversion program. It doesn’t have to be big to be effective. And the sooner you act, the fewer losses you’ll have to explain.

About Paul Curwell

3 Key Takeaways

What is Comparative Case Analysis?

Why Comparative Case Analysis Matters for Business

The Comparative Case Analysis Value Chain

How to Actually Do It (Step‑by‑Step)

Real Case Examples to Learn From

Call to Action

Further Reading

3 Key Takeaways

Introduction

The Cost of Warranty Fraud

How Fraud Affects Manufacturer Warranty Claim Forecasts

How Does Warranty Fraud Occur?

A. Customer Fraud

B. Dealer and Service Agent Fraud (Insider Threats)

C. EmployeeS (Insider Threats)

D. Warranty Provider and Administrator Fraud

4. How Should Manufacturers Protect Their Revenue From Warranty Fraud?

a. Contracts

B. Transaction Controls

C. Analytics

D. Service Network Management

Conclusion: Stop the Silent Margin Killer

Further Reading

The impact on your business

Why R&D-intensive companies are vulnerable

The professionalisation of ransomware in 2025: the 8-step targeting cycle

Case studies: when ransomware hit the labs

Conclusion: the strategic picture

Further Reading

3 Key Takeaways

You’re Bleeding Money and Don’t Even Know It

The Billion-Dollar Problem Nobody Talks About

Where Your Money Disappears: The Top Leakage Points

Manufacturing & Procurement Losses

Distribution & Channel Partner Issues

Sales & Service Revenue Gaps

MedTech is More Vulnerable Than Pharmaceuticals

Building Your Revenue Defense System

1. Implement Real-Time Monitoring

2. Strengthen Contract Controls

3. Enhance Supply Chain Integrity

4. Data-Driven Partnership Management

The Board-Level Questions You Need to Ask

Your Next Steps: Stop the Bleeding

Further Reading:

Key Points

“We Thought We Were Too Small to Be Targeted”

The Phishing Shift: Multi-Channel, Deepfake, and Voice Fraud Are the New Norm

What’s Really at Risk? IP, Trust, and your Entire Business Model

Real Example: The Deepfake COO That Killed a Fundraise

The Cloud Trap: “We Use Microsoft/AWS, So We’re Covered” (No, You’re Not)

Who Secures What in the Cloud?

So What Do You Actually Do? Here’s a Business-Ready Plan

1. Use the Cloud Security Tools You Already Own

2. Lock Down Identity, Access, and Data

3. Train for the Threats of 2025

4. Prepare for the Breach—Because It Will Happen

5. Audit Your SaaS and Supply Chain Access

6. Give the C-Suite Metrics That Matter

Final Thoughts: Security Is Commercialisation

Further Reading

3 Key Takeaways

Security Is a Business Decision—Not a Technical One

Security Creates Value—and Investors Know It

When IP Protection Becomes a Business Valuation Driver

A. Discovery Stage:

B. Prototyping Phase:

C. Clinical Validation:

D. Scaling Phase:

Scaling Stage Actions:

What Investors Now Ask (And What You Need to Answer)

The Bottom Line: Security as a Strategic Advantage

If You’re Not Watching Your Licensees, Someone’s Losing—Probably You

Manual Reporting? Welcome to Fraud City

Case Study: Royalty Pharma v. Boehringer Ingelheim

Why This Matters to Your Bottom Line

The Simple Fix: Trust, But Verify

This Isn’t Legal Stuff—It’s Strategy

**4. Prepare for the Breach—Because It Will Happen**