Compliance Expert David Lang on How Alphy’s RLC Strengthens Restricted List Detection

When it comes to compliance and market integrity, few people match David Lang's depth of experience. A former securities prosecutor and global chief compliance officer at Royal Bank of Canada — with responsibilities across 29 markets over 23 years — Lang now serves as a compliance advisor to Alphy.

We spoke with him about one of the most challenging areas in financial compliance — insider trading detection — and the critical role of spotting “tipping” before it’s too late. He shared exclusive insights into why traditional tools often fall short in containing material non-public information breaches (MNPI), what sets Alphy's HarmCheck Restricted List apart, and how contextual AI could reshape the compliance landscape.

Here’s what he had to say:

Q: Why is control list monitoring still such a challenge, despite the tools already on the market?

A: Traditional surveillance systems do a solid job of flagging obvious red flags — certain keywords, unusual trading patterns, or access violations. But in my experience, control list breaches are rarely that straightforward. They often surface in casual, shorthand, or even accidental references to ticker symbols or company names. That’s where many systems fall short.

Q: You’ve worked with many compliance technologies. What stands out about the HarmCheck Restricted List Classifier (RLC)?

A: What impresses me is that HarmCheck RLC is the only restricted list classifier I’ve seen that reliably detects company names and ticker symbols without overwhelming compliance officers with false positives. It understands when common words that also happen to be tickers — like CAT, NOW, GOOD, SHOP — are being used innocently in a sentence, versus when they’re actually being used as ticker symbols. That balance of precision and context is what makes it so valuable.

Q: How does a modern RLC work?

A: HarmCheck RLC uses fine-tuned AI classifiers to distinguish between normal language and true references to restricted tickers or company names. It looks at the context, not just the word itself. That means compliance teams get accurate alerts on the communications that matter, instead of chasing noise created by legacy lexicon-based tools.

Q: How do you see this changing the compliance landscape?

 A: It fills a critical gap. Firms have invested heavily in transaction monitoring and access controls, but communication surveillance around control lists has lagged. HarmCheck RLC strengthens the overall surveillance framework by giving compliance teams early warning signals before a trade ever happens or during subsequent investigations.

Q. Alphy employees also have a unique skillset: language, with backgrounds in journalism. How do you think that makes a difference in building a technology like the Restricted List?

A: Journalists bring critical communication skills that can complement AI by helping it better approximate human nuance and contextual understanding — improving the accuracy of alerts identified for human review. 

Q: Any final thoughts?

A: The industry has long needed a restricted list tool that bridges the gap between human nuance and regulatory rigour. HarmCheck RLC aims to do exactly that — setting a new standard for responsible, forward-looking compliance.

Bottom line: Control list monitoring will always be a high-stakes challenge — but with tools that combine human expertise and advanced AI, firms can catch risks earlier and strengthen their compliance posture. As David Lang notes, it’s about closing the gap between nuance and regulation, and setting a new industry standard for proactive, responsible oversight.

Book a free demo of RLC today: http://harmcheck.ai/demo

By Alphy staff

Alphy’s proprietary HarmCheck RLC (Restricted List Classifier) safeguards sensitive deal information in real time for banks and financial service firms. It alerts employees in real-time — rather than after the message has been sent — to restricted list watchwords. HarmCheck RLC, built with ML/AI and high-quality human generated training, is a simple email and text integration, customizable to a company’s needs. Alphy is also the maker of HarmCheck, an AI communication compliance solution that detects and flags language in real-time that is harmful, unlawful, and unethical in digital communication. For more information: www.harmcheck.ai.