A top 3 B2B stablecoin issuer scaled compliance review for a $5B+ payment volume program — without adding headcount
How a regulated B2B stablecoin issuer and payment solution — ranked among the top 3 in its category, with over $5B in payment volume — scaled program document reviews, client operations reviews, communications reviews, and client onboarding (KYB) after its banking partner called for higher scrutiny, by connecting Hookshot™ and Teach your AI directly to its existing Asana review history, with zero added headcount.
Top 3
Ranked among the top 3 B2B stablecoin issuers and payment solutions
$5B+
Payment volume processed by the stablecoin program
0
Net new headcount added to the compliance team as review volume and scrutiny both increased
Weeks → days
Time to complete submission feedback dropped from multiple weeks to several days
Senior leadership visibility
Onboarding status became visible to senior leadership, supporting company-wide goals to streamline the process
About
A regulated B2B stablecoin issuer and payment solution — ranked among the top 3 in its category, with more than $5B in payment volume, and counting two of the top DeFi wallets among its platform's users — runs compliance review across four workflows: program document review, client operations reviews, communications reviews, and client onboarding (KYB). When the program's banking partner requested heightened scrutiny as a de-risking measure, the compliance team needed to absorb materially more review volume without expanding the team.
Key workflows
- Program document review
- Client operations reviews
- Communications reviews
- Client onboarding (KYB) — privacy policy, terms of service, infosec process documentation, and related diligence
Key features
Hookshot™ Protege Agents, Teach your AI, Reusable AI skills, Automated Asana review workflows
Key integrations
Asana
Highlights
Challenges
The stablecoin program's banking partner requested heightened scrutiny across the relationship as a de-risking measure — raising the bar on program document review, client operations reviews, communications reviews, and client onboarding (KYB) all at once. The compliance team's existing review history lived in its Asana projects, built up over many cycles of manual review, but that judgment wasn't captured anywhere a system could apply it consistently at higher volume. Meeting the banking partner's new scrutiny standard the traditional way would have meant adding compliance headcount in proportion to the increased review burden — at a moment when the program needed to demonstrate tighter control, not just more reviewers.
Solution
The team connected Teach your AI directly to its existing Asana projects, where the compliance team's program document reviews, client operations reviews, communications reviews, and client onboarding decisions already lived. Rather than starting from a blank policy document, Teach your AI took the team's existing policy documents and augmented them to handle known corner cases — the edge cases analysts had been resolving manually, cycle after cycle, that the written policy never quite covered. Those augmented policies were converted into reusable AI skills, portable enough to run inside Protege or Claude rather than being locked to one interface. Hookshot™ Protege Agents built on those skills apply the same review logic going forward across all four workflows. New program docs, client operations reviews, communications reviews — privacy policies, terms of service, infosec process documentation — and onboarding files are checked against the learned standard before a human reviewer opens them, with only genuine edge cases and high-risk items escalated. Every decision is logged with full rationale, which mattered directly once the banking partner's heightened scrutiny requirement took effect.
Outcomes
The compliance team scaled to meet its banking partner's heightened scrutiny requirement across program documents, client operations reviews, communications reviews, and client onboarding — without adding headcount. Time to complete submission feedback dropped from multiple weeks to several days, and senior leadership gained direct visibility into onboarding status — visibility that helped the team streamline the process in line with company-wide goals. Because Hookshot™ and Teach your AI built on the team's own policy documents and historical Asana review decisions rather than a generic rulebook, the Hookshot™ Protege Agents reflected how this specific team already evaluated risk and handled corner cases, which shortened the path to a system the banking partner could trust. The reusable AI skills produced along the way now travel with the team — usable inside Protege or Claude — rather than being locked into a single tool.
Raising the bar across four review workflows at once
When the banking partner asked for heightened scrutiny, it touched program documents, client operations reviews, communications reviews, and client onboarding simultaneously — not one isolated workflow.
- The new standard covered more documentation, faster escalation, and additional checks across every workflow at once.
- All four review types now run against a consistent, audit-ready standard rather than four separately maintained processes.
Turning policy and past decisions into reusable AI skills
Instead of building a review policy from scratch, Teach your AI augmented the compliance team's existing policy documents to handle known corner cases, then converted the result into reusable AI skills.
- Corner cases that previously required an analyst's judgment — the ones the written policy never quite covered — are now encoded directly into the skill.
- Those skills are portable: they run inside Protege or Claude rather than being locked to a single interface.
- Hookshot™ Protege Agents apply those same skills to new program docs, client operations reviews, communications reviews, and onboarding files.
Client onboarding (KYB) as one workflow among four
Client onboarding — what the team calls KYB internally — runs through the same Hookshot™ Protege Agent workflow as program document and communications review, not a separate system.
- Onboarding review checks documentation including privacy policies, terms of service, and information security process documentation, among other diligence materials.
- Routine onboarding files clear without a full manual pass; only ambiguous or high-risk cases escalate.
Audit-ready records for a banking partner relationship under scrutiny
Every decision — approve, escalate, deny — across all four review types is logged with inputs, outputs, and rationale, built for the kind of scrutiny a banking partner relationship demands.
- The new review standard directly addressed the banking partner's request for heightened scrutiny.
- Preparation time for banking partner reviews and audits dropped.
Scaling review volume without scaling headcount
Review volume and scrutiny both increased. Headcount didn't.
- Zero net new compliance headcount added despite the banking partner's heightened scrutiny requirement.
Faster submissions, visible to leadership
Submission feedback that used to take multiple weeks now takes several days — and senior leadership can see onboarding status directly, rather than waiting on a status update from the compliance team.
- Time to complete submission feedback dropped from multiple weeks to several days.
- Senior leadership gained visibility into onboarding status, which supported company-wide goals to streamline the process.
Conclusion
Before Hookshot™ and Teach your AI, meeting a banking partner's request for heightened scrutiny across program documents, client operations reviews, communications reviews, and client onboarding would have meant growing the compliance team to match. After, Hookshot™ Protege Agents built on the team's own policy documents and reusable AI skills apply that same judgment consistently across all four workflows — at $5B+ in payment volume, with zero net new headcount, and faster submissions across the board.
