BSA/AML Analyst
Customer Due Diligence (CDD) Review
What You Do Today
Review and update customer risk profiles — beneficial ownership, source of funds, expected activity, and ongoing monitoring adjustments. Periodic reviews are triggered by risk level, and high-risk customers get reviewed annually.
AI That Applies
AI-powered CDD workflows that auto-populate customer profiles from available data sources, screen for adverse media and sanctions, and flag when actual activity deviates from expected patterns.
Technologies
How It Works
The system ingests available data sources as its primary data source. NLP models parse document text into structured data — extracting named entities, classifying sections by type, and flagging content that deviates from expected patterns. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The risk assessment decision.
What Changes
CDD reviews start with a pre-populated profile instead of a blank form. The AI highlights what changed since the last review — new beneficial owners, activity pattern shifts, adverse media hits.
What Stays
The risk assessment decision. Determining a customer's risk level — considering their business type, geography, transaction patterns, and your institution's risk appetite — is professional judgment.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for customer due diligence (cdd) review, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long customer due diligence (cdd) review takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your Chief Compliance Officer
“What are the top 5 reasons customers contact us, and which of those could be resolved without a human?”
They set the risk appetite for AI adoption in regulated processes
your legal counsel
“How do we currently measure service quality, and would AI-assisted responses change that measurement?”
AI in compliance creates new regulatory interpretation questions
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.