Effectively Documenting Transactions to Avoid Penalties

Reporters Woodward and Bernstein were famously advised to “Follow the money” as a way to navigate through the complicated web called Watergate.  Last week, U.S. regulators fired their latest warning shot across the bow of another transaction-focused business – daily fantasy sports – signaling their expectation that these businesses abide by the same regulations that bind banks, gambling casinos, and (shortly) investment advisory firms.  With their international counterparts, U.S. regulators are starting a boa-like squeeze to choke off the placement, layering, and integration of criminally obtained funds.

Non-bank organizations should take the opportunity to learn from the mis-steps that have cost banking institutions literally billions of dollars in penalties, fines, and settlement costs.  As a recent study by Thomson Reuters documents, regulators are turning increasingly to more ‘personalized’ penalties – effectively ending careers and firms who can’t or won’t comply.  This increased cost of non-compliance, coupled with aggressive transaction coverage, is designed to change behavior.

An earlier post outlined the cost implications of implementing effective AML policies – suffice it to summarize that implementation costs typically rise well beyond after initial installation.  A common driver of those increases is the cost of human review for each ‘flagged’ transaction. Estimates by established AML screening teams suggest a hard cost of roughly $50 per alert investigated.  For transaction-rich businesses using the latest screening and alerting technology, this can amount to millions of dollars of AML compliance effort – assuming you can find, hire, and train qualified AML staff.

A key reason for this – poor, incomplete, inconsistent documentation of entities, transaction details, and associated information that human investigators need to either escalate or close an alert.  Here’s a best practice every business should adopt quickly and easily – invest in technology that can unify data from disparate systems (e.g. your transaction and customer identification databases) and automatically produce consistently structured documents for reviewers.  Why?  Because that step, alone, can improve investigator productivity dramatically.

Visibility and Context Are Essential

You’ve just been alerted to a potentially illegal transaction.   Your have precisely two options – escalate the transaction case for a thorough forensic review or close the case, indicating that the transaction is unlikely to prove illegal.  Here are two review workflows.  Which is likely to be more productive?

Workflow #1

Find the suspect transaction between the entities.  After determining what’s indicative or suspicious, you want to recover other transactions executed by these parties (Should I also look at transactions they’ve made with other parties?) over some time horizon (How wide should my horizon be?). I’ll also need to review information about each entity (How much do I know about this customer?), including possible connections between the organizations they’re representing. 

Now, I’ll look for other suspicious patterns in transactions between or among all these entities.  Now, I have data that corroborates the suspicious or innocent nature of the alerted transaction.  Oh, yes … I need to document what I just reviewed and the decision I made, because regulatory authorities will audit/review our AML efforts.  I’ll cut and paste information into a pre-designed case report.

Workflow #2

When the alert was generated, a smart application collected all transaction information for each of the entities, including transactions with other parties, and information from my ‘know-your-customer’ files – correlates similar transaction patterns, and generates a case summary in a format of my choosing.  The format for the summary provides the information regulators expect to see associated with each case’s disposition.

In a recent deployment of a case enhancement solution supporting Workflow #2 above, a major bank quantified a productivity increase for reviewers of more than 60%, cutting the single most rapidly growing compliance cost component by more than one-half.  The lesson was clear – the cost of ‘false positive’ alerts can be reduced substantially – without changing existing transaction monitoring investments.  Improving visibility and adding context transform compliance analyst productivity.

A New Face for Big Data

Your organization’s transactions, in the eyes of money laundering regulators, contain more information than you’ve imagined.  Regulation means you’ll soon see them differently, as well.  Like all forms of information that record patterns of behavior, transaction records are a part of an emerging Big Data reality.

Like so many other Big Data challenges, anti-laundering monitoring and compliance solutions hinge upon visibility, enrichment, and agility.  Visibility into every relevant data stream that surrounds a transaction increases certainty.  Enrichment – adding nuance or structure to existing data - supports deeper, faster insight. And agility insures that today’s solution can adapt to the changing patterns of criminal behavior.

Focusing on the right point of leverage – compliance reviewer productivity – can have a sizeable impact of the cost of compliance; which is good news, given the cost and scrutiny of non-compliance.

Again –

  1. Connect disparate data sources, to eliminate analytic ‚blind spots’
  2. Enhance case-related information with consistent, compliant summaries,
  3. Reduce costs by improving human productivity, not analytic complexity
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