September 2015
EFT Data Management
Solving Wire Transfer and ACH Data Challenges
By Nikhil N. Fafat, Mohammad Nasar, and Christopher J. Sifter, PMP
Electronic funds transfers (EFTs) offer speed and
convenience for bank customers as well as efficiency
and low transaction costs for financial institutions. But
the widespread use of wire transfers and automated
clearinghouse (ACH) transactions also can present
significant data management challenges, especially in
terms of Bank Secrecy Act and anti-money laundering
(BSA/AML) regulatory compliance.
Nonstandardized source data and complex data formatting structures can result in
inaccurate, incomplete, or duplicate records that greatly complicate compliance efforts.
These data issues also create additional encumbrances for line-of-business processes.
A proactive approach to EFT entity resolution (improving EFT data quality) can help
financial institutions address these concerns, enabling more accurate alerts, more
efficient investigations, and improved regulatory compliance.
Challenges of Working With EFT Data
The ability to accurately identify the various unique parties involved in a transaction
is essential for compliance with BSA/AML regulatory requirements.
This necessity
applies not only to the financial institution’s immediate customer but also to all
counterparties (legal entities or a collection of entities that can pose a financial risk to
the institution) to the transaction. A bank also must be able to identify links among the
various counterparties and their accounts.
Because a bank’s ability to meet these requirements can be complicated greatly by
slight variations in customer names, addresses, and other identifying information, most
existing BSA/AML software requires external tools and processing (such as in the data
integration layer) to recognize and standardize common abbreviations and variations in
order to cross-reference and aggregate information and to identify related transactions
and accounts.
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In addition to identifying unique and related parties, an AML system must be able to
correctly identify the locations of transactions in order to accurately quantify the risk
associated with a particular operation. Institutions also need to be able to identify and
segment customers by risk profile – a university presents a significantly different AML risk
from a casino, for example. Here again, the ability to accurately identify these customer
segments depends on data quality and the consistent use of standardized formats.
These challenges are further complicated by the number of parties involved in each
EFT transaction. Parties include the customer who initiates the transaction, the
originating customer’s bank, intermediary institutions such as the Federal Reserve
Bank, the receiving bank, the recipient customer, and other corresponding institutions.
Every time a new participant enters the transaction chain, new opportunities appear
for errors and inconsistencies in data formatting.
In fact, many data quality issues are
beyond an individual institution’s jurisdiction, since the initial data input often occurs at
another institution.
Finally, it should be noted that the various institutions and interbank payment systems
employ their own particular data file formats. These include the U.S. Federal Reserve
Bank’s Fedwire, the Clearing House Interbank Payments System (CHIPS) format for
certain foreign exchange and euro-dollar transactions, the Society for Worldwide
Interbank Financial Telecommunication (SWIFT) format for international wire transfers,
and the NACHA format for domestic ACH transactions.
This diversity among data
formats adds further complexity to any data standardization effort.
Why Common Approaches Fall Short of What’s Needed
Because most AML applications cannot inherently identify and coordinate duplicate
entities, banks must resort to using a variety of other strategies to address EFT
data issues. In a recent webinar for bank executives hosted by Crowe Horwath LLP,
participants were asked to identify the techniques they use to address the challenges
of working with EFT data. By far the most frequently named technique was stricter
enforcement of the bank’s data collection policies, a finding that seems consistent
across the financial services industry.
Unfortunately, although stricter enforcement of data collection policies is the most widely
used method for addressing EFT data quality issues, there are a number of drawbacks
to this approach.
For example, it is not at all uncommon for customer-facing personnel
and managers in banks’ primary lines of business to regard their banks’ existing
data collection and know-your-customer (KYC) requirements as being unnecessarily
burdensome and intrusive. Adding even more stringent data collection requirements and
more rigorous enforcement is almost certain to generate internal resistance.
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Adding even more
stringent data collection
requirements and more
rigorous enforcement is
almost certain to generate
internal resistance.
. EFT Data Management:
Solving Wire Transfer and
ACH Data Challenges
An even greater drawback, however, is the inherently limited effectiveness of such an
approach, which cannot be relied upon to produce significant improvement in data
quality. The reason, as noted earlier, is that in most banks a sizable proportion of EFT
transactions originate from outside the institution. Cracking down on inconsistent or
nonstandardized data entry in the institution does nothing to address data collection
problems generated elsewhere.
Other attempts to address data quality concerns are more technology-driven, yet
these too generally achieve limited success. For example, developing a complex
programming solution for standardizing data and aggregating related transactions is
timely, expensive, and difficult to implement correctly.
Such efforts generally require
extensive internal IT expertise and resources.
Another common approach involves attempting to develop matching heuristics to
eliminate duplication. The drawback of this technique is its tendency to generate
multiple false positives, resulting in a significant increase in the volume of alerts that
must be investigated. As a consequence, institutions often find that their compliance
efforts actually become less efficient rather than more efficient.
EFT entity resolution must resolve ambiguities, duplication,
and inconsistencies in identifying and aggregating related
transactions and entities.
A More Effective Approach: EFT Entity Resolution
To avoid the shortcomings of the most commonly used efforts to improve EFT data
quality, many banks are seeking a more effective approach that enables them to
accomplish three fundamental steps:
1. Identify patterns of behavior (such as common originators and common beneficiaries).
2. Aggregate transactions that are tied to the same entity.
3. Aggregate alerts that are traced back to these entities.
A functional term that can be used to describe such a solution is EFT entity resolution.
It must, in essence, resolve ambiguities, duplication, and inconsistencies in identifying
and aggregating related transactions and entities, regardless of whether these
ambiguities stem from nonstandardized data formatting or from varying, complex data
file structures.
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Contact Information
Nikhil Fafat is with Crowe Horwath LLP
and can be reached at +1 312 899 4492
or nikhil.fafat@crowehorwath.com.
Mo Nasar is with Crowe and can be
reached at +1 630 574 1846
or mo.nasar@crowehorwath.com.
Chris Sifter is a director with Crowe and
can be reached at +1 312 857 7363
or chris.sifter@crowehorwath.com.
An effective EFT entity resolution approach that can overcome the limitations of the
most commonly attempted solutions must function in all three major phases of EFT
data processing:
1. Data ingestion. The system enters data from standardized raw formats and collects it
in a central repository.
2. Data resolution and cleansing. The system standardizes and cleanses the data,
merges similar entities, cross-references against master institution lists, and then links
merged entities to their original transactions.
3. Data delivery. The system transforms and delivers data to match commonly used
transaction monitoring systems such as NICE Actimize, Oracle® Mantas, and Fiserv
Financial Crime Risk Management solutions.
In addition, an EFT entity resolution approach ideally will offer a number of other
attributes.
For example, an effective solution should include automated data inputs
and outputs to reduce manual overhead and errors. It also should be scalable, allowing
the institution to adapt to organic growth as well as merger and acquisition activity.
An effective EFT entity resolution approach also must be flexible enough to
accommodate different methods of operation and transaction processes across
various lines of business, and it should be capable of accommodating new data
sources and operations that might be developed in the future.
The Goal: Proactive Data Management
In addition to improving BSA/AML compliance efforts, the ultimate goal of an effective
EFT solution is to enable institutions to anticipate and adapt to future trends in
transaction technology as well as future developments in regulatory requirements.
With EFT transactions continuing to account for a growing share of bank transactions,
such an approach can be a powerful tool for accelerating and empowering an
institution’s transaction monitoring and customer due diligence functions while
simultaneously improving overall productivity and effectiveness.
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This material is for informational purposes only and should not be construed as financial or legal advice. Please seek guidance specific to your organization from qualified advisers in your jurisdiction.
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