5 Challenges to Disclosing Financial Interests for Independence Compliance

Alex Olson
7/19/17 6:45 AM

Over the past few years, public accounting firms have invested in having financial institutions provide them files of holdings and transactions, which is commonly referred to as broker data import (BDI) and financial interest integration (FII). These files are then imported into their personal independence system to enhance ease-of-use and robust disclosure. By automating the import of brokerage data, compliance is increased dramatically and user satisfaction with the process goes up dramatically. To the extent that a process can be put in place to reduce the need for a user to log into a system and accomplish the goals of that process, the better. Also, by automating the process, disclosure of financial interests are automated. No longer are there situations where a person forgets to disclose - the system does it automatically every day. Regulators have been pushing organizations to move beyond policy to automated controls that provide compliance with the policy. Automatically importing the data is a powerful response.Disclosing_financial_interests_Independence_compliance.jpg

Top Disclosure Challenges

While FII is essential, it cannot solve all disclosure challenges alone. We have complied the top five reasons for this situation.

  • Accounts at Financial Institutions not enrolled: While some organizations are mandating certain financial institutions, others find this approach too difficult on a global basis. Therefore, FII does not provide comprehensive coverage of accounts.
  • Uncooperative Financial Institutions: After on-boarding over 100 financial institutions around the world over the past few years, we have observed certain financial institutions being uncooperative. This uncooperative nature includes legal issues, technical constraints, and other factors that make them difficult to receive files. While the financial institutions seem uncooperative, these organizations simply do not have inducements in most cases to work with the public accounting firm.
  • Incapable Financial Institutions: Antiquated systems, coupled with data that is difficult to extract and send, cause some financial institutions to be incapable of creating a file. The cost to resolve these challenges are simply too high, and therefore, the financial institution decides not to participate.
  • Multiple types of financial instruments: While the focus has been on stocks, bonds, and funds, personal financial interests include bank accounts, loans, credit cards, insurance products, and others. These financial interests are not included in most files today.
  • Jurisdictional Data Privacy concerns: In certain jurisdictions, financial institutions are limited by law or regulation to transmit certain information to third parties and/or outside of their jurisdiction. This situation creates significant challenges.

What can be done?

The good news is that every financial institution provides financial statements on a periodic basis. These documents, while unstructured from a technical perspective (not a data file), are readable by our text analytics platform. For those financial institutions that fall into one of the categories above, a user of our system can upload their financial statement and the machine identifies the financial interest. With that information, our system then can do the same matching, rule comparisons, exception processing, and notifications that users are accustomed to receiving. Based on a configuration, the user could then be prompted to ensure that the statement for the financial institution be uploaded.

If you read my blog about the Inspection Module and the use of AI technology, the concept is the same. Plus, at our customer's option, the system can store the statements for use in the inspection process which means less work for the practitioner and stronger, more robust disclosure. The results are fewer violations of independence matters and happier users.

A few short years ago, none of this was possible. Now, we have the technology to read documents and create structured information that can be used for business processes. Call us for a demonstration of our text analytics and machine learning capabilities.

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