It wasn’t that long ago when compliance was considered an afterthought by many financial institutions. With the top line being “the priority”, banks haven’t always been able to see the true benefits of compliance, and therefore make the right investments and adopt the right strategies.
With recent compliance-related losses at many leading financial institutions, the associated regulatory penalties, loss of customer confidence and overall reputational exposure, banks are taking a serious look at their compliance programs and rethinking their compliance strategies.
And the regulators too are rethinking their strategies. Regulations such as Dodd-Frank are making it mandatory for banks to uncover the full risk within the financial institution. This means that the financial institution will need to go beyond traditional methods of surveillance and risk management by having a clear and accurate understanding of its employee activities and customer relationships while uncovering previously unknown risks. Regulations are now also making their way into previously unregulated financial products, such as CFTC rules that oversee options, futures and commodities products. Another example is the recent change to FINRA rule 5270 that consolidates and then extends oversight of potential front running activities.
In every one of these cases, financial institutions are coming under significant pressure to better understand what their employees are doing,how their customers are transacting, and of course the relationships that may exist between employees and customers, and their related activities. It now comes down to the financial institution to uncover relationships and activities that were previously unknown or being intentionally concealed.
So here’s the dilemma, how does a financial institution know what they don’t know? Current compliance solutions only have the capability to analyze transactional and trade data and are limited by the contents of this structured information. Additionally, these solutions can only react and , therefore, reveal risks based on known patterns or keywords – leaving the financial institution exposed as malicious employees and customers figure out how to avoid using known keywords or engineer transactions in a way to conceal unauthorized activities.
The compliance industry is at an inflection point
There is an emerging desire on the part of financial institutions to become proactive and extend their efforts to detect employee trading abuses, money laundering activities, hidden relationships and related risks. Not only to meet the demands of the regulators, but more importantly, to uphold the reputations of their organizations and avoid the massive losses and disruptions to their businesses when these abuses and exposures are uncovered.
Here’s an interesting fact, over the course of the last 5 years, $11b have been paid out in losses and penalties by just a handful of financial institutions. This doesn’t include depreciation of equity value, business disruptions, loss of customer confidence and market share. Which for these institutions, the reputational and brand exposure is far greater than the $11b in trading and transactions losses, and regulatory penalties.
These losses and reputational exposures are pressuring banks to change the way they analyze their business and leverage their data. A good example of this; banks are starting to appreciate the wealth of information that resides within their unstructured data sources, such as email, instant messaging, dealer chat, documents and social media. Banks are searching for technologies like Digital Reasoning that can semantically reveal hidden relationships, risks and exposures within this unstructured data.
Our technology truly understands how people communicate, regardless of the data source. Having been battle tested within the intelligence and counterterrorism communities for over a decade, we operate on the principle that we need to help people “know what they don’t know”. So, when the trader intentionally avoids using the word “basket or portfolio” in order to avoid keyword or pattern detection, our technology is intelligent enough to recognize the deal-related conversion, because of other pieces of the discussion, such as a quantity, or an action (buy/sold) or a set of dates and relationships. These examples extend across a whole suite of use cases, such as:
- Anti Money Laundering: Analyze information within wire instructions and other unstructured transactional fields in order to identify hidden relationships, previously unknown household associations, high-risk geographies & locations.
- Conduct Risk: Reveal employees who have become ethically exposed, involved in bribery and fraudulent activities by analyzing communications traffic for related behaviors and assertions.
- Control Room Violations: Uncover relationships between employees that are on a restricted trading list, and their communications with external counterparties trading in the restricted securities based on insider information.
- Know Your Customer (KYC): Automate the process of building a public profile of new customers and corporate entities by scrubbing publicly available sources of information for risk-related information.
- Trading Abuse: Discover hidden relationships and trade-related activities that have been intentionally obfuscated within email, instant messaging and dealer chat.
- Trade Finance – Collateral Classification: Reveal information within collateral documentation, agreements and manifests that identify collateral risk, based on hidden relationships, assertions and associations.
A proactive compliance strategy needs to be underpinned by analytics that have proven to reveal previously unknown relationships, activities and risks. When combined with an effective transactional surveillance strategy, this approach is capable of moving any financial institution forward from a reactive compliance strategy to a proactive compliance implementation that is designed to meet evolving regulatory demands while providing an effective defense against regulatory losses and, more importantly, reputational risk and loss of customer confidence.
If you’re interested in learning more, please feel free to visit our website that contains additional information on our Proactive Compliance analytics at: http://www.digitalreasoning.com/proven-results