The Future of Fighting Financial Crime

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The anti-financial crime landscape is continuously evolving, and financial institutions need to stay a step ahead of emerging fraud trends and regulatory compliance challenges to protect their customers and themselves from loss and reputational damage.

As consumers become increasingly reliant on the speed and convenience of digital banking products, institutions should consider end-to-end financial crime management solutions that offer real-time fraud detection, targeted AML transaction monitoring and automated regulatory reporting to fight financial crime and strengthen compliance. With artificial intelligence, including machine learning and robotic process automation (RPA), behavior-based anti-financial crime management solutions can help institutions increase the effectiveness and efficiency of their fraud and AML programs.

But artificial intelligence relies on the power of big data. Anti-financial crime management solutions need an immense data set from multiple sources, including core, ancillary, open-source, third-party and consortium data. Artificial intelligence can be applied to this data with cross-institutional analysis in a cloud-based environment. Solutions built with big data and artificial intelligence reduce false positives and increase the quality and accuracy of alerts.

Analytical agents built with machine learning algorithms continuously analyze data to improve analytical performance. A large, cross-institutional data set in a cloud-based environment allows machine learning agents to train on labeled data from thousands of institutions, achieving performance levels that cannot be matched by a single institution with a limited, isolated and restricted data set. Machine learning can significantly improve analytical performance, helping institutions reduce false positives and reduce the alert review time to increase the efficiency of investigations, while continuing to detect new and emerging criminal trends.

Machine learning agents use mathematical and statistical models to learn from data without being explicitly programmed. These agents analyze new data, including transactions, demographics and customer behavior, and utilize this evidence in transaction monitoring alerts. The alerts provide feedback to the cloud-based data set, where the training data, which includes the transaction, demographic and customer-behavior evidence, and labeled data, such as cases, marked transactions and return items, are input to a machine learning algorithm.

This data is used to train many different types of machine learning agents to determine which type of agent performs best for a particular typology. Before training an agent, the data is split into training, testing and validation data sets, so that the results of the training can be validated in an unbiased manner. Anti-financial crime management solutions can use precision, recall and false positive rate to validate analytical performance and assign the most suitable analytical agent to a particular fraud or money laundering typology.

Strengthening Processes with Robotic Process Automation

Institutions can leverage technology such as RPA to improve internal processes, strengthen anti-financial crime management programs and ensure regulatory compliance. Using RPA to improve workflow automation can save financial crime investigators time by reducing manual tasks, automating steps in alert triage and regulatory reporting processes, and through prepopulating and submitting reports with consistency, speed and accuracy.

Enhanced data collection through RPA reduces human error that occurs during manual data collection and transference. It also automatically and reliably integrates multiple data sources in your anti-financial crime management and compliance solutions.

Anti-financial crime management programs can use RPA agents to validate information populated in a currency transaction report or a suspicious activity report, automatically submit reports, intelligently package related alerts together, and automatically assign work to a team or an investigator. Such solutions can also automatically triage alerts and segment customers into appropriate risk categories, increasing the efficiency and effectiveness of financial crime investigations.

To stay ahead of financial crime trends, financial institutions should consider the benefits of cloud-based solutions that leverage artificial intelligence to increase the effectiveness and efficiency of anti-financial crime management and compliance programs.

Five Derivatives Safety Tips: Accessing Power While Maintaining Peace of Mind

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derivatives-8-20-19.pngWe don’t buy products; we “hire” products to get a job done. For banks, interest rate swaps are often just the thing they need to accomplish their most important work.

As Harvard Business School Professor Theodore Leavitt famously said, “People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!” For banks needing to balance the blend of fixed- and floating-rate loans and deposits on their books, no product gets the job done more effectively than an interest rate swap.

Yet, because swaps carry the label of derivative, many community banks are hesitant to engage them — similar to a first-time homeowner on a DIY project avoiding power tools due to fear of injury or lack of knowledge. To maintain peace of mind while accessing the power of interest rate derivatives, community banks should keep these five safety tips in mind:

1. Finding the Derivative
The most-compelling benefit of an interest rate swap is that everyone gets what they want: the borrower enjoys a 10-year fixed rate, the bank maintains a floating yield. If a program offers this benefit in a “derivative-free” package, there is likely an interest rate swap hiding beneath the surface.

Transparency is essential in creating a safe work environment. Maybe my bank is not a party to a derivative, but what about my Main Street borrower? Safety begins with understanding the mechanics and the parties to any rate swap that might be present.

2. Understanding Derivative Pricing
Because the parties that assist community banks with swaps are typically compensated by building extra basis points into the final swap rate, it is important to have a basic understanding of derivative pricing to remain injury-free. When it comes to swap rates, not all basis points are created equal.

Just like the price/yield relationship with a fixed-income security, the “price value” of each basis point in an interest rate swap is a function of both notional amount and maturity term. So, while an extra five basis points would amount to $2,250 on a $1 million swap for a 5 year/25-year commercial mortgage, the value of fees would grow to $40,000 if the five extra basis points were embedded into a $10 million loan with a 10 year/25-year structure. Community banks should understand the amount of compensation built into each transaction in order to remain out of harm’s way.

3. Documenting with ISDA
The International Swaps and Derivatives Association has been standardizing over-the-counter derivatives market practices for the past 40 years, since the infancy of swaps. One of its first projects was designing the document framework known today as the ISDA Master Agreement, or “The ISDA” for short. Sometimes maligned for its length and complexity, the ISDA is often overlooked as a valuable safety shield for community banks who value simplicity.

Although originally built “by Wall Street for Wall Street,” the ISDA is carefully designed to protect both parties in a derivative relationship, defines key terms and sets forth remedies for a non-defaulting party should the other party fail to perform. Since it is recognized across the globe as the industry-standard, engaging in swaps without the protection of the ISDA can be hazardous.

4. Determining Collateral for Counterparty Risk
Counterparty risk, or the risk that an interest rate swap provider will fail to honor its obligations in the contract, can be mitigated by holding cash or securities as collateral. Before 2008, large banks and dealers required community banks to post collateral to secure their risk but were unwilling to reciprocate. The resulting damage caused by the failure of Lehman Brothers Holdings led to a self-imposed shift in market practices, whereby collateral terms in most swap relationships today are bilateral. Community banks considering using derivatives should seize this opportunity to hold collateral as a precautionary measure for the unexpected.

5. Utilizing Hedge Accounting
Embracing the recently updated hedge accounting standard is the final key to reducing the risk and volatility associated with these tools. With recent changes, the Financial Accounting Standards Board has succeeded in delivering what it promises on the cover of its now-mandatory update to ASC 815: “Targeted Improvements to Accounting for Hedging Activities.” One key improvement that helps protect community banks is the added ability to hedge portfolios of fixed-rate assets. That, when paired with more flexibility in application, has transformed hedge accounting from foe to friend for banks.

By taking heed of these five safety tips, community banks and their boards of directors can confidently consider adding interest rate derivatives to their risk management tool kits.