Best practices in Risk modeling for AML Compliance
Experts in AML Compliance are also experts in creating and leveraging Risk models. So much of successful AML hinges on successfully categorizing, identifying, and monitoring for Risk, and that includes risk models in a risk-based approach. Those are foundational elements of the work of AML Compliance. But the element that experts often overlook—or do not know exists—is the key to truly exceptional Risk Management in AML. That key: Multidimensional Risk. The following details the foundations of Risk in AML Compliance—and it explains why Multidimensional Risk is the key to gaining exceptional insight into a financial institution’s AML Risk.
What are the key sources of Risk intelligence in Risk models for AML Compliance?
The key sources are Modeled Risk, Derived Risk, Event-based Risk, and Multidimensional Risk.
- Modeled Risk— Modeled Risk, a cornerstone of AML Compliance, requires a generalized look at the risk of conducting business. Key categories of Modeled Risk include the following:
- Types and details of customers/entities served by the institution
- Products and services offered by the institution
- Geographic concerns, i.e. concerns specific to an institution’s customers/entities and where they conduct business operations and sales
- Transactional activity conducted by customers
- Derived Risk—Derived Risk is non-modeled risk realized through normal operations, such as data feeds and screening.
- Event-based Risk—Event-based Risk is the realization of negative actions or events by customers. Because it’s event-based, this type of Risk cannot be easily predicted and modeled. Event-based Risk can often be recognized during Derived Risk activities like Risk-relevant data feeds and regular screening. An example would be a change of ownership of an entity served by the bank. Actions that qualify as Event-based Risk often happen outside of the data paradigm that drives an institution’s normal Risk modeling.
- Multidimensional Risk—In Multidimensional Risk, financial institutions leverage the Risk engines in their AML software solutions to create separate Risk models for any or all of their categories and any or all of their factors. These pin-pointed Risk models can then feed other Risk models that feed other Risk models and so on. Multidimensional Risk provides for financial institutions the most accurate and finely grained analysis of Risk.
Why Multidimensional Risk supercharges Risk modeling
Multidimensional Risk is the ‘secret sauce’ of exceptional Risk Management in AML Compliance. By leveraging Multidimensional Risk, a financial institution increases exponentially its capacity to drill down—automatically–into the finely-grained complexities of Risk inherent in its book of business.
For example, an institution may want to create a model to determines the Risk level of each of their customer types. When this model runs against a customer and the type is indicated, this model inserts the proper score into the final AML Risk model. So the first model is only to determine the risk of each customer type. And that result is fed into the main model to calculate the final Risk score.
This Multidimensional Risk method allows institutions to model every single factor of Risk they have identified. This makes possible their finely grained understanding of the Risk levels of each customer in relation to each Risk factor. Those finely grained Risk levels by factor automatically flow into the final Risk model. And the final Risk model calculates the final AML Risk score for each customer.
Choose AML solutions that feature Multidimensional Risk modeling
Part of the magic of Multidimensional Risk is that once configured, it will automatically calculate Risk levels for individual factors and then feed results to other Risk models. To take advantage of Multidimensional Risk, institutions need to prioritize that feature when choosing their AML software solutions.
High-powered modern Risk engines in AML solutions will make Multidimensional Risk an embedded option. AML Partners’ RegTechONE platform features Multidimensional Risk modeling, for example. And the RegTechONE platform offers Multidimensional Risk modeling in an end-to-end AML Compliance solution.
RegTechONE users configure their Risk models for factors and related elements, and they configure which Risk models will feed other Risk models. All of which feed into the calculation of the final AML Risk score.
Multidimensional Risk: Gain total control of complex Risk analysis in your AML Compliance
The bottom line for Multidimensional Risk is that it makes possible extraordinary levels of granularity—under the full control of an institution’s experts in Risk and AML Compliance. For peak Risk Management, financial institutions should leverage every Risk-relevant tool available. And Multidimensional Risk is one of the most powerful—and most important.