Credit Unions and Regional Banks face great challenges from an AML standpoint for several reasons. Large banks have more funds available to maintain expensive compliance programs and for absorbing big fines when non-compliant. Smaller financial institutions need to be more and more efficient in identifying suspicious behaviors as the costs of maintaining AML compliance continues to grow. Furthermore, smaller financial institutions might be perceived as softer targets for cash-based activities like structuring deposits to avoid detection. Automated machine learning provides the ability to more efficiently monitor for suspicious activity.
Justin Dickerson, General Manager of Global Finance for DataRobot, and Dan Yelle, a Customer-Facing Data Scientist for DataRobot have decades of combined experience applying data science and machine learning to solve business problems in the FinTech, Insurance, and Banking industries. They work closely with partners in the Financial Services industry to ensure their machine learning initiatives are successful.
In this webinar, Justin and Dan show how automated machine learning can be used to reduce false positive rates, thereby improving the efficiency of AML transaction monitoring and reducing costs.
You'll discover how Automated Machine Learning provides:
- The ability to develop and refresh AML predictive models at any time
- The ability to deploy models with a click of a button
- The ability to operationalize AML models by following a process that is user-centric
DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.
We will contact you shortly
We’re almost there! These are the next steps:
- Look out for an email from DataRobot with a subject line: Your Subscription Confirmation.
- Click the confirmation link to approve your consent.
- Done! You have now opted to receive communications about DataRobot’s products and services.
Didn’t receive the email? Please make sure to check your spam or junk folders.