“Marta epitomises everything that the DataIQ 100 list is about — a smart, data-literate, committed, international practitioner who is putting her skills to work for the benefits of clients and their customers."
The business of collecting debt is getting more challenging. The current environment where debtors don’t pick up the phone or answer the mail has made collections even more difficult. And people who owe you money, likely owe money to many others and you are challenging for your fair share. It used to be if a department had a strong collection system they could collect their fair share. Now, that is just table stakes. The following article from Dataconomy discusses how government collections analytics are needed to truly increase collection performance. In addition, new collection strategies that take advantage of this analytics are needed which enable you to work smarter, not harder in order to collect more money using cost-effective strategies. Government Collections Analytics: Predictive Models – Who will Self-Cure All of us who have worked in the collections industry understand that different strategies work for different customers (“debtors”). Some debtors... [Read More]
Creating a collaborative, scalable, transparent process for getting advanced analytics out of the lab and into the everyday business is the only way to truly operationalize and get maximum business value from analytic investments.
“I’m Scott Zoldi and I’ve authored 95 patents on AI, machine learning and various analytic techniques. I’m Chief Analytics Officer of FICO. Ask me Anything.*
As advanced analytics permeated nearly every industry in 2018, FICO’s thought leaders continued to push it into new areas. Here were the top 5 posts in the Analytics & Optimization category last year.
Adopting machine learning to enhance not just the accuracy of models but also drive efficiency is critical to amplify a key asset - the analytic team – and stay competitive.
My recent patent work has laid a foundation for what I predict will be the tech industry’s biggest development in 2019: ethical AI.
Regulatory efforts may prove valuable, but banks and law enforcement still need to use SARs more effectively, and that’s where cognitive analytics for AML can be a tremendous boon.
Behavioral profiling approaches are extremely important in tackling fraud that happens when banks share financial data with third parties through application programming interfaces.
Uncovering hidden patterns in money movement makes machine learning for AML a very attractive enhancement to existing AML operations.