DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. This provides a great amount of benefit, but it also exposes institutions to greater risk and consequent exposure to operational losses. Model Validation – Prior to the use of a model (i.e.,

Risk 111

Risk Modeling IT Risk Management 111

Smart Data Collective

SEPTEMBER 17, 2020

Financial institutions such as banks have to adhere to such a practice, especially when laying the foundation for back-test trading strategies. Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations. The Role of Big Data. Engaging the Workforce.

Big Data 141

Big Data Finance Risk Management Risk 141

O'Reilly on Data

DECEMBER 12, 2019

Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Interpretable ML models and explainable ML. Sensitivity analysis.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. The algorithms can detect anomalies in the transactional data and helps to identify high-risk customers and transactions that may be linked to money laundering activities.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. The algorithms can detect anomalies in the transactional data and helps to identify high-risk customers and transactions that may be linked to money laundering activities. These include-.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

CIO Business Intelligence

AUGUST 23, 2023

“You’re able to select a smaller number of stocks with predictive return and lower operational and transaction costs, which ultimately means that you can reduce the variability and more accurately predict returns,” Muthukrishnan says. It’s important for us to test the technology and be ready,” Muthukrishnan says.

IT 97

IT Machine Learning Risk Optimization 97

CIO Business Intelligence

OCTOBER 13, 2023

Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143