IBM Big Data Hub

MAY 4, 2020

Many financial firms are increasing their use of AI models because they can represent the real world more accurately, and they can deliver better projections than traditional, rule-based models. But some AI models can add complexity and risk.

Risk Management 81

Risk Management Risk Modeling Management 81

CIO Business Intelligence

SEPTEMBER 29, 2022

New York-based insurance provider Travelers, with 30,000 employees and 2021 revenues of about $35 billion, is in the business of risk. Managing all of its facets, of course, requires many different approaches and tools to achieve beneficial outcomes, and Mano Mannoochahr, the companyâ??s Watch the full video below for more insights.

Machine Learning 124

Machine Learning Insurance Technology Software 124

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. What is a model?

Risk 111

Risk Modeling IT Risk Management 111

BizAcuity

APRIL 1, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. 1] With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States.

Risk 64

Risk Modeling Machine Learning Data Quality 64

BizAcuity

JANUARY 18, 2023

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. With the rise of Big Data in today’s world, Machine Learning (ML) is popularly used to identify, assess, and monitor financial risks as well as detect various suspicious activities and transactions.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Cloudera

MAY 30, 2024

In this context, Cloudera and TAI Solutions have partnered to help financial services customers accelerate their data-driven transformation, improve customer centricity, ensure compliance with regulations, enhance risk management, and drive innovation. What are some of the reasons that TAI Solutions’ customers choose Cloudera?

Data Analytics 81

Data Analytics Risk Management Digital Transformation Analytics 81

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). Foundation models can use language, vision and more to affect the real world.

Risk 70

Risk Modeling Management Metadata 70

Cloudera

JUNE 12, 2024

Traditional machine learning (ML) models enhance risk management, credit scoring, anti-money laundering efforts and process automation. Capital One leverages GenAI to create synthetic data for model training while protecting privacy. What Should Institutions Invest In?

Finance 70

Finance Risk Management Risk Data-driven 70

DataRobot Blog

JUNE 27, 2022

Monitoring Modern Machine Learning (ML) Methods In Production. In our previous two posts, we discussed extensively how modelers are able to both develop and validate machine learning models while following the guidelines outlined by the Federal Reserve Board (FRB) in SR 11-7. Monitoring Model Metrics.

Risk 59

Risk Modeling Metrics Measurement 59

DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. Validating Machine Learning Models.

Risk 52

Risk Modeling Metrics Business Objectives 52

DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

CIO Business Intelligence

MAY 13, 2024

IBM is betting big on its toolkit for monitoring generative AI and machine learning models, dubbed watsonx.governance , to take on rivals and position the offering as a top AI governance product, according to a senior executive at IBM. watsonx.governance is a toolkit for governing generative AI and machine learning models.

Risk 109

Risk Machine Learning Modeling Enterprise 109

CIO Business Intelligence

JUNE 12, 2024

CIOs believe that the top three tech initiatives driving these increased IT investments will be security and risk management (45%), artificial intelligence (AI) and machine learning (44%), and business process and IT automation (44%).

Machine Learning 52

Machine Learning Risk Management Consulting Strategy 52

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

CIO Business Intelligence

JANUARY 18, 2024

Half of CEOs say their organization is at least somewhat unprepared for AI and machine learning (ML) adoption, according to Workday’s C-Suite Global AI Indicator Report. That’s a big difference with machine learning vs. traditional approaches.” Just 6% say they are fully prepared.)

Finance 119

Finance Machine Learning Risk Management Optimization 119

IBM Big Data Hub

JUNE 10, 2024

As organizations strive to harness the power of AI while controlling costs, leveraging anything as a service (XaaS) models emerges as a strategic approach. Embracing the power of XaaS XaaS encompasses a broad spectrum of cloud-based and on-premises service models that offer scalable and cost-effective solutions to businesses.

Experimentation 63

Experimentation Optimization Risk Management Modeling 63

CIO Business Intelligence

MAY 9, 2024

That includes IT, to align AI technologies with existing infrastructure; HR, on workforce development; finance, to understand funding and new business cost models; and legal and compliance, to ensure responsible use of AI. This includes skills in statistical analysis, data visualization, and predictive modeling.

Risk Management 134

Risk Management Risk Cost-Benefit Technology 134

CIO Business Intelligence

DECEMBER 19, 2023

This year’s technology darling and other machine learning investments have already impacted digital transformation strategies in 2023 , and boards will expect CIOs to update their AI transformation strategies frequently. CIOs should look for other operational and risk management practices to complement transformation programs.

Digital Transformation 140

Digital Transformation Unstructured Data Machine Learning Risk Management 140

IBM Big Data Hub

APRIL 19, 2024

Mobile-connected technicians experience improved safety through measures such as access control, gas detection, warning messages or fall recognition, which reduces risk exposure and enhances operational risk management (ORM) during work execution. Risk-based asset strategies align maintenance efforts to balance costs and risks.

Management 85

Management Internet of Things Risk IoT 85

CIO Business Intelligence

SEPTEMBER 14, 2023

Nasdaq is currently using gen AI for a range of applications, including supporting digital investigators’ efforts to identify financial crime risk and empowering corporate boards to consume presentations and disclosures more efficiently.

Risk Management 110

Risk Management Risk Marketing Cost-Benefit 110

O'Reilly on Data

JULY 15, 2019

As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. What cultural and organizational changes will be needed to accommodate the rise of machine and learning and AI?

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

CIO Business Intelligence

SEPTEMBER 20, 2023

Data Management: CIOs are focused on effectively managing and leveraging the massive amounts of data generated by digital businesses. Artificial Intelligence (AI) and Machine Learning (ML): AI and ML are rapidly gaining traction as a means of automating processes and improving decision-making.

Digital Transformation 102

Digital Transformation Risk Management Risk Machine Learning 102

O'Reilly on Data

JANUARY 22, 2019

An exploration of three types of errors inherent in all financial models. At Hedged Capital , an AI-first financial trading and advisory firm, we use probabilistic models to trade the financial markets. All financial models are wrong. Clearly, a map will not be able to capture the richness of the terrain it models.

Modeling 136

Modeling Finance Uncertainty Data mining 136

Cloudera

FEBRUARY 4, 2021

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. Cloudera is that platform.

Risk 88

Risk Marketing Technology Management 88

CIO Business Intelligence

OCTOBER 4, 2023

There’s also strong demand for non-certified security skills, with DevSecOps, security architecture and models, security testing, and threat detection/modelling/management attracting the highest pay premiums. AI skills more valuable than certifications There were a couple of stand-outs among those.

Prescriptive Analytics 125

Prescriptive Analytics IT Machine Learning Risk 125

CIO Business Intelligence

AUGUST 23, 2023

That need for complex mathematical modeling at scale makes the finance industry a perfect candidate for the promise of quantum computing, which makes (extremely) quick work of computations, including complex ones, delivering results in minutes or hours instead of weeks and months.

IT 76

IT Machine Learning Risk Optimization 76

IBM Big Data Hub

FEBRUARY 13, 2024

This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task. Generative adversarial networks (GANs) or variational autoencoders (VAEs) are used for images, videos, 3D models and music. Autoregressive models or large language models (LLMs) are used for text and language.

Enterprise 119

Enterprise Modeling Testing Data-driven 119

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. Operations.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

Cloudera

JULY 15, 2021

For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. . Attendees included senior risk managers and analytics experts from financial institutions and insurance companies.

Risk 100

Risk Optimization Management Insurance 100

IBM Big Data Hub

DECEMBER 15, 2023

When AI algorithms, pre-trained models, and data sets are available for public use and experimentation, creative AI applications emerge as a community of volunteer enthusiasts builds upon existing work and accelerates the development of practical AI solutions. Morgan’s Athena uses Python-based open-source AI to innovate risk management.

Deep Learning 64

Deep Learning Experimentation Machine Learning Risk 64

Cloudera

FEBRUARY 24, 2021

Trend #1: The Crossroads of Risk Management and Emerging Technology. One shift the financial services industry will have to come to terms with is the fact that 2020 may have made risk management models of the past outdated or obsolete , particularly credit risk models.

Risk Management 61

Risk Management Risk Recreation/Entertainment Machine Learning 61

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 361

Risk Modeling Data Processing Software 361

DataRobot

AUGUST 9, 2021

However, many organizations don’t implement any feedback loop to monitor and control their models after they’re out in production. General Data Protection Regulation, California Consumer Privacy Act, SR 11-7 Guidance on Model Risk Management, etc).

Machine Learning 52

Machine Learning Risk Testing Insurance 52

CIO Business Intelligence

SEPTEMBER 7, 2022

Dubbed Cropin Cloud, the suite comes with the ability to ingest and process data, run machine learning models for quick analysis and decision making, and several applications specific to the industry’s needs.

B2B 86

B2B Contextual Data IoT Deep Learning 86

Cloudera

AUGUST 25, 2020

Richard Harmon, Managing Director of Financial Services at Cloudera, to find out more about how the industry is adopting new technology. Thank you for joining us for part two of our discussion around data, analytics and machine learning within the Financial Service Sector Dr. Harmon.

Prescriptive Analytics 74

Prescriptive Analytics Technology Machine Learning Risk 74

IBM Big Data Hub

JANUARY 30, 2024

Finance: Optimized for high-speed transactions and can assist in providing robust security, harnessing AI for fraud detection and real-time risk management. Retail: Manage e-commerce platforms, customer data analytics and supply chain logistics, where data analysis often must occur at the edge.

Manufacturing 71

Manufacturing Business Objectives Optimization Risk Management 71