DataRobot

AUGUST 15, 2019

Pepper Spain is one of the leading providers of consumer finance services in Spain, working with point-of-sale retailers across all industries to give them the best financing options for their business needs.

Finance 9

Finance Machine Learning Optimization Predictive Modeling 9

Jet Global

APRIL 27, 2020

Finance departments can access transparent, real-time reporting of financial results at regional and store levels. Crucially, having a handle on vital financial details from point-of-sale onward helps finance to more easily identify variables that impact a customer’s relationship with the brand.

Finance 52

Finance Forecasting Sales Reporting 52

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 90

IT Machine Learning Risk Optimization 90

IBM Big Data Hub

OCTOBER 16, 2023

Foundation models can use language, vision and more to affect the real world. GPT-3, OpenAI’s language prediction model that can process and generate human-like text, is an example of a foundation model. They are used in everything from robotics to tools that reason and interact with humans.

Risk 73

Risk Modeling Management Metadata 73

DataRobot Blog

JUNE 3, 2022

AI is touching our lives and societies in ways that no other technology has before, from improving human efficiency in the Health , Finance , and Communication sectors, to allowing humans to focus on other important decision-making tasks that machines cannot yet safely or creatively tackle.

Risk 52

Risk Predictive Modeling Modeling Technology 52

Jedox

JULY 23, 2019

As the reliance on data-driven decisions becomes more prevalent in finance, there is a need to manage data better and remove data anomalies or errors in the “cleansing” process. These will certainly give you lots of insight and some very narrowly defined foresight, but unlikely to ever be widely defined 3-way predictions for Finance.

Technology 52

Technology Forecasting Finance Data-driven 52

datapine

AUGUST 14, 2019

Big companies that utilize R in their analytics operations, such as Google, Facebook, and LinkedIn , usually are finance and analytics-driven, as R has proved to be the top mechanism for data analysis, statistics, and machine learning. Source: RStudio. R is platform-independent, meaning it can be easily applied in each operating system.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

CIO Business Intelligence

APRIL 25, 2022

Cost: $9 per month for content and forum; $29 per month for the premium bundle; $899 per month for the month-to-month intensive program; $2,499 for the three-month intensive program (financing is available). Locations: Online. Practicum , by Yandex, is a digital reskilling program that offers bootcamps for data scientists and data analysts.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

CIO Business Intelligence

AUGUST 7, 2023

Most executives have fairly siloed expertise and lean towards oversight of specific areas such as supply chain or finance.

IT 96

IT Sales Manufacturing Cost-Benefit 96

Smarten

JUNE 26, 2018

Finance – An organization might use this technique to Identify if demographic factors influence banking channel/product/service preference or selection of a type of term plan of an insurance etc.

Testing 40

Testing Statistics IT Business Intelligence 40

IBM Big Data Hub

FEBRUARY 14, 2024

Financial services AI-powered FinOps (Finance + DevOps) helps financial institutions operationalize data-driven cloud spend decisions to safely balance cost and performance in order to minimize alert fatigue and wasted budget. Banks and other lenders can use ML classification algorithms and predictive models to suggest loan decisions.

Cost-Benefit 85

Cost-Benefit Insurance Unstructured Data Machine Learning 85

Rocket-Powered Data Science

FEBRUARY 12, 2021

Interest in AI is high and growing, specifically in the areas of smart analytics, customer-centricity, chatbots, and predictive modeling. Top use cases in the back office include finance (general ledger data reconciliation), accounts payable (invoice processing and payment), and HR (new employee onboarding).

ROI 234

ROI Digital Transformation Reporting Machine Learning 234

O'Reilly on Data

SEPTEMBER 19, 2023

” Web3 has similarly progressed through “basic blockchain and cryptocurrency tokens” to “decentralized finance” to “NFTs as loyalty cards.” Bayesian data analysis and Monte Carlo simulations are common in finance and insurance. And it was good. For a few years, even.

Machine Learning 249

Machine Learning Testing Modeling Cost-Benefit 249

Occam's Razor

AUGUST 9, 2021

To help you get closer to your Finance team – you really need to be BFFs with them! – you also get a predictive metric that they will love: Revenue Prediction. Note: Strictly speaking what we are doing above is closer to Predictive Modeling, even though we have a bunch of Predictive Metrics.

Metrics 142

Metrics Analytics Key Performance Indicator Predictive Modeling 142

Cloudera

SEPTEMBER 7, 2023

Develop workshops, e-learning modules, and hands-on sessions designed to familiarize employees with the fundamentals of AI and its applications within the finance sector. AI can assist in assessing and investing in sustainable projects, a growing trend in the finance sector. Initiate basic AI training programs for staff.

Insurance 78

Insurance Risk Data-driven Finance 78

CIO Business Intelligence

JUNE 22, 2022

Furthermore, leading financial institutions poised for a digital banking future rely on data in motion to incorporate climate risk into all risk models when accounting for ESG factors, a topic that is increasingly taking centre stage in finance and investing discussions. What a platform needs to support data in motion.

IoT 96

IoT IT Manufacturing Internet of Things 96

Cloudera

APRIL 27, 2022

Furthermore, leading financial institutions poised for a digital banking future rely on data in motion to incorporate climate risk into all risk models when accounting for ESG factors, a topic that is increasingly taking centre stage in finance and investing discussions. What a platform needs to support data in motion.

IoT 94

IoT IT Manufacturing Internet of Things 94

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

Machine Learning 77

Machine Learning Modeling Deep Learning Predictive Modeling 77

Rocket-Powered Data Science

JULY 6, 2021

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

datapine

MARCH 25, 2022

While some experts try to underline that BA focuses, also, on predictive modeling and advanced statistics to evaluate what will happen in the future, BI is more focused on the present moment of data, making the decision based on current insights. Finances: can Iower financial risk? How Do BI & BA Apply To Business?

Business Intelligence 264

Business Intelligence Analytics Statistics Dashboards 264

BI-Survey

JANUARY 29, 2023

In the context of corporate planning, predictive planning and forecasting, it is therefore a major trend to use predictive models based on statistical methods and ML for forecasting and thorough analysis. It is therefore worth considering options to make improvements beyond the core finance area.

Forecasting 52

Forecasting Predictive Modeling Measurement Finance 52

CIO Business Intelligence

MARCH 22, 2023

It is often used to train machine learning models and protect sensitive data in healthcare and finance. Limitation : While synthetic data may help train a predictive model, it only adequately covers some possible real-world data subspaces. Synthetic data can generate large amounts of data quickly and bypass privacy risks.

Machine Learning 105

Machine Learning Cost-Benefit Modeling Risk 105

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

For example, proposed forecasts may come from customers, if their forecasts are based on forward-looking information about product and technology plans that would be difficult for the data scientist to extract as inputs into a predictive model.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Sisense

SEPTEMBER 25, 2020

Linear regression is a form of supervised learning (or predictive modeling). In supervised learning, the dependent variable is predicted from the combination of independent variables. When a single independent variable is used to predict the value of a dependent variable, it’s called simple linear regression. Clustering.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

Occam's Razor

JANUARY 7, 2019

My professional areas of interest cover Customer Service, User Experience and Finance, though here on Occam’s Razor my focus is on influencing incredible Marketing through the use of innovative Analytics. There is too much goodness in modeling that you are not taking advantage of. Bonus: Reporting kills, analysis thrills.

Marketing Analytics 88

Marketing Analytics Marketing Analytics Strategy 88

Cloudera

SEPTEMBER 5, 2018

Looking at various risk factors to determine the customer’s propensity for money laundering, terrorist financing, and other scenarios. More data sets for longer historical time periods usually means better predictive models. Link analysis. Looking at customer relationships with other entities.

Machine Learning 40

Machine Learning Risk Cost-Benefit Big Data 40

Cloudera

MAY 23, 2024

The image above demonstrates a KMS built using the llama3 model from Meta. This application is contextualized to finance in India. Traditionally, models are measured by comparing predictions with reality, also called “ground truth.” This contextualization is possible thanks to RAG.

Management 66

Management Metrics Data Processing Data Lake 66

Domino Data Lab

JULY 9, 2019

The data science group, in particular, includes people from a “wide variety of intellectual trainings” including cognitive science, physics, finance, applied math, and more. He went into finance for a year, then he was super bored. One of the ways I frame that is, “Are you looking to build a predictive model?

Data Science 112

Data Science Machine Learning Advertising Modeling 112

Smart Data Collective

DECEMBER 12, 2020

An evolving nature of machine learning and unique algorithms are being leveraged within the financial trading industry to compute a large number of data sets to make better and more accurate predictions and to help humans make better and more prudent decisions. In the past, these numbers had to be sorted through by real people.

Big Data 136

Big Data Machine Learning Finance Predictive Modeling 136

datapine

JANUARY 31, 2022

The finances they get from these analytics will be reinvested in the players and their training, which means that players will get better and so will the games. For example, by using prediction models, they are able to generate a heatmap to tell drivers where they should place themselves to take advantage of the best demand areas.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Depict Data Studio

SEPTEMBER 17, 2019

His experience includes evaluation and outcomes studies, ROI analysis, IBNR determination, predictive modeling, risk adjustment methodologies, advanced data visualization, dashboard design and implementation, database development and management, and identifying and evaluating trends and forces in data.

Visualization 40

Visualization Consulting Dashboards Reporting 40

Jet Global

JULY 17, 2023

The column to predict here is the Salary, using other columns in the dataset. If there are missing values in the input columns, we must handle those conditions when creating the predictive model.

Predictive Analytics 52

Predictive Analytics Reporting Software Strategy 52

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. By integrating predictive models into data pipelines, organizations can benefit from actionable insights that drive strategic planning.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

SEPTEMBER 1, 2023

Data-Driven Decision Making: Embedded predictive analytics empowers the development team to make informed decisions based on data insights. By integrating predictive models directly into the application, developers can provide real-time recommendations, forecasts, or insights to end-users.

Predictive Analytics 52

Predictive Analytics Risk Analytics Software 52

Jet Global

MAY 1, 2023

Predictive analytics use a combination of data sets from multiple sources to find relationships and correlations.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52