Data & Analytics

Learn how Experian's Credit + Cashflow Score leads to a 40% improvement in predictive accuracy compared with conventional credit models. 

Fintech analytics transforms fragmented data into real-time decisioning power, helping lenders manage risk and earn consumer trust.

Discover how data-driven risk management strategies are transforming credit risk management in the fintech industry.

Tenant screening fraud is rising fast. Discover how income verification tools, Experian income verification, and AI-powered document upload strengthen fraud detection and streamline employment checks.

Mid-sized banks should take a data-driven approach to implementing credit risk strategies if they want to expand their loan portfolios.

As financial behavior becomes more dynamic, real-time data is emerging as a powerful tool in reshaping how lenders assess risk.

Discover how cashflow data empowers lenders to gain behavioral insights into consumers, expand market reach and make more precise decisions.

Financial institutions can unlock value through analytics to gain insights that drive smarter decisions and better business results.

A unified data strategy can help unlock the full potential of an organization’s ability to turn raw data into actionable insights.

Experian and Plaid are teaming up to power smarter, faster, and more inclusive lending — fueled by real-time cashflow insights.

For financial institutions to achieve success, they need to develop high-performing models with easy access to top-tier data sources. It’s also important to focus on data governance, compliance, and risk management throughout the lending lifecycle. Industry leaders implement advanced analytics and AI solutions to improve their lending decisions, and they also incorporate integrated, efficient feature engineering into their business operations. What’s feature engineering? Feature engineering helps organizations turn raw data into comprehensive model development, following this process: Data collection Data cleaning and transformation Feature engineering Model training and evaluation Decision-making Effectively transforming data into valuable insights depends heavily on creating new custom features to enhance model performance, as well as the quality of the data being used. When data is fragmented or managed poorly, it can lead to increased operational costs, missed revenue opportunities, and compliance risks. Our feature engineering solution: Experian Feature Builder Financial institutions require optimized workflows that can accelerate development while supporting governance and ensuring transparency. Experian’s feature engineering tool, Experian Feature Builder, streamlines custom feature development and deployment across the modeling lifecycle. Providing access to 20+ years of proprietary data, Experian Feature Builder enables organizations to: Break data silos by creating unified access across multiple data types Ensure trust and compliance by embedding audit and lineage tracking at each stage Enable strategic agility with faster and more consistent feature experimentation, testing, and deployment Download our latest e-book to find out more about how Experian’s Feature Builder provides centralized feature development to accelerate time-to-market, enhance compliance, and minimize risk. Download the e-book

Industry leaders are leveraging GenAI technology to accelerate the modeling lifecycle, streamline workflows and ensure regulatory compliance.

By integrating feature engineering, organizations can convert raw data into more accurate features and build higher-performing models.

By leveraging loan loss analysis, lenders can create more profitable business opportunities throughout the entire customer lifecycle.

During economic uncertainty, lenders can leverage retention triggers to proactively engage customers and reduce churn.