Tag: data accuracy

Enhancing Efficiency with Upgraded Skip Tracing

Locating individuals quickly and accurately is crucial for debt collectors and lenders. Our skip tracing software addresses these challenges.

February 18, 2025 by Brian Funicelli
Level Up with Data-Driven Marketing Insights

Data-driven marketing insights can help your organization target more accurately and create a better customer experience.

February 21, 2024 by Theresa Nguyen
Addressing the Tax Gap with Artificial Intelligence

Underreported income is a significant budget complication that can frustrate even the most effective tax agencies, until the right tools are used.  

June 9, 2021 by Eric Thompson
Four Key Tips in the Fight Against Fraud for Credit Unions

It’s critical for credit unions to understand the specific threats presented by life online and be prepared with a fraud detection and prevention plan

April 13, 2021 by Kim Le
Utilities Q&A Perspective Series: Maintaining Quality Contact Data Throughout the Customer Lifecycle

By ensuring your organization’s data quality, you can allocate resources more effectively, minimize costs and safely serve your customers. Read more!

February 10, 2021 by Laura Burrows
Data Reporting Under Guidelines Is Better for Consumers Than Data Deletion

Learn how to accurately and consistently report on consumers' credit while complying with regulatory guidance during the COVID-19 pandemic.

April 14, 2020 by Guest Contributor
Are You Ready for the New CFPB Regulation?

The CFPB recently issued a NPRM to implement the FDCPA. If you aren’t ready for the new CFPB regulation, what are you waiting for? Read more!

August 19, 2019 by Laura Burrows
Why You Need to Pay Close Attention to TCPA

Have you seen the latest TCPA class action lawsuit? Now more than ever, it’s crucial to build effective and cost-efficient contact strategies. But how?

July 30, 2019 by Laura Burrows
CECL Q&A with Gavin Harding and Jose Tagunicar

Financial institutions preparing for the launch of the Financial Accounting Standard Board’s (FASB) new current expected credit loss model, or CECL, may have concerns when it comes to preparedness, implications and overall impact. Gavin Harding, Experian’s Senior Business Consultant and Jose Tagunicar, Director of Product Management, tackled some of the tough questions posed by the new accounting standard. Check out what they had to say: Q: How can financial institutions begin the CECL transition process? JT: To prepare for the CECL transition process, companies should conduct an operational readiness review, which includes: Analyzing your data for existing gaps. Determining important milestones and preparing for implementation with a detailed roadmap. Running different loss methods to compare results. Once losses are calculated, you’ll want to select the best methodology based on your portfolio. Q: What is required to comply with CECL? GH: Complying with CECL may require financial institutions to gather, store and calculate more data than before. To satisfy CECL requirements, financial institutions will need to focus on end-to-end management, determine estimation approaches that will produce reasonable and supportable forecasts and automate their technology and platforms. Additionally, well-documented CECL estimations will require integrated workflows and incremental governance. Q: What should organizations look for in a partner that assists in measuring expected credit losses under CECL? GH: It’s expected that many financial institutions will use third-party vendors to help them implement CECL. Third-party solutions can help institutions prepare for the organization and operation implications by developing an effective data strategy plan and quantifying the impact of various forecasted conditions. The right third-party partner will deliver an integrated framework that empowers clients to optimize their data, enhance their modeling expertise and ensure policies and procedures supporting model governance are regulatory compliant. Q: What is CECL’s impact on financial institutions? How does the impact for credit unions/smaller lenders differ (if at all)? GH: CECL will have a significant effect on financial institutions’ accounting, modeling and forecasting. It also heavily impacts their allowance for credit losses and financial statements. Financial institutions must educate their investors and shareholders about how CECL-driven disclosure and reporting changes could potentially alter their bottom line. CECL’s requirements entail data that most credit unions and smaller lenders haven’t been actively storing and saving, leaving them with historical data that may not have been recorded or will be inaccessible when it’s needed for a CECL calculation. Q: How can Experian help with CECL compliance? JT: At Experian, we have one simple goal in mind when it comes to CECL compliance: how can we make it easier for our clients? Our Ascend CECL ForecasterTM, in partnership with Oliver Wyman, allows our clients to create CECL forecasts in a fraction of the time it normally takes, using a simple, configurable application that accurately predicts expected losses. The Ascend CECL Forecaster enables you to: Fulfill data requirements: We don’t ask you to gather, prepare or submit any data. The application is comprised of Experian’s extensive historical data, delivered via the Ascend Technology PlatformTM, economic data from Oxford Economics, as well as the auto and home valuation data needed to generate CECL forecasts for each unsecured and secured lending product in your portfolio. Leverage innovative technology: The application uses advanced machine learning models built on 15 years of industry-leading credit data using high-quality Oliver Wyman loan level models. Simplify processes: One of the biggest challenges our clients face is the amount of time and analytical effort it takes to create one CECL forecast, much less several that can be compared for optimal results. With the Ascend CECL Forecaster, creating a forecast is a simple process that can be delivered quickly and accurately. Q: What are immediate next steps? JT: As mentioned, complying with CECL may require you to gather, store and calculate more data than before. Therefore, it’s important that companies act now to better prepare. Immediate next steps include: Establishing your loss forecast methodology: CECL will require a new methodology, making it essential to take advantage of advanced statistical techniques and third-party solutions. Making additional reserves available: It’s imperative to understand how CECL impacts both revenue and profit. According to some estimates, banks will need to increase their reserves by up to 50% to comply with CECL requirements. Preparing your board and investors: Make sure key stakeholders are aware of the potential costs and profit impacts that these changes will have on your bottom line. Speak with an expert

June 12, 2019 by Laura Burrows
Four Features You Need in an Analytical Environment

Any analytical environment is only as good as the data you put into it. Check these four key features when choosing the right one for your organization.

October 24, 2018 by Jesse Hoggard
Getting Beyond the Binary to Solve the Business Problem of Big Data

You want to use big data, but how do you make your analytics truly actionable to stay ahead of the competition? Using an analytical sandbox is the answer.

October 4, 2018 by Jesse Hoggard
Is Big Data a Big Problem?

There are a lot of people talking about big data who are not fully leveraging the value of their data. How do you use data to innovate and stay competitive?

September 27, 2018 by Jesse Hoggard
Dispute Rates Rising? Five Ways to Uncover Data Inaccuracies

Consumer disputes aren’t going away, but understanding the reported data and metrics behind disputes can help data furnishers minimize them and improve processes.

February 27, 2018 by Shelly Shakespeare
Financial Services Regulations: A look back and a look ahead

The mortgage meltdown and Great Recession have translated into big shifts as it relates to financial services regulations. What's to come with a new administration coming soon?

November 3, 2016 by Kerry Rivera
Data accuracy should start with proactive solutions

While organizations increasingly rely on data to make decisions, when it comes to data accuracy, too many wait to correct errors rather than implement proactive solutions.

June 23, 2016 by Kerry Rivera

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