Fintech

Fintech

The Long-Term Impacts of the Great Recession

Americans of all ages have felt the effects of the Great Recession, making it imperative to begin recession proofing for the next economic downturn.

Published: July 22, 2019 by Laura.Burrows@experian.com
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

Published: June 12, 2019 by Laura.Burrows@experian.com
Q1 2019 Consumer Credit Trends

Consumer credit trends are continuously changing, making it imperative to keep up with the latest developments in originations, delinquencies on mortgages, credit cards and auto loans. By monitoring consumer behavior and market trends over time, you can predict and prepare for potential issues within each market. In this 30-minute webinar, our featured speakers, Gavin Harding, Experian Senior Business Consultant, and Alan Ikemura, Experian Data Analytics Senior Product Manager, reveal Q1 2019 market intelligence data and explore recent advances in consumer credit trends. Watch our on-demand webinar

Published: June 4, 2019 by Laura.Burrows@experian.com
Right Place, Wrong Time: Are You Leaving Customers Waiting?

You’ve Got Mail! Probably a lot of it. Birthday cards from Mom, a graduation announcement from your third cousin’s kid whose name you can’t remember and a postcard from your dentist reminding you you’re overdue for a cleaning. Adding to your pile, are the nearly 850 pieces of unsolicited mail Americans receive annually, according to Reader’s Digest. Many of these are pre-approval offers or invitations to apply for credit cards or personal loans. While many of these offers are getting to the right mailbox, they’re hitting a changing consumer at the wrong time. The digital revolution, along with the proliferation and availability of technology, has empowered consumers. They now not only have access to an abundance of choices but also a litany of new tools and channels, which results in them making faster, sometimes subconscious, decisions. Three Months Too Late The need to consistently stay in front of customers and prospects with the right message at the right time has caused a shortening of campaign cycles across industries. However, for some financial institutions, the customer acquisition process can take up to 120 days! While this timeframe is extreme, customer prospecting can still take around 45-60 days for most financial institutions and includes: Bureau processing: Regularly takes 10-15 days depending on the number of data sources and each time they are requested from a bureau. Data aggregation: Typically takes anywhere from 20-30 days. Targeting and selection: Generally, takes two to five days. Processing and campaign deployment: Usually takes anywhere from three days, if the firm handles it internally, or up to 10 days if an outside company handles the mailing. A Better Way That means for many firms, the data their customer acquisition campaigns are based off is at least 60 days old. Often, they are now dealing with a completely different consumer. With new card originations up 20% year-over-year in 2019 alone, it’s likely they’ve moved on, perhaps to one of your competitors. It’s time financial institutions make the move to a more modern form of prospecting and targeting that leverages the power of cloud technology, machine learning and artificial intelligence to accelerate and improve the marketing process. Financial marketing systems of the future will allow for advanced segmentation and targeting, dynamic campaign design and immediate deployment all based on the freshest data (no more than 24-48 hours old). These systems will allow firms to do ongoing analytics and modeling so their campaign testing and learning results can immediately influence next cycle decisions. Your customers are changing, isn’t it time the way you market to them changes as well?

Published: May 29, 2019 by Jesse Hoggard
Leveraging Alternative Data to Improve Financial Access

Millions of consumers lack credit history and/or have difficulty obtaining credit from mainstream financial institutions. To ease access to credit for “invisible” and below prime consumers, financial institutions have sought ways to both extend and improve the methods by which they evaluate borrowers’ risk. This initiative to effectively score more consumers has involved the use of alternative credit data.1 Alternative credit data is FCRA-compliant data that is typically not included in a traditional credit report and is used to deliver a more complete view into a consumer’s creditworthiness. “Alternative credit data helps us paint a fuller picture of a consumer so they can get better access to the financial services they need and deserve,” said Alpa Lally, Vice President of Data Business at Experian. Experian recently sponsored the FinovateSpring conference in San Francisco, where Alpa had a chance to sit down with Jacob Gaffney, Editor-in-Chief of the HousingWire News Podcast, to discuss ways consumers can improve their credit scores. As an immigrant, Alpa spoke personally about the impact of having a limited credit history and how alternative credit data can help drive greater access to credit for consumers and profitable growth for lenders through more informed lending decisions. Highlights include: How alternative and traditional credit data differ Types of alternative credit data being used by lenders How “credit-invisibles” can best leverage alternative credit data Alternative credit data product solutions, including Experian BoostTM Listen now 1When we refer to “Alternative Credit Data,” this refers to the use of alternative data and its appropriate use in consumer credit lending decisions, as regulated by the Fair Credit Reporting Act. Hence, the term “Expanded FCRA Data” may also apply in this instance and both can be used interchangeably.

Published: May 17, 2019 by Laura.Burrows@experian.com
To Win with Machine Learning, It Isn’t What You Do; It’s How You Do It

To win with ML, the team and process are more important than the algorithm. Best practices before, during and after modeling to help you succeed.

Published: April 24, 2019 by Jim Bander
Experian’s Ascend Analytical Sandbox™ Named Best Overall Analytics Platform in Fintech Competition

Experian wins for a second year in a row at coveted Fintech Breakthrough Award program, which received more than 3,500 nominations from across the globe.

Published: April 3, 2019 by Brittany Peterson
How Experian is Helping Fintechs Tighten Their Fraud Risk Strategies

Regulatory trends, risk mitigation and customer trust are all critical to fintech fraud risk strategies and were discussed at a recent Experian panel.

Published: February 19, 2019 by Brittany Peterson
Experian: Powering Innovative Fintech Solutions

Today's world demands finance redefined - and fintechs have answered the call. Driven by innovative technology and data, what's next for fintechs?

Published: February 14, 2019 by Brittany Peterson
Alt Data Use by Fintechs: Q&A with Gavin Harding (Part 2)

Gavin Harding, Senior Business Consultant, continues in this Q&A with insight that spans across all lenders and their use of alternative data.

Published: November 1, 2018 by Brittany Peterson
Fintechs: Thinking of Partnering with Other FIs?

A recent report showcases the results of what happens with FinTechs and financial institutions partner together. Hear their experiences with collaboration.

Published: October 23, 2018 by Brittany Peterson
The Evolution of FinTech: Marketplace Challenger to Industry Collaborator

FinTechs first entered the marketplace as competitors, but as they grow, some have started to partner with traditional financial institutions.

Published: October 16, 2018 by Stefani Wendel
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.

Published: October 4, 2018 by Jesse Hoggard
Machine Learning for Real-World Credit Risk

Machine learning's ability to consume vast amounts of data to uncover patterns and deliver results makes it well suited for the credit risk industry

Published: September 12, 2018 by Alan Ikemura

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