Tag: case study

Evolving technologies and rising consumer expectations for fast, frictionless experiences highlight an opportunity for credit unions to advance their decisioning and stand out in a crowded market. How a credit union is optimizing their decision-making process With over $7.2 billion in assets and 330,000 members, Michigan State University Federal Credit Union (MSUFCU) aims to provide superior service to their members and employees. Initially reliant on manual reviews, the credit union needed a well-designed decisioning strategy that could help them grow their loan portfolio, increase employee efficiency, and reduce credit risk. The credit union implemented Experian’s decisioning platform, PowerCurve® Originations, to make faster, more accurate credit decisions on their secured and unsecured personal loans, leading to increased approvals and an exceptional member experience. “Day one of using PowerCurve produced a 49% automation rate! We have received amazing feedback from our teams about what a great product was chosen,” said Blake Johnson, Vice President of Lending, Michigan State University Federal Credit Union. After implementing PowerCurve Originations, MSUFCU saw an average monthly automation rate of more than 55% and decreased their application processing time to less than 24 hours. Read the full case study for more insight on how Experian can help power your decisioning to grow your business and member relationships. Download case study

 With nearly seven billion credit card and personal loan acquisition mailers sent out last year, consumers are persistently targeted with pre-approved offers, making it critical for credit unions to deliver the right offer to the right person, at the right time. How WSECU is enhancing the lending experience As the second-largest credit union in the state of Washington, Washington State Employees Credit Union (WSECU) wanted to digitalize their credit decisioning and prequalification process through their new online banking platform, while also providing members with their individual, real-time credit score. WSECU implemented an instant credit decisioning solution delivered via Experian’s Decisioning as a ServiceSM environment, an integrated decisioning system that provides clients with access to data, attributes, scores and analytics to improve decisioning across the customer life cycle. Streamlined processes lead to upsurge in revenue growth   Within three months of leveraging Experian’s solution, WSECU saw more members beginning their lending journey through a digital channel than ever before, leading to a 25% increase in loan and credit applications. Additionally, member satisfaction increased with 90% of members finding the simplified process to be more efficient and requiring “low effort.” Read our case study for more insight on using our digital credit solutions to: Prequalify members in real-time at point of contact Match members to the right loan products Increase qualification, approval and take rates Lower operational and manual review costs Read case study

  In today’s evolving and competitive market, the stakes are high to deliver both quantity and quality. That is, to deliver growth goals while increasing customer satisfaction. OneAZ Credit Union is the second largest credit union in Arizona, serving over 157,000 members across 21 branches. Wanting to fund more loans faster and offer a better member experience through their existing loan origination system (LOS), OneAZ looked to improve their decisioning system and long-standing underwriting criteria. They partnered with Experian to create an automated underwriting strategy to meet their aggressive approval rate and loss rate goals. By implementing an integrated decisioning system, OneAZ had flexible access to data credit attributes and scores, resulting in increased automation through their existing LOS – meaning they didn’t have to completely overhaul their decisioning systems. Additionally, they leveraged software that enabled champion/challenger strategies and the flexibility to manage their decision criteria. Within one month of implementation, OneAZ saw a 26% increase in loan funding rates and a 25% decrease in manual reviews. They can now pivot quickly to respond to continuously evolving conditions. “The speed at which we can return a decision and our better understanding of future performance has really propelled us in being able to better serve our members,” said John Schooner, VP Credit Risk Management at OneAZ. Read our case study for more insight on how automation and PowerCurve Originations Essentials can move the needle for your organization, including: Streamlined strategy development and execution to minimize costly customizations and coding Comprehensive data assets across multiple sources to ensure ID verification and a holistic view of your prospect Proactive monitoring and real-time visibility to challenge and rapidly adjust strategies as needed Download the full case study

The tax gap—the difference between what taxpayers should pay and what they actually pay on time—can have a substantial impact on states’ budgets. Tax agencies and other state departments are responsible for helping states manage their budgets by minimizing expected revenue shortfalls. Underreported income is a significant budget complication that continues to frustrate even the most effective tax agencies, until the right tools are brought into play.   The Problem Underreporting is a large, complex issue for agencies. The IRS currently estimates the annual tax gap at $441 billion. There are multiple factors that comprise that total, but the most prevalent is underreporting, which represents 80% of the total tax gap. Of that, 54% is due to underreporting of individual income tax. In addition to being the largest contributor to the tax gap, underreporting is also extremely challenging to identify out of the millions of returns being filed. With 85% of taxes owed correctly reported and paid, finding underreporting can be like trying to locate a needle in the proverbial haystack. Making this even more challenging is the limited resources available for auditing returns, which makes efficiency key. The Solution Data, combined with artificial intelligence (AI) equals efficient detection. The problem with trying to detect which returns are most likely to have underreported income is similar to many other challenges Experian has solved with AI. Partnerships between Experian and state agencies combine what we know about consumers with what their agency knows about their population. We can take the data and use AI to separate the signal from the noise, finding opportunities to recoup lost revenue. Read our case study on how Experian was able to help an agency identify instances of underreporting, detecting an estimated $80 million annual lost revenue from underreported income. Download case study Contact us

Today’s lending market has seen a significant increase in alternative business lending, with companies utilizing new data assets and technology. As the lending landscape becomes increasingly competitive, consumers have more choices than ever when it comes to lending products. To drive profitable growth, lenders must find new ways to help applicants gain access to the loans they need. How Spring EQ is leveraging Experian BoostTM Home equity lender Spring EQ turned to Experian’s first-of-its-kind financial tool that empowers consumers to add positive payments directly into their credit file to assist applicants with attaining the best loan opportunities and rates. By using Experian BoostTM, which captures the value of consumer’s utility and telecom trade lines, in their current lending process, Spring EQ can help applicants near approval or risk thresholds move to higher risk tiers and qualify for better loan terms and conditions. Driving growth with consumer-permissioned data Over 40 million consumers in the U.S. either have no credit file or have insufficient information in their files to generate a traditional credit score. Consumer-permissioned data empowers these individuals to leverage their online financial data and payment histories to gain better access to loans and other financial services while providing lenders with a more comprehensive view of their creditworthiness. According to Experian research, 70% of consumers see the benefits of sharing additional financial information and contributing positive payment history to their credit file if it increases their odds of approval and helps them access more favorable credit terms. Read our case study for more insight on using Experian Boost to: Make better lending decisions Offer or underwrite credit to more people Promote the right credit products Increase conversion and utilization rates Read case study Learn more about Experian Boost

Digital channels undoubtedly create convenient experiences for consumers. We have the luxury of applying for loans or creating investment accounts from the comfort of home. However, the same opportunities are available to fraudsters. Fraudsters continue to find creative and innovative ways to expose vulnerabilities across all types of businesses. They prey on inexperienced or low-bandwidth teams that have not invested in the appropriate fraud tools in the past. Despite the imminent fraud risk involved, both consumers and businesses continue to embrace digital channels. With 90 percent of consumers worldwide conducting personal banking online, how do we protect these digital platforms with finite resources? A leading digital financial services company was forced to address this question when they experienced a large-scale fraud attack. But they weren’t in this fight alone. Download the full case study to see how our risk analyst used FraudNet to prevent millions of dollars in fraudulent funding. Client: A leading digital financial services company that operates with zero in-person branches with more than 7,000 employees Challenge/Objective: In October 2018, fraudsters deployed a large-scale, scripted attack against a North American financial services company. The fraud team was extremely understaffed. The fraud team was unable to detect and respond to the attack quickly. The fraudulent account opening activities eventually blended into account takeovers. Resolution: Our risk analyst worked quickly to analyze the geolocation, velocity and device rules firing within FraudNet for Account Opening. By having these rules in place, FraudNet was able to flag and outsort thousands of suspicious applications. Despite being a small team, the fraud investigators were able to work efficiently within the FraudNet workbench and review the true, high-risk applications. Results: Thanks to our risk analyst’s quick remediation and the FraudNet proprietary device rules: 23,800 fraudulent applications were outsorted for review. An estimated $35.7 million in fraudulent funding was prevented. However, the fight against fraud is ongoing. Our risk analyst continues to work closely with the fraud team to develop an effective strategy to prepare against future attacks.

At Experian, we know that fintechs don’t just need big data – they need the best data, and they need that data as quickly as possible. Successfully delivering on this need is one of the many reasons we’re proud to be selected as a Fintech Breakthrough Award winner for the second consecutive year. The Fintech Breakthrough Awards is the premier awards program founded to recognize fintech innovators, leaders and visionaries from around the world. The 2019 Fintech Breakthrough Award program received more than 3,500 nominations from across the globe. Last year, Experian took home the Consumer Lending Innovation Award for our Text for Credit Solution – a powerful tool for providing consumers the convenience to securely bypass the standard-length ‘pen & paper’ or keystroke intensive credit application process while helping lenders make smart, fraud protected lending decisions. This year, we are excited to announce that Experian’s Ascend Analytical Sandbox™ has been selected as winner in the Best Overall Analytics Platform category. “We are thrilled to be recognized by Fintech Breakthrough for the second year in a row and that our Ascend Analytical Sandbox has been recognized as the best overall analytics platform in 2019,” said Vijay Mehta, Experian’s Chief Innovation Officer. “We understand the challenges fintechs face - to stay ahead of constantly changing market conditions and customer demands,” said Mehta. “The Ascend Analytical Sandbox is the answer, giving financial institutions the fastest access to the freshest data so they can leverage the most out of their analytics and engage their customers with the best decisions.” Debuting in 2018, Experian’s Ascend Analytical Sandbox is a first-to-market analytics environment that moved companies beyond just business intelligence and data visualization to data insights and answers they could actually use. In addition to thousands of scores and attributes, the Ascend Analytical Sandbox offers users industry-standard analytics and data visualization tools like SAS, R Studio, Python, Hue and Tableau, all backed by a network of industry and support experts to drive the most answers and value out of their data and analytics. Less than a year post-launch, the groundbreaking solution is being used by 15 of the top financial institutions globally. Early Access Program Experian is committed to developing leading-edge solutions to power fintechs, knowing they are some of the best innovators in the marketplace. Fintechs are changing the industry, empowering consumers and driving customer engagement like never before. To connect fintechs with the competitive edge,  Experian launched an Early Access Program, which fast-tracks onboarding to an exclusive market test of the Ascend Analytical Sandbox. In less than 10 days, our fintech partners can leverage the power, breadth and depth of Experian’s data, attributes and models. With endless use cases and easy delivery of portfolio monitoring, benchmarking, wallet share analysis, model development, and market entry, the Ascend Analytical Sandbox gives fintechs the fastest access to the freshest data so they can leverage the most out of their analytics and engage their customers with the best decisions. A Game Changer for the Industry In a recent IDC customer spotlight, OneMain Financial reported the Ascend Analytical Sandbox had helped them reduce their archive process from a few months to 1-2 weeks, a nearly 75% time savings. “Imagine having the ability to have access to every single tradeline for every single person in the United States for the past almost 20 years and have your own tradelines be identified among them. Imagine what that can do,” said OneMain Financial’s senior managing director and head of model development. For more information, download the Ascend Analytical Sandbox™ Early Access Program product sheet here, or visit Experian.com/Sandbox.

From a capricious economic environment to increased competition from new market entrants and a customer base that expects a seamless, customized experience, there are a host of evolving factors that are changing the way financial institutions operate. Now more than ever, financial institutions are turning to their data for insights into their customers and market opportunities. But to be effective, this data must be accurate and fresh; otherwise, the resulting strategies and decisions become stale and less effective. This was the challenge facing OneMain Financial, a large provider of personal installment loans serving 10 million total customers across more than 1,700 branches—creating accurate, timely and robust insights, models and strategies to manage their credit portfolios. Traditionally, the archive process had been an expensive, time-consuming, and labor-intensive process; it can take months from start to finish. OneMain Financial needed a solution to reduce expenses and the time involved in order to improve their core risk modeling.   In this recent IDC Customer Spotlight, sponsored by Experian, "Improving Core Risk Modeling with Better Data Analysis," Steven D’Alfonso, Research Director spoke with the Senior Managing Director and head of model development at OneMain Financial who turned to Experian’s Ascend Analytical Sandbox to improve its core risk modeling through reject inferencing. But OneMain Financial also realized additional benefits and opportunities with the solution including compliance and economic stress testing. Read the customer spotlight to learn more about the explore how OneMain Financial: Reduced expense and effort associated with its archive process Improved risk model development timing from several months to 1-2 weeks Used Sandbox to gain additional market insight including: market share, benchmarking and trends, etc. Read the Case Study

It’s the holiday season — time for jingle bells, lighting candles, shopping sprees and credit card fraud. But we’re prepared. Our risk analyst team constantly monitors our FraudNet solution performance to identify anomalies our clients experience as millions of transactions occur this month. At its core, FraudNet analyzes incoming events to determine the risk level and to allow legitimate events to process without causing frustrating friction for legitimate customers. That ensures our clients can recognize good customers across digital devices and channels while reducing fraud attacks and the need for internal manual reviews. But what happens when things don’t go as planned? Here’s a recent example. One of our banking clients noticed an abnormally high investigation queue after a routine risk engine tuning. Our risk analyst team looked further into the attacks to determine the cause and assess whether it was a tuning issue or a true fraud attack. After an initial analysis, the team learned that the events shared many of the same characteristics: Came from the same geo location that has been seen in previous attacks on clients Showed suspicious device and browser characteristics that were recognized by Experian’s device identification technology Identified suspicious patterns that have been observed in other recent attacks on banks The conclusion was that it wasn’t a mistake. FraudNet had correctly identified these transactions as suspicious. Experian® then worked with our client and recommended a strategy to ensure this attack was appropriately managed. This example highlights the power of device identification technology as a mechanism to detect emerging fraud threats, as well as link analysis tools and the expertise of a highly trained fraud analyst to uncover suspicious events that might otherwise go unnoticed. In addition to proprietary device intelligence capabilities, our clients take advantage of a suite of capabilities that can further enhance a seamless authentication experience for legitimate customers while increasing fraud detection for bad actors. Using advanced analytics, we can detect patterns and anomalies that may indicate a fraudulent identity is being used. Additionally, through our CrossCore® platform businesses can leverage advanced innovation, such as physical and behavioral biometrics (facial recognition, how a person holds a phone, mouse movements, data entry style), email verification (email tenure, reported fraud on email identities), document verification (autofill, liveliness detection) and digital behavior risk indicators (transaction behavior, transaction velocity), to further advance their existing risk mitigation strategies and efficacy.   With expanding partnerships and capabilities offered via Experian’s CrossCore platform, in conjunction with consultative industry expertise, businesses can be more confident during the authentication process to ensure a superb, frictionless customer experience without compromising security.