Tag: 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

The CU Times recently reported on a nationwide synthetic identity fraud ring impacting several major credit unions and banks.

Time is the only resource we can’t get more of, which is why we obsess over saving it. Over the last several years, a new time saver has emerged – APIs.

Experian is excited to once again take part in the 2019 CUNA Lending Council Conference, an event that brings together the credit union movement’s best and brightest in lending.

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

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

With Hispanic Heritage Awareness Month underway and the topic of growing membership a constant priority, here are some tips from a credit union CEO.

All communities are impacted by the contributions of Hispanics, and now is the time for FIs to reflect upon their largest growth opportunity.

In the financial services universe, there is no shortage of players battling for consumer attention and share of wallet. Here’s a look at how credit unions have fared over the past two years compared to banks and online lenders:

Experian took a deep dive into the data and performance surrounding the credit union universe in their first-ever “State of Credit Unions” report, featuring insights utilizing data from both 2015 and 2017.

For an industry that has grown accustomed to sustained year-over-year growth, recent trends are concerning. The automotive industry continued to make progress in the fourth quarter of 2016 as total automotive loan balances grew 8.6% over the previous year and exceeded $1 trillion. However, the positive trend is slowing and 2017 may be the first year since 2009 to see a market contraction. With interest rates on the rise and demand peaking, automotive lending will continue to become more competitive. Lenders can be successful in this environment, but must implement data-driven targeting strategies. Credit Unions Triumph Credit unions experienced the largest year-over-year growth in the fourth quarter of 2016, increasing 15% over the previous period. As lending faces increasing headwinds amid rising rates, credit unions can continue to play a greater role by offering members more competitive rates. For many consumers, a casual weekend trip to the auto mall turns into a big new purchase. Unfortunately, many get caught up in researching the vehicle and don’t think to shop for financing options until they’re in the F&I office. With approximately 25% share of total auto loan balances, credit unions have significant potential to recapture loans of existing members. Successful targeting starts with a review of your portfolio for opportunities with current members who have off-book loans that could be refinanced at a lower rate. After developing a strategy, many credit unions find success targeting these members with refinance offers. Helping members reduce monthly payments and interest expense provides an unexpected service that can deepen loyalty and engagement. But what criteria should you use to identify prospects? Target Receptive Consumers As originations continue to slow, marketing response rates will as well, leading to reduced marketing ROI. Maintaining performance is possible, but requires a proactive approach. Propensity models can help identify consumers who are more likely to respond, while estimated interest rates can provide insight on who is likely to benefit from refinance offers. Propensity models identify who is most likely to open a new trade. By focusing on these populations, you can cut a mail list in half or more while still focusing on the most viable prospects. It may be okay in a booming economy to send as many offers as possible, but as things slow down, getting more targeted can maintain campaign performance while saving resources for other projects. When it comes to recapture, consumers refinance to reduce their payment, interest rate, or both. Payments can often be reduced simply by ‘resetting’ the clock on a loan, or taking the remaining balance and resetting the term. Many consumers, however, will be aware of their current interest rate and only consider offers that reduce the rate as well. Estimated interest rates can provide valuable insight into a consumer’s current terms. By targeting those with high rates, you are more likely to make an offer that will be accepted. Successful targeting means getting the right message to the right consumers. Propensity models help identify “who” to target while estimated interest rates determine “what” to offer. Combining these two strategies will maximize results in even the most challenging markets. Lend Deeper with Trended Data Much of the growth in the auto market has been driven by relatively low-risk consumers, with more than 60% of outstanding balances rated prime and above. This means hypercompetition and great rates for the best consumers, while those in lower risk tiers are underserved. Many lenders are reluctant to compete for these consumers and avoid taking on additional risk for the portfolio. But trended data holds the key to finding consumers who are currently in a lower risk tier but carry significantly less risk than their current score suggests. In fact, historical data can provide much deeper insight on a consumer’s past use of credit. As an example, consider two consumers with the same risk score at a point in time. While they may be judged as carrying similar risk, trended data shows one has taken out two new trades in the past 6 months and has increasing utilization, while the other is consolidating and paying down balances. They may have the same risk score today, but what will the impact be on your future profitability? Most risk scores take a snapshot approach to gauging risk. While effective in general, it misses out on the nuance of consumers who are trending up or down based on recent behavior. Trended data attributes tell a deeper story and allow lenders to find underserved consumers who carry less risk than their current score suggests. Making timely offers to underserved consumers is a great way to grow your portfolio while managing risk. Uncertain Future The automotive industry has been a bright spot for the US economy for several years. It’s difficult to say what will happen in 2017, but there will likely be a continued slowing in originations. When markets get more competitive, data-driven targeting becomes even more important. Propensity models, estimated interest rates, and trended data should be part of every prescreen campaign. Those that integrate them now will likely shrug off any downturn and continue growing their portfolio by providing valuable and timely offers to their members.

Using digital technology like a big bank How was your holiday? Are the chargebacks rolling in yet? It’s no secret - digital technology like mobile device usage has increased significantly over the years, making it a breeding ground for fraudsters. As credit unions continue to grow their membership, their fraud security treatments need to grow as well. Bigger banks are constantly updating their fraud tools and strategies to fight against cybercrime and, therefore, fraudsters are setting their eyes on credit unions. Even as I write this, fraudsters are searching and targeting credit unions that don’t have their mobile channel secured. They attempt to capitalize on any weakness or opportunity: Registering stolen cards to mobile wallets Taking over an account via mobile banking apps Using a retailers’ mobile app to make fraudulent payments Disabling the SIM card in the victim’s phone and diverting the one-time password sent through text message to their own phones These are clever ways to commit fraud. But credit unions are becoming wise to these new threats and are serious about protecting their members. They are incorporating device intelligence with a solid identity authentication service. This multi-layered approach is essential to securing mobile channels, and protecting your Credit Union from chargebacks. To learn more about our fraud solutions, click here.

The pressures for both credit unions and banks, to generate returns to drive greater earnings are ever present. According to recent data released by the National Credit Union Administration, the nation's 7,019 federally-insured credit unions added 667,000 new members in the first quarter of 2012 to a record of 92.5 million. To offset these pressures, portfolio managers are aggressively expanding their policies and practices to drill more deeply and frequently into their portfolios. Increasingly, this requires the ability to trend consumer credit data, identify specific member metrics, and track those changes over time. Redefining the information your portfolios provide can by key to developing increased ROI. Learn how trended data can help you maximize your strategies and process to produce results in today's complex business environments. Source: How to drill deeper into your portfolio

Despite low demand and a shrinking pool of qualified candidates, loan growth priorities continue to rank high for most small-business lenders – both for small to midsize banks and large financial institutions. Between 2006 and 2010, overall loan applications were down 5 percent where large financial institutions saw small-business loan applications rise 36.5 percent. Banks and credit unions with assets less than $500 million showed the most significant increase of 65 percent. Read more of the blog series: "Getting back in the game – Generating small business applications." Source: Decision Analytics' Blog: Relationship and Transactional Lending Best Practices