Jie (Jay) Liu

Consumer Financial Protection Bureau (CFPB) subjecting large payment apps to the same supervision and regulation as banks, what specific areas will the CFPB monitor, and how might payment apps respond to these new regulations? Areas the CFPB Will Monitor: Privacy and Surveillance: The CFPB will ensure that large payment apps comply with regulations  regarding data collection and sharing. Consumers must be able to opt-out of certain data practices and be informed about how their data is used. Errors and Fraud: The CFPB will monitor how payment apps handle transaction disputes and fraud. Apps must manage disputes internally rather than shifting them to banks or credit card companies. Debanking: The CFPB will oversee how payment apps handle account closures and freezes. Ensuring that consumers do not face unexpected disruptions in their ability to make or receive payments is a priority. How Payment Apps Might Respond: Compliance Enhancements: Payment apps will have to pul their socks and invest in improving their compliance frameworks to meet the new regulatory requirements. This includes better data privacy measures, robust fraud detection systems, and efficient dispute resolution processes. Operational Adjustments: Companies may need to adjust their operational procedures to handle disputes internally and avoid relying on external financial institutions. This could involve upgrading their customer service capabilities and dispute management systems. Lobbying and Legal Challenges: Big Tech companies might lobby against the new regulations, arguing that they are overly burdensome or unnecessary. Legal challenges could also arise, potentially delaying the implementation of the rules. In my opinion this approach can be implemented by the regional and local regulatory bodies such as #Central #banks The regional  and local regulators could adapt similar regulatory measures to oversee large payment apps in the region. Establishing a Regulatory Framework: Developing a comprehensive regulatory framework specifically for payment apps. Defining clear guidelines and standards for data security, consumer protection, and compliance. Creating a Dedicated Oversight Body: Establishing a dedicated department within the governing body to monitor and regulate payment apps. Implementing Compliance Requirements: Requiring payment apps to adhere to AML, KYC, and other financial regulations. Mandating regular audits and reporting to ensure compliance. Promoting Transparency and Consumer Rights: Ensuring payment apps provide transparent information to consumers about their services. Protecting consumer rights by enforcing fair practices and efficient dispute resolution mechanisms. By adopting these measures, the local regulator can ensure that payment apps operate in a secure, transparent, and consumer-friendly manner, similar to the objectives of the CFPB. #CFPB Central Bank of Oman Mala'a #payments #privacy #Surveillance #Debanking #Compliance

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Researchers at the Federal Reserve just published an interesting FEDS note, providing more granular insight into rising #auto lending delinquency rates. As the authors point out, auto loans account for about 25% of non-mortgage consumer credit, so understanding auto defaults is a good window into understanding overall consumer financial health. Takeaways that struck me: 1. Most of the deliquencies are from loans originated in 2022 or afterwards. (Even notwithstanding the fact that 64% of auto loans were originated in the last two years, loans originated in 22-23 have steeper delinquency rates than other vintages.) 2. The rise in deliquencies appears to be heavily driven by increasing loan sizes. Other research, including recent Consumer Financial Protection Bureau blogs, have highlighted the role of larger payments in the rising deliquencies. But the Fed authors now disintangle the components of the larger payment: they show it’s not higher interest rates, but instead higher loan amounts. Said another way, due to pandemic-era supply constraints and demand-side consumers being flush with stimulus cash “As car prices surged, car buyers sought larger loans.” 3. The not-so-great news is some of the loan size growth is due to auto lenders, IN THE AGGREGATE, loosening their underwriting standards. “The increase in loan amount likely reflects the interactions of both credit supply and demand factors: borrowers demanded larger loans amid the run-up in car prices from mid-2020 to mid-2023 and lenders, in aggregate, appeared to relax their credit standards to originate these loans.” 4. But, as James Mulholland smartly pointed out earlier today, the authors find that banks tightened their auto lending in 2022-23. (!!!) Instead, credit unions and non-bank finance rushed in with looser loans . . . leading consumers (and the broader economy) to the trendlines that we’re seeing today. Here’s the relevant quote, with footnotes omitted: “[T]he composition of lenders originating auto loans changed significantly during this period. Banks, which held about 35 percent of loans outstanding in the auto market in 2019, appeared to tighten standards and pull back from lending in 2022 and 2023. At the same time, credit unions and finance companies stepped in and filled this gap. In particular, independent finance companies experienced increases in originations and, as of the end of 2023, accounted for a greater share of originations. These companies are not affiliated with a car manufacturer and tend to focus on riskier segments of the population, as evidenced by both higher loan-to-value ratios and higher delinquencies. As a result, their loans tend to have higher delinquencies and their LTV ratios, on average, are currently about 40 percentage points higher than those of banks.” #Boom #perShaggyItwasntme #regulatoryperimetermuch? https://lnkd.in/eH3ENCKJ

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🚨 From Modern Redlining Maps to Data Gaps: What’s Hiding in Your HMDA Data? 🚨 HMDA reporting season is just around the corner, and your Loan Application Register (LAR) data tells a story. Today’s redlining challenges may not involve old maps, but they can still highlight patterns of inequity in lending. Are you confident your data reflects fairness—or could it raise questions? Fair Lending is about more than just meeting regulatory requirements; it’s about ensuring your practices build trust, serve your community, and withstand scrutiny. At MQMR, we specialize in helping lenders: ✅ Identify and address redlining risks ✅ Analyze lending patterns for equitable practices ✅ Turn potential pitfalls into opportunities for growth Your data has the power to either protect your reputation—or put it at risk. Let’s work together to ensure it tells the right story. 📊 Ready to dig into your LAR data? We’re here to help. #MQMR #FairLending #RedliningRisks #HMDACompliance #MortgageIndustry

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Another great post from Melinda Roy on discovering that data governance is already happening at your institution, just in less formalized ways. This article describes how you can match data governance roles to existing higher ed roles. #highereducation #datagovernance #irwatercooler educause

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Did you know? Mortgage lending disparities persist, disproportionately impacting communities of color. NCRC’s latest Mortgage Market Analysis sheds light on the stark realities of home loan approvals across racial and ethnic groups. Together, we can push for a fairer system that ensures equal opportunities in homeownership for everyone. Dive into the data and join us in advocating for change. Learn more: https://lnkd.in/evjg7MMG #justeconomy #EconomicJustice #HousingEquity #RacialWealthGap

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Mortgage lending trends reveal persistent challenges for low- and moderate-income borrowers and communities of color. The NCRC Mortgage Market Analysis dives into these trends, offering insights into creating a more equitable housing market. Read the report: https://lnkd.in/evjg7MMG #JustEconomy #HousingEquity #MortgageTrends

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🚀 Banks are embracing AI and geospatial analytics to revolutionize CRA lending! 📈 By targeting underserved communities, they’re not just staying compliant—they’re boosting loan approval rates by 10-15% and achieving a staggering 10x ROI on marketing efforts! 💰💡 Discover how AI can fast-track loan closures and drive profitability while making a real impact. #BankingInnovation #CRA #AI #LendingSolutionsFuture-Proofing Your CRA Strategy: How AI Can Drive 10x ROI in Underserved Communities https://hubs.ly/Q02Qt_zs0

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Visualized: US Currency in circulation, past and present 38 By Chris Hemedinger on The SAS Dummy February 27, 2024 Topics | Analytics Data Visualization Programming Tips Industries | Banking This phenomenon has been in the news recently, so I've updated this article that I originally published in 2017. The paper currency in circulation in the US is mostly $100 bills. And not just by a little bit -- these account for 34% of the notes by denomination and nearly 82% of the value (data as of 2022). I originally wrote this article when I was inspired by a news story on NPR's Morning Edition about the merits and risks of the $100 bill. There are a lot of them in circulation, but no one knows exactly where they are. According to the report, they are seldom used for legitimate business transactions. When a transaction reaches into the hundreds of dollars, the business parties tend to resort to a digital transaction (or maybe a good-old-fashioned personal check). Large cash transactions are often used to avoid taxation or, more nefariously, to hide criminal activity.

If your institution's CECL model is not “fit for use” when evaluating the potential credit and capital exposures - do you know how you can best prepare❓❓❓ Join experts Mark Haberland & Chase Ogden of Darling Consulting Group as they share insights from recent model validations through real-life examples of how solid foundational documentation can enhance credit risk mitigation and improve your institution’s resilience in any economic climate. Register today for this 1-hour session: https://bit.ly/3XghbRZ #FMS #FMSWebinars #CPE #education #financeindustry #professionaldevelopment #risk #CECL #ModelValidations #CreditRiskMitigation

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⏰ BREAKING: The Fed, FDIC, and OCC just released a new guide to help Community Banks manage their third party risk. One key point of emphasis: "A community bank may engage an external party to conduct aspects of its third party risk management. However, the bank cannot abrogate its responsibility to employ effective risk-management practices, including when using a third party to conduct third-party risk management on behalf of the bank." Outsourcing third party diligence to a firm isn't enough - it's crucial to invest in internal operations because the bank is ultimately responsible. 🗒 Reach out to our team at hi@kobaltlabs.com if you'd like to learn how we can help strengthen and streamline in-house efforts.

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Forecasting Techniques - can you predict the future? Yes (sort of). Time series forecasting uses historical data to predict future outcomes. In Part 3 of my time series project, we cover: - Naive forecasts, where sometimes the simplest approach works best. - Moving averages, a method to smooth out noise and reveal trends. - Real-world forecasting, like predicting hive weight in a beehive to decide the best time for harvesting honey without stressing you bees! 🐝 What’s the most creative way you’ve seen forecasting used in your work? #Forecasting #DataScience #TimeSeries #MachineLearning #PythonProgramming #DataDriven

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Very interesting piece of research conducted by the Federal Reserve Board Dallas, NYU Stern School of Business and Rice University using CoreLogic's predictive Climate Risk Analytics (hazard, geospatial and resiliency science) and 2 more information service powerhouses, S&P Global and ICE. Well worth a read. Available at SSRN:  https://lnkd.in/grKJGWTp Heavyweight research conducted by Shan Ge (Assistant Professor at NYU Stern), Stephanie Johnson (Assistant Professor of Finance, Rice University) and Nitzan Tzur-Ilan (Research Economist Federal Reserve Bank of Dallas) The research paper continues the research into the intersection of natural disasters, mortgage markets, and insurance premiums. As temperature increases' intensify the frequency and severity of natural disasters, homeowners’ insurance premiums are rising sharply. This study investigates how increasing insurance premiums influence mortgage delinquencies and prepayments by leveraging a novel dataset linking insurance policies to mortgage outcomes of 6.7 million borrowers. The analysis shows that higher premiums significantly elevate the chances of mortgage delinquency and prepayment. These findings are robust to using an instrumental variable for premium increases. The effect of delinquency is more pronounced for mortgages with higher loan-to-value ratios, while the prepayment effect is smaller for these loans. Additionally, we find that delinquency effects are present in both GSE and non-GSE mortgages, implying risks for both the Federal Government and the private financial sector. The paper also points to the risks that rising insurance costs pose for mortgages and mortgage-backed securities. Delinquencies represent negative shocks for mortgage holders, a significant portion of the financial sector. Thus, our findings not only illustrate the direct impact on households but also uncover broader implications for financial stability as insurance costs rise due to climate change. For policymakers addressing the issue of insurance affordability, the findings carry critical implications. The results suggest that escalating insurance premiums are severely limiting household liquidity, driving some into mortgage delinquency. Given the broader economic consequences of mortgage defaults, our research underscores the potential value of policy measures like means-tested insurance subsidies to mitigate these effects. Patrick Dodd Devi Mateti Jayme (Poladian) Beck Howard Botts Mahmoud Khater George Gallagher Hallie Nester, M.S. Jennifer Castenson Robin Wachner Kristie Vainikos Stegen Kent David Lance Lambert Joe Francica Amy Gromowski Paul Gaspar Srinath Ravulaparthy Robin Sun Pete Lumbert Mark Weaver Mark Gongloff Selma Hepp, PhD David Claussen, PhD Clayton Collins Peter Carroll Diego Sanchez Malliga Krishnan GAICD Tim Lawless Eliza Owen Jennings Anand Singh Chris Hatter

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The ol' adage "a picture is worth a thousand words" is very true. Take this picture ... this is explaining CLIP - CoreLogic's Property identifier, what a SSN is to you and I. CLIP is the glue between 210M+ addresses, across 176M+ structures sitting on 157M+. Indeed we track 250,000 to 500,000 changes per quarter ... new addresses, parcels split, new development. Why is it useful? Allows our clients to focus on the insight ... traversing market position, new leads, operational efficiency all the way through to risk mitigation use cases on their book of business. So easy to CLIP your book of business. Whether handling lat/long, shape files, APNs, addresses, CoreLogic takes the pain away of mastering property & location geospatially - to allow you to focus on the insight and the business decision. Took us over 2.5 years to build and has been in the market getting used across the housing industry for over 4 years. To the product, geospatial scientists and technology geniuses who created it Anand Singh Shaunak G., Matt Kjernes Frankie Famighetti Hari Krishna Kandula Chris Tackett Manny Cuevas Patrick Dodd Devi Mateti Jay Kingsley Garret Gray Lance Lambert Kristie Vainikos Stegen Robin Wachner Amy Polvado Robin Sun Massimo Mascaro Pete Lumbert Mark Weaver Bill McGinn Heidi Russell Bill Bernabei John Sikaitis This is CoreLogic 2.0

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𝗜𝗻 r𝗲𝗮𝗹 e𝘀𝘁𝗮𝘁𝗲, 𝗳𝗿𝗮𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗱𝗮𝘁𝗮 𝘀𝗹𝗼𝘄𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀. But what if all property data—internal, external, and third-party—existed in a single source of truth? Last week, I hosted a 𝗳𝗶𝗿𝗲𝘀𝗶𝗱𝗲 chat with L.D. Salmanson, CEO of Cherre, a leading real estate data platform. He walked us through how Cherre connects property data from over 150 partners, finally putting a stop to the Excel spreadsheet madness we have all endured (and many still do) for decades! What hooked me was the parallel he drew between real estate and financial services. He emphasized that real estate investments should be as #DataDriven as stock market trades—a perspective I enthusiastically agree with! He also presented real estate-specific #CAPM models that his team created during the initial stages of the company (interesting application! Ask him about it!). 𝗜𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁 𝘀𝘂𝗰𝗰𝗲𝘀𝘀 𝗰𝗼𝗺𝗲𝘀 𝗱𝗼𝘄𝗻 𝘁𝗼 𝗰𝗹𝗲𝗮𝗿 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘀𝘆𝘀𝘁𝗲𝗺𝘀. Companies must rethink how they assess risk and returns using real data while moving beyond outdated spreadsheets and intuition-based models. L.D. also urged my audience—from students to professionals—to build and hire for #specialization over generalization. His leadership approach focuses on building a specialized team, cultivating trust through transparency, and upholding a long-term vision that prioritizes sustainable growth over rapid exits. His guiding principle? “𝙒𝙚 𝙤𝙣𝙡𝙮 𝙙𝙤 𝙤𝙣𝙚 𝙩𝙝𝙞𝙣𝙜 𝙖𝙩 𝘾𝙝𝙚𝙧𝙧𝙚—𝙧𝙚𝙖𝙡 𝙚𝙨𝙩𝙖𝙩𝙚 𝙙𝙖𝙩𝙖—𝙖𝙣𝙙 𝙬𝙚 𝙢𝙪𝙨𝙩 𝙗𝙚 𝙩𝙝𝙚 𝙗𝙚𝙨𝙩 𝙞𝙣 𝙩𝙝𝙚 𝙬𝙤𝙧𝙡𝙙 𝙖𝙩 𝙞𝙩.” He also opened up about his early challenges and resilience. Starting to code at 13, L.D. went on to sell his first company within a few years. Alongside his co-founder and right-hand Ben Hizak, he channeled this entrepreneurial drive to build Cherre, pitched to more than 100 firms before landing the company’s first data partner, and positioned Cherre as the #firstMover in the industry. Today, Cherre stands at $130 million in funding and empowers data analysts and scientists like me to bring the real estate market to the new frontier—closer to data-driven decision-making, #machineLearning, and potential #GenAI applications. Although #AI offers significant potential, data quality #challenges persist. Human oversight will remain important, particularly when interpreting surprisingly subjective terms such as "market" or "asset class". Companies must invest in data literacy and #infrastructure to remain competitive in an #AI-driven future. His advice: “𝑩𝒆 𝒑𝒆𝒓𝒔𝒊𝒔𝒕𝒆𝒏𝒕, 𝒃𝒖𝒊𝒍𝒅 𝒕𝒓𝒖𝒔𝒕, 𝒂𝒏𝒅 𝒅𝒐𝒏’𝒕 𝒇𝒆𝒂𝒓 𝒓𝒆𝒋𝒆𝒄𝒕𝒊𝒐𝒏—𝒊𝒕’𝒔 𝒑𝒂𝒓𝒕 𝒐𝒇 𝒕𝒉𝒆 𝒋𝒐𝒖𝒓𝒏𝒆𝒚.” As an industry professional and educator, I can't agree more with #grid. #RealEstate #AI #BigData #DataIntegration #PropTech #InvestmentAnalytics #DataScience #Automation #Leadership #Entrepreneurship #Chapman #ChapmanMSRE

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On October 29, CU's ERM Program celebrated the launch of "The Credit Analyst’s Survival Manual," co-authored by Chris Droussiotis, a distinguished part-time lecturer at Columbia University. Chris shared his expertise and discussed the key themes of his book, including the evolving landscape of credit markets, essential skills for effective credit analysis, and strategies that empower financial professionals to thrive. Watch the recording here: https://lnkd.in/ekxqtSEg #columbiaerm #enterpriseriskmanagement #ERM #riskmanagement #businessstrategy #authorspotlight #interview #industryexpert #expertise #creditmarkets #creditanalysis #financialprofessionals #perspectives #advice #discussion #networking

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