March 10, 2020 1,608 Views Editor’s note: This feature originally appeared in the March issue of DS NewsThere’s no doubt that we are living in times of accelerated change. If you look at how any industry has evolved over the past 100 years—whether it’s travel, communications, or entertainment—you will see a sharp contrast between how slowly things changed a century ago compared to how quickly they are changing today.As just one example, vinyl long-playing records, or LPs, were the standard for decades until the mid-1960s, when 8-track tapes and cassettes took over. Then came CDs in the 1980s, followed by digital music files in the early 2000s. Now most people stream their favorite music through online apps. LPs still exist, but their primary value is based on nostalgia.Eventually, everything changes, but some things take longer than others. Innovation such as artificial intelligence, machine learning and data capture technologies have taken hold in loan manufacturing but have been slower in adoption on the secondary marketing and servicing end of the market. Here they could be enabling faster, more efficient MSR acquisitions and onboarding of loans. Their potential to transform the secondary market is undeniable.The Costs of Yesterday’s TechnologiesAn abundance of diligence questions along with legacy systems with wildly differing customizations has led to a lack of any type of consistency or uniformity in how institutions behave in the secondary market today. As a result, an institution that sells loans of the exact same asset class to both Buyer A and Buyer B is going to have two totally different experiences. This lack of continuity really makes it cumbersome for all parties involved.There are advantages to using trading platforms, of course. They are, on the whole, a much more efficient way to manage capital market price, time of trade, and reduce trade fails. But these platforms do not address the validation of loan documents and data to identify any data inconsistencies. In a single file, you could have a piece of data that says one thing, and documents that say something else entirely—and no means to reconcile the two.Data ingestion is another factor that contributes to variability because of the fact some institutions have modified their systems so they are capable of boarding a sizable amount of data, while other institutions haven’t. Even though there is more loan data available than ever before, those that are slow to adopt have no place to store it—so they stick with spreadsheets or archive the trade tape, figuring that as long as they have the data somewhere, it’s okay.Most secondary market trading platforms have also failed to solve two of the biggest issues MSR traders face, the first of which is timing. Given how quickly prices change in the capital markets, spending days or weeks on MSR acquisitions can be costly and result in the loss of better opportunities.The second issue is the functional fulfillment of the loan and making sure that you bought what you thought you did. This is where things can get clumsy, given the overall lack of data quality and the high degree of variation in document ordering and naming from sellers. In the past, the spreadsheet became the great equalizer, using macros to map data and manual processes to determine if data was missing and to enter it into the buyer’s systems. That approach is neither accurate nor scalable.On the origination side of the business, consumer demand for a simpler, faster, digital experience has motivated lenders to adopt increasingly higher levels of automation. It’s quite a different story in the secondary market, where institutions have been slower to implement automated tools and seem to remain loyal to embedded manual practices. In fact, capabilities already exist that could enable institutions to conduct MSR trades and onboard loans in a fraction of the time it currently takes. With the increasing adoption of these new technologies, however, things are starting to change.Understanding AI’s ImpactOne of the most exciting things happening in the secondary market today is the emergence of AI technology, as well as machine learning tools, which are a subset of AI. AI describes technologies that analyze data and make decisions based on data patterns, whereas machine learning describes technologies that learn to distinguish patterns in data from human instruction and self-learning algorithms.In truth, AI and machine learning, while often talked about, are not as commonplace as many are led to believe. They can create the uniformity these institutions need through the data normalization they provide across sellers’ loan files, making it much easier to ingest documents and data accurately. This then can lead to the use of more sophisticated applications that can significantly help servicers and investors gain greater insights on their portfolios and their trading decisions, especially when determining where risk lies and which loans to sell versus which loans to retain.AI and machine learning technology also enable MSR traders to capture a greater amount of data off loan files and then automatically run business rules around that data. This eliminates the historic “stare and compare” methods of checking data and loan quality and greatly reduces the time and overall cost of due diligence. By green-lighting the vast majority of files in which the data can be trusted, companies can focus on exception-based processing, which allows them to move loans forward much more efficiently.A particular benefit of these technologies lies in the fact that different investors look for different data elements when determining risk. There’s a huge variation among loan purchasers in terms of the data elements that they are concerned about. Certain buyers require checks on 40 different data fields, while others may want to look at 30 or 50—there’s really no consistency among them. Their legal agreements all differ as well. If an investor needs to check 30 unique data elements when buying a pool of loans, they could do so in seconds using machine learning tools to aid the process, rather than spend several days poring over them by hand.These tools are also great for filtering loans. For example, if I’m buying MSRs and I don’t want a large concentration of loans in a specific state or zip code because of the perceived risk involved, I can get that information with a click of a button. I could also build a view of key data elements that are important to me for the loans I’m acquiring and have this information presented in nanoseconds.New technologies also give sellers a huge advantage when it comes to market timing as well, which is a big deal in a rising rate environment. When you’ve made a commitment to sell a pool of loans and there is an agreement in place and a price locked in 10 or 15 days, and you don’t deliver the files in time, you’re at risk of having your loans repriced at today’s rate, which cuts into the premium you were expecting to receive. Because new technologies enable faster trades, the timing issue virtually disappears.When it comes to onboarding loans onto one’s servicing platform, buyers want to make sure there are no data defects and make sure they reach out quickly to borrowers to let them know they are their new servicer. Automated technologies allow them to make sure they have all the correct information, send out borrower letters and have staff reach out to borrowers much faster—servicers can even set up these processes with automated dialers and messaging. This saves an enormous amount of time and improves loan retention.How Momentum Is GrowingOver the past two years, we’ve seen a tremendous amount of pickup in machine learning and data extraction tools in the secondary market. Ultimately, I believe this will bring greater consistency to how the secondary market operates, as well as new best practices. Similarly, secondary market participants that invest in these new technologies won’t simply be able to absorb a great number of loan file types faster and more efficiently, they will also be able to build stronger, more efficient organizations that are better able to compete going forward.Yet there is a major obstacle that lies in the way that I haven’t talked about. Inertia. There’s an entire generation of secondary market professionals who grew up doing things a certain way and remain loyal to those processes—and the people who perform them. There is a different way to think about this, as new technologies do not necessarily mean these jobs will go away. If institutions that both originate and service loans no longer need 30 acquisition team members to onboard newly acquired loans, but instead only need five, they can move their staff to the origination side of the business and have more flexibility to scale on either side as market volume ebbs and flows. It’s really a matter of reallocating your human resources to best utilize their skills to improve your business.Sometime in the future, there will be an inflection point at which participants will either adopt these new emerging technologies or put their companies’ futures at risk. Throughout the business world, there are countless examples of companies that are no longer around because they couldn’t keep up with the pace of accelerating change. It is naïve to think that it can’t happen in the secondary market.At the end of the day, it’s not a question of if the secondary market will embrace new AI and machine learning technologies, but when. The reduction in time, the cost savings, and the higher quality assets that will result from these changes are too great to ignore much longer. In any event, there will come a time when the predominant technologies used in the secondary market today will be looked at like yesterday’s vinyl records—minus the nostalgia. The Times, They Are a’ Changin’: AI in Mortgage Servicing Sign up for DS News Daily Craig Riddell is EVP, Chief Business Officer at LoanLogics. He is responsible for establishing and developing ongoing relationships with LoanLogics’ largest enterprise clientele, as well as leading the sales, marketing and account management functions. He can be reached at [email protected] About Author: Craig Riddell Share Save Demand Propels Home Prices Upward 2 days ago Servicers Navigate the Post-Pandemic World 2 days ago The Best Markets For Residential Property Investors 2 days ago Data Provider Black Knight to Acquire Top of Mind 2 days ago Previous: How Institutional Housing Investors Shaped Recovery Next: Industry Responds as Coronavirus Declared a Pandemic Demand Propels Home Prices Upward 2 days ago The Week Ahead: Nearing the Forbearance Exit 2 days ago Data Provider Black Knight to Acquire Top of Mind 2 days ago Related Articles The Best Markets For Residential Property Investors 2 days ago Governmental Measures Target Expanded Access to Affordable Housing 2 days ago Subscribe Print This Post 2020-03-10 Seth Welborn Governmental Measures Target Expanded Access to Affordable Housing 2 days ago Home / Daily Dose / The Times, They Are a’ Changin’: AI in Mortgage Servicing in Daily Dose, Featured, News, Print Features, Technology Servicers Navigate the Post-Pandemic World 2 days ago
Governmental Measures Target Expanded Access to Affordable Housing 2 days ago The Best Markets For Residential Property Investors 2 days ago Sign up for DS News Daily Data Provider Black Knight to Acquire Top of Mind 2 days ago Print This Post How many articles have you seen over the past year about the benefits of digital mortgages? At the time of this writing, Google News turned up 130 stories about digital mortgages in a single month. Those are just stories captured by Google—there are certainly countless more, not to mention a plethora of white papers, webinars, and eBooks all focused on the topic. Who has time to digest them all?There are many ways to go about adopting a digital mortgage strategy, and certainly reading up on the subject is a good place to start. But to be successful, there is no more important piece to the digital mortgage puzzle than having an experienced and trusted fintech partner at your side—a partner with the right blend of technology, resources, experience, and skills to fit your company’s needs and goals, and one that will take all those stories and synthesize them so they make sense to you.What Makes a Good Partner?A solid fintech partner is one that understands the intricacies of the digital mortgage process from all angles, from origination to pre-closing, closing, and post-closing. They also understand not only the technologies and services you need to achieve your goals, but also the needs and goals of your business partners and other relationships, so everybody is working toward the same plan.The right partner will work with you to determine which digital processes are right for your company. For example, do they have experience in the areas of your business, whether that is conforming and nonconforming loans, or both? Will they develop a relationship with you and create a timeline for adopting a digital strategy? During the relationship, will they act as your advocate throughout the entire project, not just through the implementation stage but during the production stage and beyond?Perhaps the most important question to ask a prospective partner is how much practical, digital experience they have. Do they have experts on staff who have developed and implemented fintech solutions for companies like yours? Do they understand digital processes and their impacts from the perspective of all life-of-loan participants? And will they educate and train your team and your partners on an ongoing basis?Truly effective partners are constantly innovating to incorporate new technologies, as well as staying abreast of new data interchange standards, best practices, and innovations.The Importance of SMART DocsPerhaps the most critical attribute a digital partner must possess is a deep understanding of the impact of eNotes on all parties, throughout the life of a loan. That includes your trading partners and their trading partners, too.A capable partner will be able to deliver documents in a standard data format, which requires access to a doc engine built entirely on SMART Docs. This is an important point, as many outsourcing providers use PDFs instead of SMART Docs, and PDFs are not nearly as efficient or accurate.Before a borrower can electronically sign a PDF file, for example, someone must manually ‘tag’ the file to accept the borrower’s signature. PDFs can’t be read by machines with 100% accuracy, either, which means they are reviewed by humans for errors. These extra steps are inefficient and introduce opportunities for error.A good partner will provide a complete library of SMART Docs that encompass all types of loan documents. Because SMART Docs can also be rendered in PDF, they allow you to choose XML or PDF for each doc type. They also allow you to change that mix to meet borrower and trading partner demands. While many providers concentrate on just having the note be a SMART Doc, having access to an entire library of SMART Docs enables truly digital versions of every document so they can be electronically reviewed for due diligence after they are executed.The ideal partner will offer a wide range of mortgage services beyond eClosings. By being able to take on loan application, underwriting, and due diligence services through closing, delivery, custody, and secondary stages, a capable partner can help you better manage staffing levels, especially when there is a rapid increase or decrease in volume. If your partner offers these types of services, they should have digital capabilities imbedded into them.Where to Start Your SearchSo, where to find capable partners? Two of the best sources are the eMortgage vendor lists that are maintained by Fannie Mae and Freddie Mac.The GSEs have conducted actual tests with the eNote delivery systems. If a vendor is on the list, that means the GSE has worked with them to ensure their technologies were developed to meet the GSEs’ requirements. While neither Fannie Mae nor Freddie Mac will endorse any vendor—they encourage companies to conduct their own due diligence when selecting a vendor—the GSEs are a great place to start.Identifying the fintech partner that fits your needs takes time and effort. But, as Mary Poppins would say, “Well begun is half done.” Of course, learning how to “begin well” can be confusing. That’s why it’s best to choose a partner that will educate you on the concepts and possibilities. Let them keep up with the articles and white papers, customize all that information to your needs, and put all the pieces together for you. Once you do, you’ll be “well begun” and well on your way to success. Share Save March 19, 2020 9,225 Views Previous: REITs Aren’t Dead Next: Single-Family Homes are Shrinking About Author: Katie Paolangeli Home / Commentary / The Most Important Item in Your Digital Toolkit Governmental Measures Target Expanded Access to Affordable Housing 2 days ago FinTech 2020-03-19 Seth Welborn in Commentary, Daily Dose, Featured, News, Print Features, Technology Servicers Navigate the Post-Pandemic World 2 days ago Data Provider Black Knight to Acquire Top of Mind 2 days ago Katie Paolangeli is the SVP, Product Management of eMortgage Technology for Evolve Mortgage Services. A former VP of eCommerce for MERSCORP, Paolangeli has more than 30 years’ experience in mortgage technology and has participated in dozens of panels, webinars, presentations, and training sessions on the topic of electronic mortgages. She can be reached at [email protected] The Week Ahead: Nearing the Forbearance Exit 2 days ago Demand Propels Home Prices Upward 2 days ago The Most Important Item in Your Digital Toolkit The Best Markets For Residential Property Investors 2 days ago Servicers Navigate the Post-Pandemic World 2 days ago Related Articles Tagged with: FinTech Demand Propels Home Prices Upward 2 days ago Subscribe
Students applying to Oxford will now have their postcode taken into account as admissions tutors consider which applicants to interview.A University spokesperson said that the move was not about “massaging our figures” but “finding the brightest students with the greatest potential to succeed at Oxford.” She insisted that academic excellence would not be compromised.Tutors will also look at the results achieved by the applicant’s school, whether they have spent time in care, or attended specific programs for disadvantaged pupils. Any sufficiently able student who is flagged up in at least three of the criteria will be interviewed.Students will still need predictions of 3 As at A-Level and must be within the top 80% in any pre-interviews tests. The spokesperson said the information will play “no part in deciding who will receive an offer, or what that offer is.”Paul Dwyer, OUSU VP for Access and Academic Affairs, suggested that the university may be engaging in what OUSU deems “positive discrimination” on the grounds of a student’s socio-economic status or geographical location. He also highlighted OUSU policy which states that “contextual data that is not related to a student’s educational potential” during the admissions process.Professor Alan Smithers, director of the Centre for Education and Employment Research at Buckingham University, said that he was “worried” by the measures and attributed the move to “governmental pressure.”He said, “The key thing for a world class university is to select and admit students on the basis on their intellectual ability and that should be the sole determinant.”A first year student at St Peter’s College called the changes a “step in the right direction”, and argued that many state schools are ill equipped for the Oxbridge application process.She said, “I had to carry out most of the research myself and this isn’t particularly unusual. It’s great the university finally seems to be recognising this.”Dr Tom Kemp, admissions tutor at St John’s, said, “the colleges still have the freedom to use whatever information they choose, and my own will not place very much weight at all on this particular evidence.” Oxford’s announcement follows recommendations by the National Council for Educational Excellence that ‘contextual data’ should be used when assessing academic potential. There has been speculation that the £3,145 cap on what universities can charge each year might be removed, further limiting the higher educational opportunities open to poorer students.In February, Bill Rammell, the higher education minister, singled out Oxford and Cambridge as the poorest recruiters of state school pupils. Nationally, only 29% of students are from poor backgrounds, whilst at Oxford and Cambridge the level is significantly lower – 9.8% and 11.9% respectively.A study by the Sutton Trust last year showed that students from top private schools were twice as likely to gain admission as those from top grammar schools.
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RelatedPosts Real One, Baby Face, Esepo to headline GOtv Boxing Night 21 GOtv Boxing Night 20: Ehwarieme eyes world title Esepo delighted at winning best boxer prize at GOtv Boxing Night 20 West African Boxing Union welterweight champion, Rilwan “Baby Face” Babatunde, and national super featherweight champion, Ridwan “Scorpion” Oyekola, have promised to return to the ring in an explosive fashion at GOtv Boxing Night 20, scheduled to hold on 12 October. The two shinning stars are billed to fight at the event slated for the Indoor Sports Hall of the National Stadium in Lagos. In his last fight at GOtv Boxing Night 19, Baby Face famously knocked out Ghana’s Eden Biki, who was punched into unconsciousness in the 10th round. The WABU champion next opponent is Jafaaru Suleiman. Speaking in Lagos on Monday, the WABU champion said he’s already looking beyond Sulaimon, whom he said he plans to use as preparation for the African Boxing Union title bout. He said: “Sulaimon is not an opponent in the real sense. He’s a training apparatus. I’m looking beyond the fight, as my target is the ABU title.” Oyekola, whose last engagement saw him dethrone long-reigning champion, Taofeek “Taozon” Bisuga at GOtv Boxing Night 18 in Ibadan, said his next opponent, Sikiru “Omo Iya Eleja” Shogbesan, will suffer the same fate as Bisuga, who suffered a first-round technical knockout after falling thrice. The Ibadan-based boxer, who spoke in a phone chat, advised Shogbesan to pull out of the bout or risk being beaten legless. “There is no dispute about me being the best in my category. Bisuga is well placed to tell Shogbesan how I made him see stars. If Shogbesan ignores my advice, the walls of the Indoor Sports Hall will appear to him as wobbling by the time I finish with him,” said Scorpion. GOtv Boxing Night 20 will be headlined by the much anticipated pairing of ABU lightweight king, Oto “Joe Boy” Joseph, and WABU champion, Rilwan “Real One” Oladosu, who face each other in the ABU title bout. Also on the card is the national bantamweight title bout between Sadiq Adeleke and Opeyemi “Sense” Adeyemi. Other bouts include a national welterweight challenge a national light heavyweight challenge bout between Adewale “Masevex” Masebinu and Kabiru “KB Godson Towolawi; and a national featherweight challenge bout between Tope “TP Rock” Musa and Olusegun “Embargo” Moses. Graduates of GOtv Boxing NextGen Search 5 will also make their debut at the event as Alaba “Elybow” Omotola, best boxer of the competition, will take on Bolaji “Fight to Finish” Abdullahi in a national lightweight challenge contest. There is also an all-female bout as Cynthia “Bobby Girl” Ogunsemilore will square up against Aminat “Smart” Yekini in a super featherweight challenge.Tags: Baby faceGOtv Boxing Night 20Ridwan OyekolaRilwan babatunde