Non-prime lending has revolutionized the lending sector. In times where people lack a stable credit history, securing a traditional loan is not easy—and non-prime has become a go-to option in such scenarios. In the past few years, alternative financial services have gained momentum in terms of acceptability and volume. There are various companies in the […]
Non-prime lending has revolutionized the lending sector. In times where people lack a stable credit history, securing a traditional loan is not easy—and non-prime has become a go-to option in such scenarios. In the past few years, alternative financial services have gained momentum in terms of acceptability and volume. There are various companies in the market that offer instant loans even to the borrowers who have a weak credit history. But how do we infer how many people have migrated to non-prime online borrowing from the traditional borrowing set up, and how many people have migrated back to the traditional set up?
Experian’s Clarity Services, a credit reporting agency specializing in near prime and subprime consumers, offers credit data to alternative financial service (AFS) providers. This helps lenders gain a wider perspective of non-prime applicants and further enables them to make more informed decisions.
The company furnishes the AFS trends report that specifies the prevailing trends and consumer behavior in the market by studying the underlying factors. In the 2019 AFS Lending Trends Report, Clarity studied a sample of 350 million consumer loan applications and more than 25 million loans to evaluate the market trends for the 2014 to 2018 time period. Clarity also leveraged Experian’s national credit bureau data to analyze consumer behavior.
Alternative Financial Services — What Do the Market Trends Say?
Non-prime consumers include people who may have been irresponsible with credit previously, youngsters with inadequate credit history, people who face sudden and unexpected emergencies, recent immigrants in the US or someone in immediate need of cash. The basis for the report includes factors of loan origination (involves the online and storefront channels) and loan types (includes installment payments and single pay).
In order to study the rise of the online lending market from 2014 to 2018, Clarity studied online installment and single pay loans by the number of loans originated and total dollars funded.
The graphs illustrate how online installment loans have been steadily growing from 2014 to 2018. The volume of online installment loans in 2018 was 7.4 times higher than the volume in 2014. Whereas, the volume grew up until 2016 in the case of online single pay loans, plummeted in 2017 and held steady in 2018.
As per the report, more than half of online borrowers are new to the alternative credit space. The table below illustrates the consumers who opened an online loan in 2018, tracking their past behavior from 2014 to 2018.
Clarity also tracked the activity of 2017 alternative financial borrowers in 2018 and if they continued with online platforms. The results showed that 41% of online borrowers again availed an alternative loan, while 24% of the borrowers did not show up in 2018. Also, 35% of the borrowers applied for a loan but did not open one.
Further investigations gave another interesting insight. Around 34% of 2017 borrowers who did not have any applications or loans in 2018 had switched to traditional lenders. This implies that 7% of overall 2017 borrowers migrated to traditional lending in 2018.
As per an examination of the credit classification of consumers who obtained and did not obtain loans from traditional lenders in 2018, 23% of borrowers who switched to traditional lending possessed a near prime credit score, and only 8% of the borrowers continuing in the alternative finance space were classified as near prime.
Factors Influencing Migration from Online Platforms to Traditional
While the migration of borrowers from AFS platforms to traditional ones might not be a shocker, borrowers who had a subprime credit score and were ineligible to apply for traditional loans were mostly the ones who moved to online or the AFS space to get the credit they needed. As and when their credit scores improved, they reverted to the traditional space. While AFS is convenient in terms of credit scores and repayments, there are strong factors that influence the borrowers to move back to traditional methods.
Frauds: With the advent of technology, fraud too has evolved. With data breaches, the fraudsters create a synthetic identity that cannot be easily decoded. This is leveraged by fraudsters to open fake and additional accounts.
Generation Bias: Gen X is more comfortable with online borrowing and less likely to be inclined towards storefront options. Another study under the report implies that the Silent and Boomer generations only account for 25% to 30% of all AFS borrowers.
Income Trends: In the past five years, online installment borrowers reported a higher income (while the values have been steady since 2016) and the reported incomes of storefront installment borrowers have been stagnant since 2014.
Due to the recession in 2008, the majority of borrowers had suffered a hit to their credit worthiness. On the other side, traditional lenders folded due to the toxic asset built up in their balance sheets. This created a vacuum for the AFS players to capture. It was a win-win as they were able to tap into a multi-hundred-billion-dollar market unchallenged, and the affected borrowers got a chance to get the credit they needed desperately.
With record economic growth, the 2019 scenario is different. Borrowers are returning to traditional ways of borrowing. The trends report puts light on the activities of the borrowers and how their needs have changed over time. In the given scenario, Clarity’s alternative credit data is a key asset when studying borrower behavior in the market.
The evolving landscape of digital lending is turning traditional bank loans and credit analysis into a distant memory. The rise of big data and technological progress have led to alternatives or augmentations to Fair Isaac Corp.’s proprietary FICO score, the dominant credit score used to vet consumers’ creditworthiness. Now, a bill is making its way […]
The evolving landscape of digital lending is turning traditional bank loans and credit analysis into a distant memory. The rise of big data and technological progress have led to alternatives or augmentations to Fair Isaac Corp.’s proprietary FICO score, the dominant credit score used to vet consumers’ creditworthiness. Now, a bill is making its way through the U.S. legislative process that would require Ginnie Mae and Fannie Mae to consider credit scores beyond FICO. Although these proposals are focused on mortgages, one can infer that alternatives to FICO are welcome across the board, including consumer loans. And we now have the technical means to deliver.
When it comes to consumer lending, lenders have traditionally relied upon a loan applicant’s FICO credit score obtained through a credit bureau such as Experian or Equifax to help determine an applicant’s creditworthiness. These three-digit scores are derived using a proprietary formula that uses data like payment history, credit history length, and credit line amounts. The lower the score, the less likely an applicant is to secure a loan. The exact formula is a trade secret, known only to Fair Isaac Corp. Hence, we are already relying on a proprietary “black box” to make a credit decision. We’ll get back to that point later when we discuss machine learning algorithms. Enter digital lending.
Digital Lending Creates a New Way to Vet Applicants
New credit models are based on the proposition that the old ways of approving applicants based on FICO credit score alone do not paint a complete picture of an applicant’s creditworthiness. The proliferation of new data points about consumers provides a wealth of raw data ready for analysis.
With the use of machine learning algorithms, and more broadly artificial intelligence, new models are looking at hundreds, and thousands of other data points, and not all are related to traditional financial risk. Enhanced use of personal information may include educational history, employment history, and even seemingly non-financial information such as bedtime, website browsing patterns, spelling on loan applications, social media data, and even messaging patterns.
While using big data could muddy the waters by creating more confusion than clarity, artificial intelligence could have a big impact on how alternative lenders perform.
Artificial Intelligence Streamlines Sales and Strategy
Savvy digital lending startups are testing the waters with machine learning to make underwriting decisions and enhance their loans. Machine learning algorithms can help to determine if applicants are telling the truth about income by looking at past employment history and comparing it to similar applicants. However, this technology can also favor the applicant by finding hidden patterns.
This data collection is advantageous for people with insufficient credit history, low incomes, and young borrowers who are typically charged with higher interest rates if they obtain credit at all. These methods may also appeal to mortgage companies looking to automate less risky applicants through a similar process.
Yet several challenges exist with these new credit models:
First is what we’ll call a slow rinse and repeat the cycle. Machine learning algorithms, like humans, learn by doing and repeating while making correctional adjustments along the way. Economic credit cycles can last 5-7 years. Even if we back test a model using historical data, how do we know it will work in the future? A cliche in finance is that “past performance is not indicative of future returns.” It may take a long time to prove that a model is right or wrong because the model itself, like an inexperienced loan officer, hasn’t seen enough credit cycles.
Second, models need to explain their black box to gain trust. FICO gets away with being a “black box,” but artificial intelligence cannot. Even if a model works, humans need to have some kind of explanation to feel comfortable with the output.
Bank regulators need to know what’s going on. Fair credit regulators require that lenders keep records for the reason that credit was denied. The applicant has a right to inquire about why they were rejected. Disclosing the reason for a rejection is easy to do with an old-fashioned credit scorecard, based on a transparent point system. But what would regulators or auditors do with machine learning model outputs? For now, the practical answer is to run a traditional model as a backup whenever a machine learning model rejects an applicant, and hope that they both give the same answer! If so, record the traditional model’s output as the reason for credit denial.
For now, the most beneficial result of machine learning is the ability to detect consumer fraud by analyzing customer behavior with baseline data of ordinary customers and singling out outliers, such as how much time people spend considering application questions, reading contracts, or looking at pricing options. This filter alone leads to more accurate underwriting decisions, which, in turn, reduces defaults for lenders and lowers interest rates for consumers.
Blockchain Changes the Future of Funding
Peer-to-peer lending platforms originated out of one simplistic idea, one peer borrower asks for a loan, and another peer lender will decide to fund the loan. Both parties benefited by “cutting out the middleman” – the borrow paid a rate lower than that of a traditional loan, and the lender received a rate higher than that of a traditional savings account. But the peer-to-peer, or “people helping people” model, changed as large lending companies and institutional investors entered the space to become lenders, and, in institutional parlance, “buy loans” in bulk. Moreover, peers lack the expertise or ability to perform proper credit risk on other peers. Peer-to-peer became institutional-to-peer.
However, what if blockchain or distributed ledger technology could return us to the original concept of peer-to-peer lending? Blockchain-based solutions are currently developing identity and reputation models. With blockchain, an entire loan process can live online. Many parties share a record of transactions and supporting documents eliminating the need for intermediaries and third parties. Once I transfer the ownership to you, it’s done. I no longer have it. Currently, we can transfer ownership, but we need someone to record the transfer.
Eliminating the Need for Third-Party Risk Managers
With distributed ledgers, you can create a smart contract on a public utility blockchain without the need for a third party to execute the contract. This allows you to build a low-cost, high-trust platform that didn’t exist before. A handful of startups are designing platforms offering secured loans on a blockchain for those that are holding digital assets for the long term. Cryptocurrency investors will be able to earn interest on their holdings while the digital lender uses them as collateral for consumer loans.
Others are testing mechanisms for collateralized lending based on the value being stored in a smart contract on a blockchain. Collateral could be a security, a bond, a property, a title, data, or gold. The asset must have been digitized and recorded on a blockchain. For instance, the Perth Mint, Australia’s official bullion mint, announced plans to issue cryptocurrency backed by gold.
Mehul Agarwal is a Customer Success, Business Development and Marketing expert working with both users and creators of technologies to achieve their Engineering & Technology goals.
Mehul has worked with several startups, mid-size and large companies from the Valley and outside especially in the FinTech, Medical Devices, Connected Devices amongst others. He has generated over $45 Mil in revenue in the last couple years building one of the largest customer accounts for one of the companies he has worked with.
He mentors startups from around the world around Sales, Strategy, Growth & Marketing both as part of accelerator programs and independent companies.
On the education front, he has a bachelor’s and master’s degree in Economics from Pune University and also a Master’s in Customer Relationship Management from Symbiosis University.
Reports estimate that over one-third of the American population has no record in any of the credit bureaus and, therefore, have no credit history. Millions of Americans do not have access to financial services, and this is an even more common scenario in developing markets. Over 80% of the African population do not use lending […]
Reports estimate that over one-third of the American population has no record in any of the credit bureaus and, therefore, have no credit history. Millions of Americans do not have access to financial services, and this is an even more common scenario in developing markets. Over 80% of the African population do not use lending or banking services because they have no fixed income. The situation creates a question mark on the relevance of traditional credit scoring agencies and their impact over the larger population. Thankfully, fintech innovators are heading towards new, alternative data sources like rent payments, cell phone data, and even social media usage to evaluate credit risk. The aim is to replace traditional credit models with a more complete assessment of a prospective borrower. The focus is to create a win-win situation for both lenders and loan seekers by providing a new foundation to lenders for credit underwriting and providing millions of borrowers a chance to step up on the credit ladder.
The Current Credit Scenario
People with a low or no credit score find it impossible to prove their eligibility for loans. The most disenfranchised are minorities and women. This then creates a vicious circle as they can’t get a loan due to no score, and they can’t improve their score because no one is ready to give them credit.
Currently, the credit score of a person is calculated depending on the information in his credit reports. This information consists of the person’s name, phone number, social security number, employment information, account information, loan repayment details, and credit card accounts.
Alternative Credit Scoring Models
The following alternative credit scoring models have a different approach, leveraging their own data sources, proprietary algorithms, and technology to disrupt existing industry systems. The idea is to reach new audiences and onboard creditworthy borrowers who are lost due to the current model’s shortcomings.
FICO Score XD
FICO (Fair Isaac Corporation) is best positioned to bring the change. Its FICO is synonymous with credit scoring and is usually the most important element in deciding if a person can qualify for a loan.
FICO’s new alternative model, FICO Score XD, developed in partnership with LexisNexis Risk Solutions and Equifax, considers alternative data sources like internet and phone bills to help users who do not have credit data attain a score.
FICO Score XD 2 was able to score over 26.5 million previously unscorable consumer files
11.8 million were without any credit file and unscorable via any traditional bureau
The new system has increased coverage from 91% of applicants to almost 98% of applicants
Another scoring model has been developed by credit reporting giant TransUnion in order to integrate alternative data and provide a solution to those who do not have any credit score. It concentrates on “trended data” as compared to only considering historical data in silos. So it not only evaluates the current situation of the borrower but also the credit details for last two years for a more comprehensive credit-scoring model. It has been able to score over 60 million borrowers who were previously unscorable.
Cignifi, based in Cambridge, Massachusetts, is an interesting alternative credit scoring startup. Backed by the Omidyar Network, it provides a platform for providing credit and marketing scores for consumers (especially in the developing world) via mobile phone behavior data. Its big data engine allows the mobile network operators and insurance partners to discover eligible customers for credit cards, loans, insurance, savings, and other banking services.
Cignifi’s main focus is on “financial inclusion,” which uses risk scoring technology to serve the unbanked population who do not have credit scores. It leverages mobile and texting patterns, routine of being at workplace or home, and contact with reputable borrowers.
This India-based fintech startup offers alternate data-based credit scores for underwriting first-time borrowers using machine learning and big data analytics. It has raised $7 million in funding and uses over 10,000 digital footprints via in-house designed APIs. It has been able to help lenders attract first-time borrowers as well as reduce the processing time from days to 30 minutes.
India alone has 800 million unscored individuals, thus the market size is huge and lenders desperately need a service which can help them tap such a massive segment of the population.
Advantages of Alternative Credit Scoring Models
Access to a wider customer base: It enables the widening of the prospective borrower base. This is extremely vital for fintech lenders as it is difficult for them to compete with the big banks on pricing. But their ability to utilize new credit models and give borrowers with “thin” credit files a chance will lead to the expansion of the entire market.
Customer experience: Alternative credit scoring also automates the process of credit decisioning and allows for a more hassle-free digitally-enhanced experience. This enhances the utility to millions of borrowers who were otherwise supposed to visit their nearest branches for processing of their loan applications.
Improved underwriting process: All the alternative data adds a layer of analytics to the existing data, as well. This gives deep insight to the underwriters and helps in developing an enhanced credit-scoring model.
These alternative credit-scoring models aim to bring banking to the unbanked. This empowers lenders to reach out to individuals who were rejected for the reason that they had no/thin credit flies. The new models will shake up the industry, and lenders incorporating them into their credit underwriting process will see better traction and stronger customer loyalty, especially from those who were earlier denied credit on a faulty premise.
News Comments Today’s main news: SoFi seeks to poach Twitter COO for CEO slot. Zopa increases investor interest rates. SoftBank considers IPO in London. TransferWise launches borderless bank account. Spotcap partners with BAWAG Group for same-day financing. Today’s main analysis: Super high-interest loans in California have boomed. Today’s thought-provoking articles: How online branding can help businesses get a loan. Today’s […]
SoFi offers Twitter COO top slot. AT: “I’m sure they’re making a lucrative offer, but the indication here is that Anthony Noto may decline. I would imagine this would be a good move for him, a high-profile move in a growing industry with a chance to make a historical mark. Of course, if Twitter counters with a more lucrative offer to keep him, then the ball will be in SoFi’s court.”
How businesses can use online branding to get a loan. AT: “To my knowledge, no alternative lender in the U.S. is using social media as the primary source of credit data. It’s more than they use alternative data as additional information to traditional metrics, but this could change.”
California’s super high-interest loans are booming. AT: “I’d be curious to see how they’re doing in other states, as well. Given that Texas-based Elevate Credit is one of the top three lenders in this segment, it’s likely that other states have seen a similar increase in these types of loans.”
Anthony Noto, a top Twitter Inc. executive, is in discussions to become the next chief executive of Social Finance Inc., according to people familiar with the matter, as the online lender grapples with accusations of improper workplace culture.
The San Francisco-based company has offered the job to Mr. Noto, currently Twitter’s operations chief and before that a top Silicon Valley banker atGoldman Sachs GroupInc.,people familiar with the matter said. Mr. Noto is likely to make a decision in the coming days, the people said.
He may turn down the offer, as terms haven’t yet been completed, or Twitter might lobby hard to keep him, especially with CEO Jack Dorsey splitting his time between the social-media service and Square.
An increasing number of the largest online lenders, such as Kabbage (a ValuePenguin affiliate) and Funding Circle (also a ValuePenguin affiliate), are relying on online data in addition to traditional data points to gain a fuller picture of a business’s health.
Kabbage, which recently received $200 million in funding from Credit Suisse, uses a fully automated underwriting process (involving no humans) to approve applicants and requires business owners to link online accounts, which run the gamut from bank accounts to vendor accounts, to complete an application.
Even traditional lenders are getting in on this trend. JPMorgan Chase (a ValuePenguin affiliate), which recently renewed its partnership with online lender OnDeck (also a ValuePenguin affiliate), the largest online lender to small businesses, uses the latter’s underwriting technology, which considers online data points, to help it offer online business loans.
Not long ago, personal loans of this size with sky-high interest rates were nearly unheard of in California. But over the last decade, they’ve exploded in popularity as struggling households — typically with poor credit scores — have found a new source of quick cash from an emerging class of online lenders.
These pricey loans are perfectly legal in California and a handful of other states with lax lending rules. While California has strict rules governing payday loans, and a complicated system of interest-rate caps for installment loans of less than $2,500, there’s no limit to the amount of interest on bigger loans.
In 2009, Californians took out $214 million in installment loans of between $2,500 and $5,000, now the most common size of loan without a rate cap, according to the state Department of Business Oversight. In 2016, the volume hit $1.6 billion. Loans with triple-digit rates accounted for more than half, or $879 million — a nearly 40-fold increase since 2009.
The number of loans between $5,000 and $10,000 with triple-digit rates also has seen a dramatic 5,500% increase, though they are less common. In 2016, loans of that size totaled $1.06 billion, with $224 million carrying rates of 100% or higher.
Many of the loans can be tied to just three lenders, who account for half of the triple-digit interest rate loans in the popular $2,500-to-$5,000 size range. LoanMe, Cincinnati firm Check ‘n Go and Fort Worth’s Elevate Credit each issued more than $100 million in such loans in 2016, as well as tens of millions of dollars of loans up to $10,000 with triple-digit APRs.
Within this large document, there are four key actions being proposed:
Affordability test: This imposes two burdens on payday lenders. First, conducting an affordability analysis would increase the cost of underwriting a loan. Second, people generally turn to payday lenders when they are broke.
Limit payday rollovers
Exemptions made for alternatives to payday lenders, including credit unions and community banks: If a lender derives less than 10% of its revenue from payday loans, it is exempt from some of the most onerous rules. This particular restriction is odd. Why is the hated payday lending product acceptable, so long as the institution making the loan only generates 9.99% of its revenue from such activities? Are high rates and frequent rollovers acceptable when coming from a bank? Or is there a presumption that payday lenders are evil while bankers are not?
Limit on the number of times a checking account can be debited. This rule limits the lender to two unsuccessful debit attempts. Afterwards, the lender can only attempt to debit the account if it receives authorization from the borrower.
The outrageously high APRs paid on payday loans can make anyone’s stomach churn. But why are APRs so high? I believe there are three main drivers:
Risks are high: The people using payday loans are very high risk borrowers.
Price competition is absent: For a payday loan, people value speed and access.
Good behavior does not get rewarded: Payday lenders generally do not report to credit bureaus.
The Consumer Financial Protection Bureau on Thursday dropped a lawsuit against four payday lenders.
Since 2012, two of the firms — Golden Valley and Silver Cloud Financial — offered online loans between $300 and $1,200 with interest rates of up to 950%. The other two firms — Mountain Summit Financial and Majestic Lake Financial — also offered similar terms on loans, according to the bureau.
BofA added about 2 million users to its digital channels, predominantly to mobile. The bank’s active digital users jumped from 32.9 million to 34.9 million annually, an increase largely driven by mobile banking users, which increased by 2.6 million users year-over-year (YoY).
Engagement is rising too. Mobile channel usage rose 34% YoY to reach 1.3 billion interactions in the quarter.
BofA consistently updated its digital and mobile offerings throughout 2017, adding contactless ATM functionality, for example, and integrating tools like the popular peer-to-peer (P2P) offering Zelle. These innovations have likely contributed to rising interactions.
Just under 30 percent of U.S. households are underbanked or unbanked, according to the FDIC. What these terms mean has been up for debate and subject to misconceptions. Let’s look at some of the most pernicious myths regarding underbanked Americans and debunk them:
The person-to-person payments service Zelle differentiates itself from rivals by promising users that transactions sent over its network will clear in near-real time. Yet in recent months, the service has faced a number of complaints from consumers who say they are having problems sending or receiving money or setting up accounts in the first place.
Zelle has acknowledged the problems, but says the occasional delay is the price some users will have to pay as the big banks’ rival to PayPal and Venmo aims to create one of the industry’s strictest fraud-prevention programs.
One of the biggest (and most unique) new companies working in the online lending space is Loanable – a platform that brings together crowdfunding and peer-to-peer lending, but with a twist.
According to Bernard Worth, who created Loanable along with co-founder Justin Straight, there is a whopping $1.3 trillion in American student loan debt.
This system, which just launched in October of this year, is designed specifically for loans from friends and families. Loanable is an innovative way to get a low-interest loan from multiple friends and family members, without of lot of the awkwardness and tension that’s typically involved with borrowing from people you know.
The friends and family loan set-up process is pretty straightforward. You simply need to enter some information:
The full amount of the loan
Each lender’s name, address and email
The borrower’s name, address and email
The interest rate – which is usually between 2% and 10% for friends and family loans
With tax season around the corner you might have noticed a deluge of Jon Hamm commercials for interest free tax refund advance loans. This is a newer product used by tax preparation firms to build their customer base around tax season.
Zopa, one of the largest peer to peer lenders in the UK, has announced an increase in interest rates paid to investors. Zopa currently offers two diversified investment tiers: Zopa Core and Zopa Plus. Returns have increased from 3.7% for Core and 4.5% for Plus respectively. The higher rate reflected by Plus is indicative of an increase in risk profile. Zopa said this is the first time target returns have increased since 2015.
Softbank Group, the Japanese technology conglomerate, is considering the sale of 30 per cent of the shares in Softbank Corp, a subsidiary that is Japan’s third-biggest mobile phone operator, in an initial public offering.
The mega-deal could raise up to two trillion yen (£13 billion) and may take place this year in Tokyo and London, with the proceeds channelled into investments in new technology businesses, the newspaper Nikkei reported last week.
Research from an independent senior recruitment specialist firm, Tindall Perry, reveals that 74 per cent of finance directors describe their knowledge of alternative finance as average or above. However, only a quarter said they were comfortable with accessing crowdfunding or peer-to-peer lending.
In contrast, 85 per cent of companies said that they understood how best to access asset-based lending (ABL), while invoice finance, trade finance and venture capital all saw a positive response rate of between 55 and 75 per cent.
Despite this, traditional bank lending remained the funding of choice for financial directors, with 83 per cent suggesting that they would approach their bank for finance in the first instance.
Envestnet | Yodlee has launched a single API solution to make it easier to comply with the UK’s PSD2 and open banking API specifications for account information services, reports David Penn at Finovate (FinTech Futures’ sister company).
“We’ve recruited more than 1,000 specialised consultants across BCG working on topics which didn’t exist just five years ago,” says Mr Morel. They are technologists, data scientists and process specialists who help banks decide what to prioritise and how to design and implement solutions. Most of those newcomers work in financial services, including 100 who work with UK institutions.
In fact, with real estate crowdfunding services like Fundrise Reviews you can invest with as little as £500 in commercial real estate. Something that means you could be looking at a return of over 10 per cent, not bad for such a small investment.
Peer to peer lending is another fantastic option for investors that have a smaller pool of capital to work from.
The past New Year’s Day holiday might not have been a time of celebration for some Peer-to-Peer (P2P) investors in China.
Several Chinese online lending platforms announced a repayment delay or liquidation amid tightening government regulations.
On Dec. 26, 2017, a Beijing-based online lending platform ishoutou.com made an online announcement that it was going into liquidation due to compliance risks. It promised to pay back all loans by 30 percent, 30 percent and 40 percent respectively in the three months from February to April.
However, the company owner, Yang Yinghua, went missing the next day.
And yet it is Orange that has launched one of the most audacious attempts to break into mainstream banking and challenge tarnished incumbents. A couple of months ago Orange Bank was launched with a mission to attract 2m clients and shake up the staid world of French finance.
The shift to smartphone banking should put telecom operators, handset makers and the big technology groups in a strong position to go head to head with the traditional banks.
Springhouse today announced that it has received Morningstar Credit Ratings, LLC’s MOR RV2 residential-vendor ranking as an asset valuation provider. Morningstar’s forecast for the ranking is Positive.
As a member of the Altisource Portfolio Solutions S.A. family of businesses (“Altisource”), Springhouse leverages Altisource’s shared services.
Eiffel Investment Group actively supports the development of digital lending throughout Europe.
We are excited to sponsor the first EUROPEAN DIGITAL LENDING AWARDS.
The event will take place on February 1st, 2018, in Paris (25 Rue du Petit Musc, 75004 Paris) at 7 pm. If you would like to attend, please send us an email at firstname.lastname@example.org (advanced registration is mandatory).
Launched in January, the company’s ‘borderless’ account – coupled with a debit card – allows users to hold up to twenty-eight currencies. Once signed up, account holders can carry out transactions in a currency of their choice as they travel around the world.
But there are other new players in the market. For instance, Revolut – which styles itself as a digital banking alternative, offers a prepaid debit card that allows users to hold up to sixteen currencies. Again, transactions can be carried out in the currency of choice.
Meanwhile, WorldFirst – a foreign exchange broker serving companies and relatively wealthy individuals – last year announced that it was launching a World Account, Aimed at SMEs, the new account offers the ability to open local bank accounts overseas and hold dollars, sterling and euros.
To Illustrate the potential demand for its service, Worldfirst cited research suggesting that small and medium-sized companies were carrying out foreign-exchange trades to a value of £76bn every month.
According to Bank of America’s Year-end Millennial Snapshot, 49% of Millennials believed that the Great Recession drastically altered their attitudes about banks, specifically with regard to their saving, investment and expenditure.
According to PwC’s Global FinTech Report 2017, FinTech startup funding is over $40 billion in cumulative investment, growing at a compound annual growth rate (CAGR) of 41% over the last four years.
Embrace the Millennial Banking Revolution
59% of Millennials interviewed by BNY Mellon says they’ve never come across a financial product specifically meant for them. A report by The Millennial Disruption Index cited that all the four leading banks in the US are among the least-loved brands by millennials.
AlfaToken, a service enabling startups and innovative entrepreneurs to create their own ICO tokens and smart contracts without coding skills, is gearing about to conduct its Initial Token Offering with the help of ICOBox, the world’s leading provider of ICO solutions. AlfaToken plans to offer services in 14 smart contract areas, from initial coin offerings and real estate rentals, lending and insurance, to business process management, smart homes and property transfers.
Founded in 2017, AlfaToken identified a gap in the ICO market where initial coin offerings are forecast to rise from 43 in 2016 to 537 in 2017, according to coinmarketcap.com. In particular, the company perceived an opportunity for its Ethereum smart contracts in the real estate rentals market, worth $2.8 billion (Airbnb forecasts), in the peer-to-peer lending market (including mortgages), worth up to $180 billion according to Business Insider, and also the insurance market valued at $4.5 trillion according to a 2016 report by the Institute of International Finance.
Every digital financial transaction you’ve ever made in your life has had to go through a bank or large financial institution at some point. They authorise, facilitate and record the transaction, often taking a cut along the way. Blockchain essentially replaces the middleman in this process. It’s international, unregulated, instant and unhackable.
94% of economists surveyed by finder.com.au in November 2017 expect blockchain will have widespread use in the financial sector and economy.
2. Biometric payments
Although biometric payments are increasing, finder.com.au research shows 60% of Aussies – over 11 million people – either feel uncomfortable using biometric identification when logging on to their mobile banking apps, or aren’t really sure about it.
3. The end of our low-interest world
Australia’s cash rate sat stagnant throughout 2017 at a record low of 1.5%, producing low savings rates, cheap mortgages and escalating property prices.
4. The declining human face of banking
A sharp rise in mobile and online banking has meant Australians are less likely than ever to need to visit their local branch. We expect the number of branches to fall further in rural, regional and remote areas.
5. The rise of one-to-one lending
For example, the average three-year term deposit in December 2017 paid 2.55% interest. However, peer-to-peer lender RateSetter are currently offering 7.4% for the same period.
6. The disappearance of ATMs and cheques
The number of ATM withdrawals per month has fallen from a high of 73 million in 2010 to just 47 million in 2017.
It has been noted that youngsters are averting eyes towards quick personal loans with lesser interest rates rather than the credit cards, says Aditya Kumar, founder of Qbera, a Bengaluru based fintech company. They recently compiled a stats on spending on travel loan trends in 2017. “Millennials, covering more than 50 percent of the Indian population are constantly looking for online digital platforms to plan their finances for holidays; unlike their predecessors who’ve always relied on savings. It has been a regular practice to narrow down their search to fintech lenders for financing their travel needs,” he adds.
According to his company’sstatistical report, out of 1700 applicants of travel loans till last year November, the age of 728 applicants is below 28 years and 105 female applicants within the age span of 20-28 years (both single and married), he adds.
The Financial Services Authority (OJK) is planning to issue a policy in financial services institutions, including guiding principles for Digital Financial Services Providers that include registration and licensing mechanisms as well as the application of regulatory sandbox and policy on crowdfunding.
Not only has the US Federal Reserve started to raise interest rates – a move mirrored by China’s central bank and the Hong Kong Monetary Authority with more developed countries expected to follow suit – but a market correction may be in the works following a strong run in both the US and Malaysian stock markets.
Yet despite its prices taking a plunge recently, its demand is still going strong. Similarly, ethereum, ripple, litecoin and Zcash continue to enjoy the mania status garnered by anything related to cryptocurrency. Equally enticing opportunities are abound with the rapid growth of equity crowdfunding (ECF) and peer to peer (P2P) lending platforms.
Russia’s biggest lender Sberbank plans to help small firms raise funds from private investors with a peer-to-business platform, three sources familiar with the plans said, competing with two other ventures that support the cash-starved companies.
The state bank’s foray into p2b lending suggests it sees a revival in fortunes for small businesses as consumer spending picks up.
It also reflects the commitment of chief executive German Gref to enhance the bank’s use of new technology.
In the U.S., consumers tend to take credit for granted. Access to credit is nearly ubiquitous, and the three major credit unions ensure that the vast majority of Americans have a credit score, which allows them to be assessed for risk by potential lenders considering making an offer for a loan product. But the recent […]
In the U.S., consumers tend to take credit for granted. Access to credit is nearly ubiquitous, and the three major credit unions ensure that the vast majority of Americans have a credit score, which allows them to be assessed for risk by potential lenders considering making an offer for a loan product. But the recent Equifax data breach proved that there are drawbacks to the robust credit scoring system, even in the U.S. Pave seeks to solve that problem with their Global Credit Profile, a decentralized database that allows the consumer to control who has access to their credit information.
Why Credit Data Should Be Decentralized
As the Equifax data breach shows, no one’s credit information is secure. It’s estimated that 143 million Americans and as many as 400,000 Brits may have been affected by the breach. Since the breach has been reported, there has been a run on credit monitoring products. And none of the credit bureaus can guarantee that hackers won’t gain access to their data. In fact, its getting increasingly more difficult for any company using the Web for database storage to insure the data they keep is 100% secure.
What Pave wants to do is solve that core data issue for the consumer.
“We’re looking at the existing paradigm and saying it’s broken,” Pave CEO Oren Bass said. “Not too many people are looking to solve the data access problem on a global basis.”
Bass said the three major credit bureaus—Experian, Equifax, and TransUnion—collect information on individuals, which they get from banks, credit card companies, and other businesses that issue credit, and sell that data to third parties. The individual doesn’t get any of the money. They’re cut out of the equation altogether. And who can guarantee that the buyer of the data can keep it safe from bad actors? Pave’s solution is to wrap up the data in a digital wallet-like security lock connected to the blockchain.
Pave’s Meandering Path to Its Data Security Solution
Bass started Pave in 2012 with co-founders Justin Mitchell and Sal Lahoud. They founded the company as a response to the 2008 financial crisis. Their primary product was an income sharing agreement for people with limited credit history, and the target audience was millennials.
“Due to lack of data and legal clarity on the product, it didn’t have staying power,” Bass said, “so we pivoted to include short-term consumer loans.”
Their intent was to lend to people with limited credit histories, but they struggled with getting a solid process for underwriting them. That’s when they wrote an algorithm to assess creditworthiness and were delighted to see it worked so well. They ended up lending to 1,700 people with limited credit histories.
Then, 2016 happened. A difficult year for online lenders on the whole, it proved to be very difficult for Pave. “We capsized as a marketplace lender,” Bass said. “We didn’t have the equity capital to become a balance sheet lender.” So they started using their technology to solve a different problem—the problem of data access for the underserved population.
Earlier this year, Pave ended a seed round and funded half a million dollars in startup capital for the Global Credit Profile. Since 2015, they’ve managed to fund $18 million including a Series A funding round that year.
What the Global Credit Profile Does
The gist of Pave’s Global Credit Profile consists of its three buckets. They collect data for marketing, or prospecting, for underwriting, and to assess the value of consumer information. But when you collect information on individuals, you have to make sure that data is secure. That’s why they decided to connect the data to the blockchain.
Using the Global Credit Profile, users will be able to:
Monitor and control their own financial data in real time
Dispute errors and omissions
Link credit accounts so that more data is included in their profile
Port their data anywhere they want to globally to ensure they have access to the best credit products in any country they live or travel to
Control who gains access to the data and get paid for that access
Pave’s Global Credit Profile will work by leveraging the inherent decentralization of the blockchain as a distributed ledger allowing each credit transaction to be approved using the same or similar processes used to record cryptocurrency transactions in real time today. Any information currently collected by the credit bureaus can be kept in a consumer’s self-controlled file including rent and mortgage payments, utility bill payments, lines of credit, and more. Plus, the credit profile can include social data gathered from user’s social media accounts.
Each user gets an IP address and a key to enable the application. The user can access all of their financial information in one location.
Who is Using the Global Credit Profile Right Now?
In pre-launch, Pave got quite a few users, but it escalated when they decided to lend to consumers. They have lent $23 million to 1,700 users. Current users include many in Africa and India who connect their utility bills and payment data.
Pave’s technology is powered by a core data center including visualization and data integration. The data is hosted on Amazon Web Services (AWS). For data storage, they use IPFS. Due to the decentralized nature of their system, a hacker wanting access to credit information would need to hack as many 145 million different files with information on different individuals within each file.
The bulk of Pave’s user base today are immigrants, people who have a credit history abroad but don’t have a credit profile in the U.S. where they are living. They’re new to credit, but they have a low profile. They can use their education history, social data, and utility payments. Bass said they want to help these individuals build a credit profile and work their way up to prime status.
“We hope the credit bureaus will partner with us and use our technology to protect against the security issues they have,” Bass said.
Bass sees alternative data becoming the norm in credit profiling in the future. That will include machine learning algorithms, social data, and utility payments for many of the world’s unbanked and underbanked. They currently have plans to raise more capital through an ICO token issue, but they’re currently working with private investors. Ultimately, they want to build an ecosystem that will allow others to develop and build apps that interact with the Global Credit Profile. To make that happen, they need more people on their team with alternative credit, data, and programming expertise.
“The only way we’ll be successful is to take on the status quo of the credit bureaus,” Bass said. And Pave is off to a good start.
When FICO first introduced the credit score in the 1980s, it had good intentions: To level the playing field for consumers and make decisions easier for lenders. Nearly 30 years later, we still use the exact same model. And while it’s never been perfect, its flaws have become much more apparent in recent years as […]
When FICO first introduced the credit score in the 1980s, it had good intentions: To level the playing field for consumers and make decisions easier for lenders.
Nearly 30 years later, we still use the exact same model. And while it’s never been perfect, its flaws have become much more apparent in recent years as consumers’ financial habits have started to evolve.
Currently, we use a traditional credit score to gauge creditworthiness for untraditional consumers, and this situation has created serious limitations. Fortunately, a solution is well within reach, and it comes in the form of a new, alternative credit score.
Unpacking the Value of Alternative Credit Scoring
In order to meet the evolving needs of consumers, it’s time to introduce a new type of credit score — one that looks at data beyond traditional financial institutions in order to understand the creditworthiness of the growing number of consumers who choose to manage their finances in new ways.
While there’s no single prevailing model for alternative credit scoring, many have already been introduced with great success. These models typically rely on a combination of the following activities as a way to gauge consumers’ propensity to pay bills:
Traditional loan repayment behavior
Non-loan payment data (e.g. utility or rent payments)
Cash flow information
Home, job and lifestyle stability information
Education and employment data
Personal and professional connections
Some of the most common data points used to understand these activities include:
Checking and savings account transactions to understand cash flow based on income, spending habits and account balances
Utility bill, rent, cable and/or mobile phone payments to understand intent to make payments and typical payment patterns (early, on-time, late)
Mobile phone location to verify home and work addresses as a way to understand stability
Social media activity to assess home, job and lifestyle stability, education and occupational attainment, online behaviors and personal and professional connections
While the latter two data points (mobile phone location and social media activity) are considered less reliable than bank account and bill payment data, some alternative credit scoring models have used them with success.
Ultimately, with the right data in place, these alternative models can prove just as trustworthy as the traditional FICO credit score and provide several benefits for consumers and lenders alike.
Trust in Alternative Credit Scoring Models
The trustworthiness of alternative credit scoring is extremely important, as lenders must be able to rely on these models to limit their risk. Fortunately, there are several data points that have proven their worth.
According to a recent study on the predictive value of alternative credit scores by the Center for Financial Services Innovation, utility bills and rent payments are among the most reliable data points used in alternative credit scoring models. The fact that these data points are easy to collect only makes them all the more appealing.
The study also reports that many consumers who would be unable to obtain a loan using traditional credit scoring models actually represent prime or near-prime credit risk for lenders, making alternative models that can generate scores for most adults an ideal solution to safely broaden access to credit.
Of course studies are one thing. How all of this works in practice is quite another. So far, though, the results have been positive. Consider the case of TransUnion, which now uses an alternative credit scoring model that it calls CreditVision Link. The firm has over three billion non-traditional data points for more than 260 US adults including property, tax, and deed records; and checking, debit, or payday lending information. TransUnion has used these alternative data points to accurately score more than 90% of applicants who would have been unscorable under the traditional model.
Benefits of Alternative Credit Scoring Models
Once lenders establish trust in alternative credit scoring models, both lenders and consumers can begin to reap the benefits.
For lenders, the benefits of alternative credit scoring typically include:
Enhanced predictions due to access to more timely and holistic information on consumers’ spending habits and payment behavior
Lower costs and increased efficiency due to the use of less expensive data sources and faster data collection methods
Reduced discrimination due to the use of automated data collection, which removes the need for manual and discretionary decision making
For consumers, benefits of alternative credit scoring typically include:
Increased access to credit due to the use of data points beyond traditional financial behavior that fail to capture information on the millions of unbanked and underbanked consumers
More accurate portrayal of creditworthiness due to the use of more timely information, which can make it easier for consumers to build credit
Better service due to a more efficient and less discretionary processes
When all is said and done, FactorTrust, the alternative credit bureau, reports that underbanked US adults represent $105 billion in untapped opportunity for lenders while VantageScore Solutions finds that alternative credit scoring could help approximately 7.6 million consumers who are currently unscorable reach a credit score of 620 or higher.
Why It’s Time for a Change
Why exactly do we need to introduce a new model for credit scoring? There are many factors driving the need for change, but they are largely led by Millennials who are unlike any generation before them. There’s no shortage of articles that try to pick out defining characteristics of the Millennial generation, good and bad — they’re digital, they’re narcissistic, they support brands with a cause.
And whether or not these broad strokes actually define Millennials, one thing that is certain is that this generation approaches many different everyday challenges in their own unique way. Perhaps the best example of this is how they manage their finances.
A New Financial Mindset
Not too long ago, everyone “banked.” We opened checking and savings accounts and we used credit cards — it was just the norm. Those who didn’t follow this pattern typically did so due to dire financial circumstances.
Today, however, we live in a different world. We live in a world shaped by a great recession in which many people were failed by the very banks that they trusted to keep their finances safe. This experience hit particularly hard for Millennials, who came of age in the throes of the recession.
As a result, many Americans (led by Millennials, but not confined to this generation) have started to re-think how they handle their finances.
Growing Financial Options
In addition to world events shaping a new financial mindset, so too has the rise of technology.
Today, consumers have far more options than they once did for how to store and spend money. For instance, many online options now exist that help consumers manage their money and retain access to it digitally, all without any involvement from traditional financial institutions. One of the best examples of these options is Amazon Cash, which enables consumers without credit or debit cards to load cash directly to their Amazon accounts via kiosks at retailers like CVS.
A Change in Banking Status Norms
As a result of a new financial mindset and the growing number of non-traditional financial options, a change in banking status norms has set in.
According to the FDIC, 27% of US households are unbanked or underbanked. Those terms are defined as follows:
Unbanked: No one in the household has a checking or savings account.
Underbanked: The household has an account at an insured institution, but also goes outside of the banking system to alternative financial providers for services and products like money orders, check cashing, international remittances, payday loans, refund anticipation loans, rent-to-own services, pawn shop loans, and auto title loans.
A large portion of consumers who fall into this group cited non-financial reasons for retaining an unbanked or underbanked status including a lack of trust in banks, privacy concerns, and high or unpredictable bank account fees.
Although the growing number of financial options may make it easy for these unbanked and underbanked households to get by without engaging traditional financial institutions, this status poses a major problem when it comes to credit.
From obtaining a loan with which to buy a house or underwriting for insurance to gauging responsibility when applying for a new job, credit scores are used for a variety of purposes. As a result, credit counts for a lot when it comes to mobility in the US economy.
However, because of how credit scores are traditionally calculated, those who are unbanked and underbanked are typically credit invisible (meaning they have no file with any of the major credit bureaus) or credit unscorable (meaning they have a file with at least one of the major credit bureaus but the information is either too little or too stale to generate a reliable score). Today, 45 million US adults are credit invisible or credit unscorable.
Essentially, this means that the growing group of unbanked and underbanked consumers is severely limited when it comes to activities like buying a house.
It’s Time to Embrace Alternative Credit Scoring Models
Under the status quo, the vast majority of lenders use the traditional FICO credit scoring model. However, this model prohibits 45 million US adults from obtaining credit due to their banking choices rather than the risk they pose to lenders, and seriously limits upward social and economic mobility as a result. Perhaps the most concerning part of this problem is that the overwhelming majority of these credit invisible and credit unscorable consumers are actually good candidates to receive credit.
At a time when more and more consumers are choosing to go outside the traditional financial system, whether it’s because of a lack of trust in banks, the growing number of alternative financial options, or anything else, it’s clear that we need a new type of credit score.
Fortunately, the solution is well within reach. Many firms have already created alternative credit scoring models based on data points like checking and saving account data and utility bill, rent, and mobile phone payment history, and these models have proven their trustworthiness time and again.
Best of all, alternative credit scoring models provide benefits for lenders and consumers alike by enhancing creditworthiness predictions, making the credit application process more efficient and less expensive, and expanding access to credit in a risk-averse way.
In the US, there are tens of millions who do not have a reliable FICO score, either because their credit history is not sufficient or it is non-existent. This becomes a vicious cycle and an important reason why subprime borrowers struggle to obtain credit. Traditional lenders are dependent on FICO, and handicapped as they lack […]
In the US, there are tens of millions who do not have a reliable FICO score, either because their credit history is not sufficient or it is non-existent. This becomes a vicious cycle and an important reason why subprime borrowers struggle to obtain credit. Traditional lenders are dependent on FICO, and handicapped as they lack qualitative information about subprime borrowers who might otherwise be creditworthy. Clarity Credit Bureau was born with the clear goal to collect subprime data and cater to this population, which is not being served properly by the big three credit bureaus.
Over the years, the company has been able to carve its own niche in the subprime market. Now, lenders and financial institutions are using Clarity for subprime borrowers across the entire credit spectrum, and they are using the bureau in conjunction with other credit bureaus in order evaluate credit applications at a more granular level. This layering of Clarity above traditional data has created value for Clarity clients as they are able to offer credit to a wider client base with the assurance that they are creditworthy.
Around 200-220 million consumers within the age group of 19 to 65 form the largest part of the credit consumer population in America. About one-third of this nearly 70 million person group are subprime borrowers. Sixty million are covered by Clarity, which is nearly 80% of the entire subprime market. This extensive and elaborate data is what makes the company stand out and be the sought after credit rating agency for subprime borrowers. on average, the entertains anywhere between 400,000 to 800,000 report requests every day.
Clarity does not use FICO data. The company has developed over 30 different report products. They also use the same information as traditional bureaus such as credit history, identity verification, etc. The only difference is that Clarity focuses on data collection for a different population set.
Traditional Bureaus as Laggards
Traditional Bureaus lag behind Clarity Credit Bureau due to the paucity of an adequate mechanism to have access to the subprime borrower data. Typically, financial institutions do not provide financial services to subprime customers without FICO data, and they report to credit bureaus.
But, if a lender client of Clarity requests a report on a customer and extends credit to that customer, the financial service provider submits the performance of the credit line to Clarity. It is structured as a “Give and Get” model, similar to other credit bureaus.
Competitive Edge in the Market
According to the Clarity’s founder, Clarity Credit Bureau is the largest bureau in the subprime credit reporting space. Moreover, it has succeeded in carving its niche as the most innovative player in this segment, and its revenues grew by over 70% from 2014 to 2015.
A Solution for Loan Stacking
Loan stacking is a serious threat in the P2P lending space. Borrowers have managed to take advantage of lenders due to the shortcomings of the alternative lending industry. To fend off loan stacking, lenders have been using a consortium approach for 10 years. This involves a group of lenders getting together and sharing every approved application among the consortium. It’s a temporary fix as information sharing is restricted to the consortium, and if the consumer gets a loan from a non-consortium player like a tribal lender or payday lender, the original lender would not be any wiser.
Keeping this in mind, Clarity has developed a real-time solution: Temporary Account Record, a patent-pending solution that will close the reporting gap from hours to minutes, which helps reduce the risk of underwriting unsecured loans. Everyone who is part of the Clarity family and using this technology will be notified when a lender approves a loan.
In today’s world, where technology changes hands in mere weeks, methods used by the three big rating bureaus are quite off the pace. These bureaus use archiving technology for updating their database. Archiving technology will add new data to an existing database randomly from time to time. The resulting report generated might not be up to date or accurate. Clarity, however, uses real-time technology for reporting where the updated information is gathered and stored in the original format along with the date and timestamp.
Clarity Credit Bureau makes use of MySQL, an open source relational database, and the Bongo database system to capture and leverage big data. It uses an on-premise database architecture, instead of operating on the cloud, with multiple data centers complying with industry standard security and encryption certification. Though this is a costly solution, it is necessary as they deal with extremely sensitive public data.
Clarity Credit Bureau was founded in 2008 and is headquartered in Clearwater, Florida with the aim to provide unprecedented credit risk solutions to lenders and service providers that deal with nonprime consumers. The company also collects and analyzes multiple data points on the behavior of nonprime consumers, and endeavors to provide customized data-driven solutions to clients to meet their specific needs and circumstances.
Clarity Credit Bureau has over 100 employees and around 600 clients.
Founder and Manpower
Tim Ranney, the President and CEO at Clarity Services, has expertise in the IT sector and large database systems. Prior to the inception of Clarity Credit Bureau, he spent nearly 20 years in Internet security and risk management, serving as chief operating officer of an industry leader and senior executive for both Network Solutions and VeriSign.