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Auto Loan Origination: Is the Dealer Still King in 2023?

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Auto Loan Origination:
Is the Dealer Still King in 2023?

In the ever-evolving landscape of auto financing, the dynamics of the auto loan origination process have shifted dramatically, thanks to the integration of fintech innovations. This transformation has ushered in a new era where data-driven decisions play a pivotal role in reshaping the automotive lending industry. In this comprehensive guide, we delve deep into the world of auto loan origination, dissecting its process, fraud detection, and the role of fintech.

What is Auto Loan Origination?

Auto loan origination, at its core, is the process through which financial institutions, such as banks, credit unions, or online lenders, create and process loans for individuals seeking to purchase vehicles. This process encompasses everything from the initial loan application to the disbursal of funds.

Understanding Loan Origination System:

A crucial component of auto loan origination is the loan origination system, often referred to as LOS. This is a specialized software platform used by lenders to manage and streamline the loan application process. The LOS ensures that all necessary information is collected, verified, and assessed in a consistent and efficient manner.

How Does the Process of Auto Loan Origination Function?

The auto loan origination process can be broken down into several key stages:

  1. Application Submission: The journey begins when a prospective borrower submits their loan application. This application typically includes personal information, financial details, and the desired loan amount.
  2. Credit Evaluation: Lenders evaluate the applicant’s creditworthiness by examining their credit score, credit history, and other financial factors. The fintech-driven auto loan origination system plays a critical role in automating this assessment.
  3. Data Gathering: In addition to credit data, lenders may gather information related to the vehicle being financed, such as its make, model, and purchase price.
  4. Decisioning: This is where fintech takes center stage. Decisioning, powered by advanced algorithms and big data analytics, helps lenders determine whether to approve or decline the loan application.
  5. Documentation and Verification: Once a loan is approved, lenders require applicants to provide documentation to verify the information provided in their application. This step helps mitigate potential fraud risks and ensures compliance with regulatory requirements.
  6. Loan Funding: After successful verification, the lender disburses the loan amount to the borrower or, in many cases, directly to the dealer.

Decision-Making for Automotive Lending with Comprehensive Data – Sources and Services

In the modern auto loan origination landscape, data is paramount. Lenders now have access to an array of data sources and services that enable them to make more informed lending decisions.

  • Credit Bureaus: Traditional credit reporting agencies provide credit reports and scores, which remain a cornerstone of the auto loan origination process. Lenders use these reports to assess creditworthiness and determine interest rates.
  • Alternative Data: Beyond traditional credit data, fintech lenders tap into various data sources, such as utility bill payments, rental history, and even social media profiles, to build a more comprehensive view of an applicant’s financial health.
  • Machine Learning: Advanced machine learning algorithms analyze vast datasets to identify patterns and trends, aiding in predicting an applicant’s likelihood of default or delinquency, and their propensity to pay
  • Fraud Detection Services: To combat potential fraud in auto loan origination, lenders employ specialized services that flag suspicious applications and activities.

Identify Potential Auto Loan Fraud with Decisioning

Auto loan origination fraud is a persistent challenge in the industry. Fraudsters employ various tactics to secure loans they have no intention of repaying, resulting in financial losses for lenders. Fortunately, advanced decisioning systems equipped with fraud detection capabilities are instrumental in identifying and mitigating such risks. These systems analyze multiple data points to flag inconsistencies, suspicious behavior, or potentially fraudulent applications.

The Evolution of Auto Financing

The automotive industry has undergone a remarkable transformation since the days of the Model T, priced at a modest $850, equivalent to approximately $20,000 in today’s currency. During that era, financing became a necessity, as few individuals had such substantial sums readily available. Recognizing the opportunity, companies like GM and Ford swiftly established financing divisions, not only boosting car sales but also diversifying their revenue streams—a stroke of genius!

For a century, auto dealerships held sway in the auto lending domain, facing minimal competition beyond their peers. Buyers would stroll onto the dealership lot, engage in negotiations over lukewarm coffee, haggle over sticker prices, and drive off in a new car, savoring the scent of fresh upholstery. Trade-ins and financing were mere formalities in the car-buying ritual.

However, as time progressed, winds of change began to sweep through the industry, reshaping the dynamics of auto financing.

The Rise of Informed Consumers

In today’s automotive financing landscape, consumers wield an unprecedented amount of information. As the saying goes, knowledge is power, and this newfound knowledge empowers buyers while challenging the traditional balance of power in the auto lending domain.

This scenario parallels a scene from Game of Thrones, where Lord Petyr “Littlefinger” Baelish engages in a tense exchange with Cersei Lannister. In this dialogue, “Knowledge is power” is asserted by Baelish, but Cersei counters with a simple yet profound statement: “Power is power.” This mirrors the contemporary auto lending dynamic, with buyers armed with knowledge seeking to assert their position in the auto financing realm.

Disrupting the Status Quo

Waiting around at a dealership in order to complete financing paperwork can be tedious. And consumers these days aren’t content to wait around for long. But when consumers express dissatisfaction with an industry, it creates an opening for innovative businesses to disrupt the status quo. Hence, competition in auto financing is growing, and dealerships are working harder than ever to secure financing alongside car sales.

The Future of Auto Finance

A peek into the future of auto financing reveals a landscape where financing can be secured with a simple click, and a new car can be delivered to your doorstep within hours, bypassing the need to set foot in a dealership.

Threats to the Dealership Finance and Sales Process

  1. Direct Lending: Direct lending has become commonplace and competitive, challenging traditional dealership financing.
  2. Aggregators: Aggregator platforms are offering transparency to buyers while streamlining the often cumbersome paperwork for dealers.
  3. Online Upstarts: Digital platforms are emerging, catering to customers who prefer an online experience over visiting a dealership.
  4. Brands Entering the Game: Car manufacturers themselves are testing the waters with direct-to-consumer financing.

However, amidst this evolution, one constant remains—the importance of technology in enhancing both business and customer experiences.

Relationships That Stand the Test of Time

In a world where relationships are the key to longevity in lending, dealers must treat their customers as equals. The hard sell, lengthy application processes, and delayed approvals no longer suffice. Customers have alternatives, and they won’t wait.

To retain their throne in auto loan origination, dealerships must offer an experience that aligns with customer expectations. In today’s digital-first world, this means a seamless and competitive experience that values the customer’s time and understanding.

Seamless Experience:

  • Streamlined Process: The finance process should be quick and easy, with minimal paperwork.
  • Rapid Decision-Making: Technology-driven decisioning can process applications in milliseconds.
  • Customer-Centric: Show customers that their time is valued by going the extra mile to simplify the process.

Competitive Pricing:

  • Industry disruptors offer personalized pricing based on advanced risk models.
  • To compete, dealerships need technology that provides quick decisioning and accurate, risk-based pricing.

The Future of Auto Loan Origination:

The story is far from over, and the throne is up for grabs. The winner will be decided by who provides the superior experience—dealers or disruptors. The battle for buyers’ attention is likely to continue, with customers ultimately determining who shares the throne in the future.

Discover how to drive a better consumer experience in auto financing.

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QUESTIONS

Frequenly Asked Questions

Get in Touch

  • How has fintech transformed auto loan origination? 

    Fintech innovations have streamlined the loan origination process, making it faster, more efficient, and data-driven.

  • What role does data play in auto loan origination decision-making? 

    Data is crucial for assessing creditworthiness, detecting fraud, and personalizing loan terms for borrowers.

  • Are traditional dealerships still dominant in auto financing? 

    Traditional dealerships face growing competition from online lenders and fintech disruptors in the auto financing industry.

  • How can dealerships adapt to the changing landscape of auto loan origination? 

    Dealerships can thrive by offering seamless, technology-driven experiences and competitive pricing to meet customer expectations.


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15 Companies Setting the Trends in Buy Now, Pay Later

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15 Companies Setting the Trends
in Buy Now, Pay Later

Within the Buy Now, Pay Later (BNPL) industry, a lot has changed since the point-of-sale loans rose to the spotlight in 2020: providers are maturing and making a pivot into profitability.  BNPL is growing across the world, expected to account for roughly 25% of all e-commerce transactions by 2026. By 2027, the market size is expected to explode to $744 billion, growing at a CAGR of 25%. BNPL is here to stay. But what that looks like is still being decided. 

Consumers and businesses alike are increasingly turning to BNPL to make purchases more manageable, from everyday needs to critical business resources. New BNPL verticals are popping up globally, covering everything from B2B credit to healthcare to groceries. 

Discover the newest trends in this rapidly expanding industry and the companies working to put them on the map.

The Trend:
BNPL stomps its way into the $125 trillion global B2B market.

  • Hokodo – Buy now, pay later is becoming increasingly popular among retail merchants, so offering payment options for B2B purchases is a unique twist. Today, B2B merchants are essentially forced into offering payment terms to their customers with outdated methods of credit management – including paper-based applications, manual credit checks and painful invoicing programs. Enter in Europe-based Hokodo, which aims to make selling to business buyers easier. Business buyers shop on selected merchant’s sites, with real-time offers of payment terms, “powered by Hokodo’s trade credit APIs.” They claim that the wrong payment options are one of the biggest reasons that B2B buyers drop out of a sales funnel – will BNPL help increase that conversion rate? Hokodo thinks so. Recently, Hokodo partnered with French marketplace-focused fintech Lemonway to power Europe’s B2B marketplaces by offering online credit. This comes as a much-needed alternative for cash-strapped businesses struggling through a worldwide capital crunch.

Also, read: What is Banking as a Service?

The Trend:
BNPL helps provide health and financial care.

  • PrimaHealth Credit – In countries without government-funded healthcare, both necessary and elective health treatments are out of reach for many. A report from Financial Technology Partners notes that only 23% of Americans can afford a medical bill of over $2000. Subprime credit scores, or individuals without any credit history at all, means significant market opportunities for BNPL services in healthcare. PrimaHealth Credit’s mission is “helping more patients say yes to treatment,” with simple, transparent payment options offered by healthcare providers at point of care. Giving people more affordable options to access the healthcare they need can always be considered a win.
  • Sunbit – BNPL isn’t just for wish-list clothes and vacations. Sunbit aims to help consumers pay for everyday items that some of us take for granted, including automotive, optical, and dental services. The organization’s model is to offer back-end services to the businesses where these essential transactions take place – like your local dentist or optician’s office or the dealership that already has your car up on a hoist. “Sunbit’s flagship product allows businesses to guide customers through the financing process, which is integrated with their own point-of-sale systems” for a more seamless customer experience. Providing payment options for services that are prone to becoming unexpected expenses is also a very forward-looking proposition: millennials are by far the age cohort that is most likely to have to use a payment plan for unexpected medical and self-care bills.

The Trend:
Forget luxury items. BNPL finds a home in Home and Lifestyle financing.

  • Deferit – As with healthcare and other medical services, there are certain essential items that we all need to pay for. Deferit, an Australian-based organization, lets customers split utility, telco, car registration or childcare bills into installments. With a vow to empower customers, including options to change payment terms, Deferit has created an easy budgeting tool for payments, eliminating interest and annual fees.
  • Flex – While we’re talking essential services, housing comes to mind. Many people face hard choices on where their money goes each month – rent or food or other essentials – especially amidst today’s economic uncertainty. There are estimates that $5 billion in late fees goes to landlords every year. Flex understands these challenges (and the stress they cause!) and aims to get you out of paying late fees by covering your rent for you and offering flexible options to pay them back, without any hidden fees or interest.

The Trend:
BNPL to face the rising need for online grocery shopping as consumers struggle with rising cost-of-living.

  • Flava – Billed as the UKs first Buy Now, Pay Later supermarket, Flava offers zero interest and an initial ‘basket’ credit of £100, which can increase to £320 per order once re-payment history is established. Offering a full range of brand-name grocery products, delivery to your door, and flexible repayment plans, Flava aims to help customers with food insecurity stock their cupboards amid economic uncertainty.

The Trend:
BNPL puts retail shopping on steroids, online and in-store.

  • Zip – One of the leaders of BNPL, Zip (formerly known as QuadPay) offers payment options for retail giants, including Apple, Amazon, Walmart and Target, as well as exclusive retail partnerships. With categories covering everything from education and pets to shoes and travel, Zip is available on a variety of platforms as well as in physical retail locations, providing you with interest-free options virtually anywhere you want to shop.
  • Simpl – Indian startup Simpl has a straightforward mission – make it easy for people to purchase what they like, when they like, with installment payment terms. In a country with complicated financial systems that often make it difficult for people to obtain credit, Simpl allows its users to buy now and pay at a more convenient time. With a full-stack, mobile-first platform for credit-based payments, Simpl enables one-click purchases and promises full transparency to its users and merchants alike.
  • Paidy – In Japan, many consumers prefer not to use credit cards for online payments, leaving massive opportunities for alternative options like BNPL. Japanese fintech Paidy allows consumers to shop at a variety of online retailers with a convenient mobile app that only requires your email address and phone number – repayments in installments can happen via bank transfer, direct debit and even in convenience stores, all by just showing the app.

The Trend:
BNPL offers more customized payment plans and features closer to legacy finance, as BNPL prepares to meet its match in legacy banking in 2023.

  • Sezzle – Sezzle offers typical installment payment plans, but also features some products exclusive to their users that they call strategic differentiators. Sezzle Up for example, lets a shopper build their credit rating by enabling the company to report payment history to credit bureaus. They’ve also partnered with Ally Bank to offer longer-term financing options, proving again that flexibility in payment options may be a key driving factor in growth.
  • Splitit – Headquartered in New York, Splitit is unique in the BNPL space in that it actually allows consumers to leverage their existing credit. By using their own credit or debit cards with its installment program, customers will see installment charges on their bills, effectively evening out cashflows. The ability to break down payments into smaller pieces without additional interest, applications or fees and build credit at the same time makes Splitit an attractive option for consumers, while being a safe option for merchants. In 2023, Splitit expanded its reach into the Asian market by partnering with Alipay to offer the eCommerce’s clients an installments option.
  • Twisto – Featuring a different ‘twist’ on BNPL, European company Twisto offers a monthly credit limit for your payments once you register with them. Shop online or in stores up to this set amount each month and then receive your invoice. Once invoiced, you can settle the full amount with Twisto or pay 10% and defer the rest to a later date. Twisto also offers return options and varying monthly plans, with features like personal finance management and family travel insurance.
  • Tymit – Different than the typical pay-in-four installment plans many BNPL providers offer, Tymit’s credit card allows you to select varying installment plans as you make your purchase – including repaying over 3 months with no interest, or even longer (up to 36 months) with transparent pricing quoted upfront. Tymit also offers Tymit Booster, a top-up credit card that allows you to build your credit score and still offers 0% interest on all purchases.

The Trend:
Resurrecting the travel industry and introducing Gen Z to air travel

  • Fly Now Pay Later – The UK’s Fly Now Pay Later has expanded into the travel-starved US market, while  increasing operations in the UK and Germany. With a mission to make travel affordable and flexible, the company is capitalizing on post-pandemic recovery by offering travel payment plans that work for everyone – destinations and customers. With an easy-to-use booking app, Fly Now Pay Later pays for your holiday with your selected travel provider, leaving you to pay them back with flexible payment options over time.
  • Uplift – Headquartered in California, Uplift’s mission is to help people purchase what matters most – in their case, travel. With international partners ranging from cruise lines and resorts to airlines and vacation package dealers Uplift hopes their buy now, pay later plans will “be the economic kickstarter needed to ignite the travel industry.” Uplift works directly with merchants to reinforce brand loyalty, offering customers a simpler way to pay for travel by selecting Uplift options at checkout, without driving consumers to their own proprietary marketplace. BNPL moves into the travel industry have their aim set on future travelers, as two-thirds of Generation Z and millennial would be more likely to take vacations if offered installment options.

These trends are only the beginning of a new, sustainable Buy Now, Pay Later. With a strong credit risk decisioning foundation, you can follow any trend without having to compromise your risk appetite. If you’re ready to rethink your BNPL technology, fortify your strategy, and pivot to profitability, explore the ebook, The Pivot to Profitability: Evolving with Buy Now, Pay Later.

Sustainable BNPL is here – is your strategy future-proof?

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The Essential Guide to Credit Underwriting

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The Essential Guide
to Credit Underwriting

What is Credit Underwriting?

Credit underwriting is when financial institutions (like banks, fintechs, credit unions or credit card companies) evaluate how creditworthy an individual or business is for the purpose of determining if they should be able to access credit. Typically, the credit underwriting process is kicked off when an individual consumer or a business applies for a form of credit, which could be anything from a credit card or business loan, to a mortgage or auto lease. The main objective of credit underwriting is determining how risky it is to lend to the applicant – in other words, how likely they are to pay back the loan or otherwise meet their credit obligations. A number of factors are usually considered when determining creditworthiness, including credit score, income, and debt ratio as examples. Credit underwriting evaluates the creditworthiness, but also helps determine the specific terms and conditions of the loan, including interest rates and credit limits.

What exactly is a Credit Underwriting Engine?

Sometimes referred to as a decision engine, or automated credit risk decisioning, a credit underwriting engine is a software application that automates the entire credit risk assessment process. It takes data from a variety of sources, including credit bureaus, bank statements, and alternative sources like social media profiles and utility payment info, and uses algorithms or risk models to analyze the data and generate a credit score or risk rating. This credit score or risk rating/profile is a way of determining an applicant’s creditworthiness. Based on the appliant’s overall risk profile and the parameters set out by the lender, it is then determined whether to approve or reject a particular credit application, and if approved, to set the specific terms of the loan.

In a nutshell, credit underwriting engines are computer programs that use data and risk models/algorithms to quickly assess the creditworthiness of loan applicants. They are becoming increasingly popular in the financial industry, especially among lenders who need (or want!) to process large volumes of credit applications quickly and accurately. In this guide, we will explain the key features and benefits of credit underwriting engines and offer some tips on how to choose the right one for your business.

Key Features of Credit Risk Underwriting

Some of the key features of automated credit risk underwriting processes include:

  • Data Integration: The ability to pull data from a variety of sources, including credit bureaus, bank statements, and social media presence – which is key to more holistically assessing an applicant’s risk level.
  • Data Analysis: The ability to analyze data using advanced algorithms and machine learning techniques to identify patterns and trends.
  • Risk Assessment: The ability to generate a credit score or risk rating that reflects the applicant’s creditworthiness as determined by the particular parameters set out by the lender.
  • Customization: The ability to customize the underwriting engine to meet the specific needs of the lender (which may include different criteria for a variety of product offerings, regions, etc.).
  • Real-Time Decision Making: The ability to make real-time, accurate loan decisions based on the credit score or risk rating.

Benefits of Credit Risk Underwriting Engines

Credit underwriting engines offer several benefits to lenders, including:

  • Increased Speed and Efficiency: Credit underwriting engines can process loan applications much faster than traditional underwriting methods, allowing lenders to say yes to more customers and grow their revenue.
  • Improved Accuracy: Automated credit risk underwriting processes use advanced algorithms and machine learning techniques to analyze data, which reduces the risk of human error and improves the accuracy of loan decisions.
  • Better Risk Management: Credit risk underwriting provides lenders with a more accurate assessment of the applicant’s creditworthiness, which helps them make better lending decisions and reduces the risk of defaults.
  • Increased Customer Satisfaction: Automated credit underwriting provides faster loan decisions and a more streamlined application process, improving customer satisfaction and retention.

Choosing the Right Credit Underwriting Engine

hen choosing a credit underwriting engine, it is important to consider the following factors:

  • Data Sources: Ensure you can easily integrate the data sources you need to make accurate lending decisions. Look for underwriting engines that can integrate a variety of types of data sources via a single API for maximum efficiency.
  • Customization: Look for an underwriting engine that can be customized to meet the specific needs of your business, whether it’s customer thresholds, regional differences, or your particular variety of product offerings.
  • User Interface: Choose an underwriting engine with a user-friendly interface that is easy to navigate and use, which will limit the amount of reliance on vendors or your IT team when you want to make changes to your decisioning workflows.
  • Cost: Consider the cost of the underwriting engine and make sure it fits within your budget, but be sure to factor in the increased revenue from faster, more accurate risk assessments when looking at expected ROI versus initial investment.
  • Technical Support: Can the underwriting engine provider offer technical support and training to ensure your team can use the software effectively?

A credit underwriting engine is a powerful tool for lenders looking to streamline the loan application process, whether for consumer lending or commercial credit underwriting and ensures more accurate lending decisions. They offer a range of benefits, including increased speed and efficiency, improved accuracy, better risk management, and increased customer satisfaction. If choosing the right partner seems daunting, consider the factors we’ve outlined when looking at providers. Above all else, look for a provider that can offer you seamless data integration and an easy-to-use interface so you can make changes quickly and easily as market needs and consumer demands evolve. Because if you aren’t meeting the needs of your loan applicants quickly, your competitors will.

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The Reinvention of Banking

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The Reinvention of Banking

Why banks need to ensure resiliency and innovation to achieve long-term profitability

As economic stability increasingly looks like a thing of the past, what does this mean for traditional banks? With disruption after disruption in the financial services sector, it’s clear that resiliency is a must. According to McKinsey, “banks will need to become more resilient and reinvent their business models to ride out the current volatile period and achieve long-term growth and profitability.” But what does reinvention really mean? And is it possible to reinvent your business models quickly? We’re looking at some of the key challenges the banking industry is facing, and the ways that upgrading credit risk decisioning capabilities can help solve for some of these challenges.

Banking Disruptors:

Banks and the financial industry as a whole face many challenges, not the least of which includes fintechs and challenger banks. But the need to keep up with the competition is not the only obstacle banks are facing.

Evolving Regulations: Complying with various regulatory requirements is always a challenge, but it’s even more difficult when those regulations are constantly evolving. Look at the world of Buy Now, Pay Later as an example – as this non-traditional financial services offering continues to grow and shift worldwide, more and more traditional banks are sitting up and taking notice. But getting into the market can be fraught with compliance issues, which can be costly and time-consuming, and as a result, impedes your ability to innovate and respond quickly to changing customer needs.

Increasing Digitization: If the last few years have taught us anything, it’s that more things than ever thought possible can be done digitally. Customers increasingly want digital channels to meet ALL of their needs, including financial services of all kinds – whether that’s applying for credit or embedded finance enabling banking super-apps. But this requires clear investment in technology from banks to remain competitive.

Growing Competition: Speaking of remaining competitive – more than ever, new players are continually entering the market, vying for a share of the wallets of increasingly discerning consumers. Whether it’s established players with new offerings or innovative fintech startups, the landscape is changing, putting pressure on banks to reduce costs and improve offerings, while still providing frictionless experiences for consumers.

Also, read: What is Banking as a Service?

Turning Disruption into Opportunity:

But it’s not all dire. Banks can be uniquely positioned to effectively deal with these disruptors. As Siobhan Byron writes, “established banks, though still only recently starting to harness the power of digital, have a key advantage over new entrants. Their decades of institutional knowledge is difficult to build up quickly.” Banks are also in a better position to deal with market shifts than they were a decade ago – if they can leverage data analytics and automated workflows to make “better and more informed credit decisions.”

So, if you’re a bank, what can you do? Look for ways to leverage advanced technology like artificial intelligence and machine learning, automated credit risk decisioning, and data integration to improve efficiency, reduce costs, and renew your focus on customer-centric products and services.

Increase Efficiency: Machine learning algorithms can enhance your credit risk models, processing vast amounts of data quickly and reducing the time and person-power needed for risk assessments and credit decisioning.

Reduce Costs: Automating your credit risk decisioning process reduces the manual labor required, allowing you to allocate resources to other strategic initiatives that can help grow your revenue and improve the customer experience.

Enhance the Customer Experience: Focus on frictionless onboarding and customer management, with faster credit decisions, digitized processes, and more personalized product offerings (including everything from interest rates to loan terms, upsell/cross-sell offers, and even optimized collections strategies).

Improve Risk Management: Advanced analytics can enable you to identify key patterns and trends in customer behavior, ensuring more accurate risk assessments and reduced losses due to defaults and improved fraud detection.

Enable Agility: With more flexible, user-friendly decisioning technology, you can make changes to decisioning workflows quickly, respond to market shifts, meet changing consumer demands, and launch new products faster to stay ahead of your competition.

Foster Innovation: Enabling all the above points (with more automated decisioning, advanced analytics, superior data integration, improved efficiency, etc.) means you can foster a true culture of innovation. Allow your teams to focus on strategic initiatives, competitive insights, and innovative product development for customer-centric offerings that can help put you ahead of the competition.

Roadmap for Success:

The larger the bank and the more complex the systems, the more daunting it can feel to implement any changes to your decisioning software or data sources. But fear not, follow some simple steps to incorporate tech upgrades into your credit risk decisioning – and remember, it’s not all or nothing: look at decisioning solutions that can easily work alongside your existing systems and/or partners that have experience replacing legacy systems to ensure a smooth transition.

  1. Assess Current Capabilities: Evaluate your existing credit risk decisioning capabilities and identify areas where you can improve your processes.
  2. Define Your Objectives: What are your goals for upgrading your tech? Prioritize the areas that are most important for you (i.e., reducing costs with improved efficiencies, versus enhancing the customer experience with increased digitization capabilities).
  3. Select Technology Capabilities: Choose what is most critical to upgrade – is it automated risk decisioning, machine learning, data integration?
  4. Choose Your Solution: Outline a plan for integrating the chosen technology into your existing systems and workflows, with a partner that can help with timelines, resource allocations, and important milestones.
  5. Test and Iterate: Be sure your chosen risk decisioning solution offers you the ability to test workflows, refine your credit models, easily integrate new data sources, and iterate your processes – on your timeline, not theirs!

With the right technology in place, not only can you accomplish all the goals set out above, but you can more easily maximize the value of your customers across the entire lifecycle. Because with upgraded credit risk decisioning, you can more efficiently move beyond credit origination and onboarding and bring that customer-centric experience to all the financial services products you offer. As McKinsey points out, “banks that have already embedded high-performance credit-decisioning models into their digital lending have reaped three key benefits,” including increased revenue, reduction in credit losses and gains in efficiency. So, what are you waiting for?

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Top Three Mortgage Lending Trends: How to Make Smarter Credit Decisions Today to Thrive Tomorrow

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Top Three Mortgage Lending Trends:
How to Make Smarter Credit Decisions Today to Thrive Tomorrow

From HELOC to HELOAN, the global mortgage lending market is vast – it reached almost $11.5 billion in 2021 and – despite economic slowdowns – is estimated to grow at a CAGR of 9.5% through 2031, reaching a mammoth size of $27.5 billion. 

However, the last few years have brought the mortgage industry face-to-face with an unprecedented challenge – to digitize core functions almost overnight to tackle record levels of origination and forbearance activities. Many lenders had to expedite tech projects to provide the necessary infrastructure needed to support these new practices and accelerated digital solutions to create better customer experiences and reduce operational costs.

While the industry has found success in adopting new digital solutions, the UK still faces a housing affordability crisis, leaving consumers even more reliant on credit for mortgage originations, refinancing, and regular payments. Though there are attempts to combat the lack of affordable mortgages, like this initiative from Skipton Building Society, rates continue to rise.

Amidst these economic challenges, however, innovation and technological advancements in the industry provide opportunities for companies to adapt and succeed in this challenging environment. From better customer experiences to more accurate credit risk decisions and more financial inclusion, the industry is evolving. 

Discover the top three mortgage lending trends that can help you make smarter credit decisions today to thrive tomorrow.

Trend 1: Increased Use of Automation

Mortgage lending can be tedious for both lenders and applicants at the best of times, due to lengthy, complex processes with multiple stages. While mortgage transactions can take between six to eight weeks to close on average, consumers believe they should take no more than three. That’s why automation is a trend with wind in its sails: decisioning automation can help lenders meet borrower expectations. 

Why it’s popular

Instead of having to wait months for a mortgage, decisioning automation allows lenders to approve customers in a fraction of the time. Even the most complex processes are streamlined, saving time (and brain power) across the board. Customers benefit from approval periods that align with their expectations, while lenders expedite their workload to produce more accurate decisions, faster – freeing up resources to attract and retain customers while boosting sales volume. 

How to use it

While automation may seem intimidating to actually use, finding the right decisioning automation tech is often the biggest hurdle. Take control with flexible technology that offers drag-and-drop UI, letting you configure and reconfigure automations to reflect your changing needs, eliminating reliance on vendors and dev teams. With optimized data and integrated workflows that can layer on top of existing tech and talk to a variety of systems, automated decisioning can be as simple as clicking a few buttons.

Trend 2: Data-Driven Risk Decisioning

Credit risk decisioning is an essential element of mortgage lending, ensuring that lenders are mitigating fraud and default risk and borrowers are getting the right loan terms. For long term loans like mortgages, accuracy is essential to mitigate risk and provide competitive offers to consumers. And an increasing number of mortgage lenders are using data-driven risk decisioning to do both.

Why it’s popular

Mortgage lenders no longer have to accept uncertainty – whether it be in economic conditions or customer behavior. Accessing real-time data ensures more accurate creditworthiness assessment and lower risk for the lender. It can also help businesses grow by providing the insights needed to hyperpersonalize offers for both new and existing customers, improving competitive advantage. On-demand data can also help flag if risk profiles change, allowing lenders to step in long before missed payments or home repossession.

How to use it

The ideal way to harness data-driven risk decisioning for your mortgage lending business is to invest in a data and decisioning ecosystem in which the decisioning engine pulls real-time data on demand from a variety of data sources through a single API. The streamlined, integrated tech stack helps you better understand consumer needs across the entire customer lifecycle. Add in machine learning for evolving customer insights that will eliminate the guessing game and let you make smarter credit risk decisions.

Trend 3: Alternative Credit Scoring Models

Financial inclusion has been gaining traction in the fintech world for years, but recent global economic and political overhauls permanently changed the way we think about access to financial services. Alternative data is a central feature enabling financial inclusion initiatives for lenders across the world. No wonder 65% of credit risk/lending decision makers use alternative credit data on at least half of their credit applications. And that number is only growing, helping lenders accelerate financial inclusion by enabling the creation of alternative credit scoring models, eliminating reliance on traditional credit bureau data alone.

Why it’s popular

Traditional credit scores don’t tell the whole story, especially when it comes to thin or no-file consumers – and 71% of credit providers agree. Alternative data lets lenders access a variety of data that doesn’t come from credit bureaus, including utility payment history, employment data, geographical data, and rent payment history – data that would be especially relevant to establish creditworthiness for a new homebuyer. Mortgage lenders who use alternative data to build alternative credit scoring models can expand their customer bases without increasing risk and support financial inclusion at the same time.

How to use it

In order to build alternative credit scoring models, you need decisioning tech integrated with alternative data. The most powerful data and decisioning platforms simplify the data supply chain, pulling in the relevant data exactly when you need it to ensure more accurate decisions for every application. And don’t compromise on risk – create processes that pull in more alternative data for thin file applicants and less or none for traditionally creditworthy applicants. 

These Trends are Here to Stay

Mortgage lending is often a long, complex process that puts a strain on both lenders and borrowers. The trends we explored today help alleviate that strain, and that’s why they’re here to stay. 

From automation that improves processing speed and customer experience to data-driven risk decisioning that improves risk assessment accuracy and competitive edge through personalized offers to alternative scoring models that help lenders grow their business and accelerate financial inclusion of the under or unbanked, these trends represent the future of the industry.

Want to take these trends and run with them? Make sure your mortgage lending business is ready with our eBook, The Secret to Consumer Lending Success. Download it today!

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The Lending Revolution: Building World-Class Digital Lending Experiences in Southeast Asia

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The Lending Revolution:
Building World-Class Digital Lending Experiences in Southeast Asia

Digital lending has the potential to revolutionize financial inclusion in Asia’s emerging economies. For individuals and small businesses in the region, accessing credit has traditionally been a daunting, time-consuming process, often resulting in high rejection rates and limited options. 

However, with the arrival of digital lending, the process has become faster, more efficient, and more accessible, offering a world of opportunities for those previously excluded from formal financial systems. Digital lending offers faster decision-making, better risk assessment, and more customized product features. By accessing real-time data, lenders can make faster credit decisions, which leads to faster disbursements and better customer experiences. 

Aditya Chintawar is the Chief Product Officer at KoinWorks, an SME-focused neobank that helps customers build credit scores to solve the problem of accessing credit in Indonesia. With a population of over 270 million people that are largely unbanked or underbanked, a report by McKinsey & Company estimates that the economic impact of digitization would be a $150 billion or 10% of GDP growth. By leveraging digital platforms and technologies, lenders can reach a wider customer base, which can help drive economic growth and development. Aditya recently spoke to Provenir’s General Manager for APAC, Bharath Vellore about their experience building world-class digital lending experiences tailored to this market. Check out some of the key takeaways from the discussion. 

Digitization vs. Automation: Understand the Difference and the Path to Follow

Digitization and automation are not the same! Step one to digital lending is effective digitization: the process of transforming analog or manual processes in lending into digital ones. This involves the use of digital technologies such as Optical Character Recognition (OCR), data analytics, machine learning algorithms, and digital platforms to improve operational efficiency, enhance customer experiences, and expand reach to underserved segments of the population. By taking a written statement on a new lender, digitizing it and inserting it into your data lake, you enrich the quality of your models and open the doors for new customers with no previous credit histories. Digitization allows lenders to access data in real time to make faster credit decisions, and provide more customized and personalized products to their customers. Digitization is a key factor in transforming the lending industry and enabling lenders to compete in today’s rapidly evolving market and provide more customized products to their customers.

Once a process has been digitized effectively, it can then be automated. Manual to digital to automation is the path to follow, and it is essential to understand what is being digitized to ensure it is effective. Digitalization unlocks additional data points, making it easier to build better products, perform better risk assessments, and provide better customer experiences. Understanding lending behavior through key data points is critical, and the development of any digital lending product should take this into account. In terms of client experience, the customer response to digitalization has been great, and certain forms of face-to-face interaction can still be maintained, such as voice KYC or video calls.

Balancing Inward and Outward Focus

To digitize effectively and launch new digital products, lenders must balance inward and outward focus. Inward focus requires proper digitalization – adapting operational processes such as underwriting so they can be done by computer systems – in order to reduce friction, make credit underwriting faster, and provide insights into risk assessments. However, properly executed digitization must also happen on the operational level for the availability of services to be possible. A step-by-step approach ensures that each aspect of the process is able to handle the previous load, ultimately ensuring that the availability of service is on-demand, 24×7. Many digital lending products are launched with an outward focus on great front-ends designed for great user experiences. Koinworks operates in a setting where the average smartphone has 4GB of RAM and 64GB of storage. To be relevant to users, the app needs to have a small footprint and be easy to use. The app also offers a dedicated support team to help users with their loan applications and other needs. But if the back-end cannot function up to speed, it will lead to client frustration. Providing ongoing analysis of user behavior can help identify cross-selling opportunities and increase loan limits for existing customers. So, when it comes to inward or outward development focus, it’s an issue of building an agile, end-to-end infrastructure, to strike a balance between the two and launch as quickly as possible. 

The Challenges of Retention in Digital Lending

Retention in digital lending is challenging. Strategies for reducing rejection and anxiety include defining trust and critical parameters with the business to avoid fraud and risk, and maintaining effective communication with the client. Lending is a complicated business, and testing underwriting systems takes time, so running multiple programs on smaller budgets to identify which product works is essential for each type of customer is essential. Additionally, the focus should be on creating a seamless customer experience, reducing friction, and taking into account customers’ digital footprint.

The lack of trust in emerging economies where financial inclusion plays a huge role, has a significant impact on decision-making and strategy. Building trust and infrastructure is essential for the success of digital lending in these markets. Scalability and agility are also important, as they allow lenders to adjust their offerings to meet changing customer needs. Fintechs should focus on agility when building product features to respond to changing market needs quickly. Finally, being open to new ideas and defining trust and infrastructure will help fintechs succeed in a rapidly evolving environment. That’s why digital lending becomes, not just a nice-to-have, but a must-have in order to compete on quality and time-to-market.

“The goal is to create a virtuous cycle. Better data leads to better risk assessment, which leads to better products and experiences. All of which, in turn, lead to better data.”

– Aditya Chintawar, Chief Product Officer at KoinWorks

Digital lending is transforming the lending industry in Southeast Asia and around the world. By leveraging digital technologies and data, lenders can improve their operational efficiency, enhance customer experiences, and expand their reach to underserved segments of the population. However, to succeed in these markets, lenders must balance inward and outward focus, understand the difference between digitalization and automation, address challenges related to retention, and build trust and infrastructure.

Watch the full fireside chat with Bharath and Aditya to learn more.

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Shaking Up Consumer Lending in the UK

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10 Fintechs Shaking Up
Consumer Lending in the UK

Looking at the UK landscape and 10 innovative global fintechs

With the ever-evolving landscape of financial technology, consumer lending has never been more accessible and efficient – in large part, due to fintech innovation. With a global consumer credit market size of $110 billion (in the UK, consumer lending reached reached over 28 billion British pounds in January 2023, which is a dramatic recovery from early in 2020), rapidly growing middle classes in emerging markets, and economic uncertainty affecting us all, the opportunity for lenders to tap into the consumer need for credit is immense.  

As predicted, the UK economy in particular is adapting as many experts feel a major recession has been avoided, and as a result, banks are expected to increase their lending this year. “Total loans in the UK are expected to rise 1.2% this year… with falling inflation, lower-than-anticipated energy bills and a resilient job market” contributing to an increase in the UK GDP, “driving an increase in consumer and business borrowing.”

When it comes to consumer lending specifically, fintechs are answering the call for increased borrowing demands and are looking to disrupt the traditional. No credit score? No problem. Worried about missing payments? You’re covered. From a company supporting gig workers around the world to a credit card for foodies, these ten global fintechs are shaking up auto lending, BNPL, credit cards, mortgages, and retail/POS. 

Auto Lending

Lendbuzz – USA

If you’re new to credit, it can be difficult to get approved for auto financing. Lendbuzz is here to change that. The fintech proves a simple and fast application process that assesses creditworthiness with data beyond just your credit score. Working directly with auto dealerships, Lendbuzz offers personalized loans and instant decisions, taking you through the process from start to finish.

Moove – EMEA and India

Founded in Nigeria in 2020, Moove is a global startup that aims to democratize access to vehicle ownership for “mobility entrepreneurs” across Africa, the Middle East, Europe, and India. Tackling the high barrier to vehicle financing that millions face, especially in emerging markets, Moove uses a revenue-based financing model to offer car loans that drivers then pay off through their ridesharing app. 

Buy Now, Pay Later

ShopBack (formerly Hoolah) – Southeast Asia and Australia

Singapore-born ShopBack is a fintech that provides improved shopping experiences to consumers and broader reach and shopper engagement to brands and retailers. Operating across APAC, their integrated BNPL service allows you to pay off purchases in installments of three, which can be combined with features such as cashback and prepaid retail vouchers. ShopBack hopes to make shopping “more rewarding, delightful, and accessible.”

Nelo – Mexico

If you want to buy now, pay later at Mexico’s top merchants, you want to download Nelo’s top-rated app – it’s the first of its kind in the region, enabling shoppers to pay in installments with a virtual card generated at checkout. And through the company’s partnership with Mastercard, you can use it at any online merchant. You can also use it to finance everyday expenses like utilities and other bills, a mark of BNPL innovation and a sign of how the segment is likely to evolve.

Credit Card

Cred.ai, USA

Cred.ai is an AI-powered credit card designed to help users build credit while mitigating missed payments. The fintech sets up automated spending limits, helping you spend within your means, and their proprietary underwriting model means you don’t need a FICO score to apply. The card itself is metal, unicorn-themed, and free for approved applicants. It works best with their digital banking product and comes with features like an early paycheck (called flux capacitor) and digital “self-destruct” cards called stealthcards. 

Yonder, London

A rewards credit card “great for expats and immigrants,” Yonder is a rewards credit card that boasts no foreign exchange fees, worldwide travel insurance, and you can apply without a UK credit score. Leveraging open banking technology, the credit card is able to focus on financial inclusion while rewarding users for the experiences that enrich their lives, whether it’s travel or dining at Yonder’s curated restaurant partners around London.

Mortgage

Hypofriend, Germany

Hypofriend was founded to simplify and personalize the process of getting a mortgage for Germans. They use advanced technology to analyze your optimal finance strategy while predicting bank decisions in order to connect you to a personalized mortgage offer from a lender that fits your needs. The Hypofriend team is also there to advise from start to finish, demystifying the complex process and providing transparency to support more financial literacy and understanding.

HomeCrowd, Malaysia

Focused on helping Millennials in Malaysia achieve the dream of owning a home, HomeCrowd uses holistic, data-driven credit scoring to match mortgage applicants with peer-to-peer (P2P) lenders on a blockchain-powered, Web3 platform. The company is the first in the country to be licensed and regulated for P2P lending specifically for mortgages and consumer financing by the government. 

Retail/Point-of-Sale (POS)

Blnk, Egypt

Did you know that less than 4% of Egyptians have access to credit cards? The majority of Egyptians must rely on savings or finance purchases with high-interest loans. Blnk is here to change that – they enable any consumer to receive instant credit at the point-of-sale. Their current network of merchants includes over 300 businesses and the fintech has already disbursed over $20 million in loans. 

Acima, USA

US-based Acima offers consumers lease-to-own solutions as an alternative to traditional retail financing. You don’t need credit to apply and your credit score isn’t affected. Simply lease the furniture, electronics, or any other item you want to purchase and “rent” it until the cost of the item is covered, or pay early at a discounted rate. If you no longer want the item, just return it! Acima enables online and in-store shopping and offers flexible payment terms.   

Unlocking Consumer Lending Innovation

As access to consumer credit increases around the world, both fintechs and traditional financial service providers will need to leverage the right technology to provide it. The ten fintechs you just read about have found their innovative idea to disrupt consumer lending – what will yours be?

No matter the idea or use case, you need a technology partner that thinks like you. Future-proof your consumer lending strategy and launch new products with a data and decisioning ecosystem that manages risk, so you can focus on what matters most: serving your customers in new, disruptive ways. 

Read the eBook, The Secret to Consumer Lending Success, to discover how you can overcome any lending challenge with a robust credit risk decisioning platform that grants access to both alternative and traditional data sources through a single API.

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5 Ways Credit Risk Analytics Can Help Your Business Make Better Decisions

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5 Ways Credit Risk Analytics
Can Help Your Business Make Better Decisions

In today’s rapidly changing business environment, companies need to make informed decisions to stay competitive. One way to achieve this is by leveraging credit risk analytics. By analyzing data related to credit risk, businesses can gain valuable insights into their customers’ financial behavior and make better decisions based on that data. In this blog post, we’ll explore five ways credit risk analytics can help your business make better decisions.

Better Understand Your Customers

  • Credit risk analytics can help you better understand your customers’ creditworthiness, payment history, and overall financial behavior.
  • This information can help you make more informed decisions when it comes to extending credit or setting credit limits.
  • Use credit risk analytics to segment your customers based on their credit risk profile, allowing you to tailor your offerings and pricing to meet their specific needs.

Mitigate Risk

  • Credit risk analytics can help you identify potential risks before they become major issues.
  • By analyzing data related to credit risk, you can identify customers who are more likely to default on payments or who have a history of late payments, helping you mitigate risk and avoid potential losses.
  • Use credit risk analytics to monitor your customer portfolios and identify trends or patterns that could indicate future risks across the entire customer lifecycle.

Optimize Pricing

  • By analyzing credit risk data, you can optimize your pricing strategies.
  • Identify customers who are more likely to default on payments and adjust your pricing accordingly to mitigate the risk.
  • Use credit risk analytics to determine the optimal pricing and loan terms for each customer segment, based on their unique credit risk profile.

Improve Collections

  • Credit risk analytics can help you improve your collections process – reducing collection costs and improving your cash flow.
  • By analyzing data related to credit risk, you can identify customers who are at risk of defaulting on payments and take proactive measures to collect payments before they become overdue.

Enhance Customer Experience

  • Credit risk analytics can help you enhance the overall customer experience.
  • With a better understanding of your customers’ financial behavior, you can tailor your products and services to meet their specific needs and preferences.
  • Use credit risk analytics to identify customers who are most likely to be interested in a particular product or service, and target your marketing efforts accordingly.
  • You can also personalize your customer interactions and offer customized solutions based on each customer’s unique credit risk profile.

By leveraging credit risk analytics, you can gain valuable insights into your customers’ financial behavior and make more informed decisions. Whether it’s optimizing pricing, mitigating risk, or improving collections, credit risk analytics can help you achieve your growth goals and stay competitive in today’s dynamic business environment. With the right credit risk analytics tools and strategies in place, your business can stay ahead of the curve and make the best decisions possible.

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Unlocking the Power of Credit Cards: Three Innovative Trends Driving Change in the Industry

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Unlocking the Power of Credit Cards:
Three Innovative Trends Driving Change in the Industry

The credit card industry has come a long way since the first credit card was introduced in the 1950s. Today, bankcard balances have reached a new record of $930 bn in the US alone, and the industry as a whole is growing rapidly across the globe. With rapid growth comes stiff competition, so issuers are constantly looking for ways to attract new customers and retain existing ones.

With economic uncertainty shaping financial services worldwide, flexibility and creative thinking have become necessary for issuers and other lenders trying to reduce risk and default as much as possible. Traditional approaches include adjusting lending criteria, reducing credit limits, and increasing interest rates to protect against potential losses. However, forward-thinking lenders have chosen to embrace macro trends like digitization to provide better customer service and financial inclusion to expand the addressable market. 

More specifically, trends like alternative credit cards, offering BNPL functionality, and hyper-personalization are not only strengthening lenders’ risk positions and growing their business, but are changing the way we use and think about what a credit card can be. 

Explore the three innovative trends driving change in the credit card industry:

Trend 1: “Alternative” Credit Cards

Alternative credit cards are credit cards designed for new-to-credit (NTC) consumers with thin credit files or no credit history, including college students, immigrants, and low-income earners to help build credit and improve creditworthiness. Unlike traditional credit cards, these do not require hard credit pulls and often come hand-in-hand with features like financial literacy education, auto-payments and rewards to help users build credit while promoting responsible card usage. Alternative credit cards could be a great entry point for the 1.4 billion adults who are unbanked across the globe.

Why they’re popular:

Alternative credit cards offer consumer lenders an opportunity to attract new users who wouldn’t typically qualify for traditional credit cards due to a thin credit file, no credit file, or low credit score. By offering cards that teach users how to build credit, with low spending limits and auto-payments, lenders can help consumers establish good credit and build a relationship with them for future financial products.

How to offer them:

Perhaps not surprisingly, alternative data is the key to alternative credit cards. Alternative data refers to all the financial information that is not included in a credit report, like utility bills, rent payments, employment history, and sometimes even social media. Since these cards are built for consumers without traditional bureau data, lenders can create their own credit scoring models by integrating a wealth of alternative data into their decisioning engines. If you’ve got alternative data, you’ve got the foundation for alternative credit cards.

Trend 2: BNPL Payments

Buy Now Pay Later (BNPL) functionality is becoming increasingly popular in the credit card industry as credit card lenders look to carve out space in their direct competitors’ $19.5 billion market. Adding BNPL-style payments to credit cards allows consumers to spread out the cost of their purchases over time, typically with a short-term, interest-free period between three and six months. It also allows credit card lenders to take back some of the business they’ve lost to BNPL players.

Why it’s popular:

BNPL functionality is becoming popular because it offers increased flexibility and accessibility to consumers while adding additional revenue streams and competitive advantage for credit card lenders. Consumers get more time to pay off larger purchases and don’t have to create an entirely new BNPL account or download yet another app to benefit. An added bonus is built-in rewards they already receive with their credit card. Lenders can enjoy boosted revenue from BNPL interest, but the major draw is the potential to attract new customers and retain existing ones – if your credit card already offers BNPL, there’s no need to make purchases with another financial service provider.

How to offer it:

To use BNPL functionality effectively, issuers need to increase the flexibility of their platform. This can be achieved through the use of advanced decisioning capabilities, which can identify users who are most likely to use BNPL functionality, determine personalized offers, and even monitor behavior to optimize plans based on payment activity – all while reflecting your risk appetite. 

Trend 3: Hyper-Personalization

80% of consumers want credit card offers tailored to their needs – personalization is no longer a bonus, but a basic requirement. From onboarding through the entire customer lifecycle, hyper-personalized credit cards are meeting customers where they are and supporting them on their financial journeys. As economic conditions vary, these cards – which are powered by machine learning and advanced decisioning and analytics – can help ensure consumers can still pay off their cards and credit card lenders can maintain low risk portfolios.

Why it’s popular:

Hyper-personalized cards are attractive to new users, looking for tailored benefits and rewards built specifically for their spending patterns, behaviors, and even lifestyle. A hyper-personalized credit card may offer rewards for specific categories of spending that the user frequently engages in, such as travel, dining, or online shopping. The card may also offer exclusive benefits such as discounts, cashback, or concierge services, which all drives customer loyalty. The data-driven approach behind hyper-personalized credit cards can also help users to better understand their spending habits and make more informed financial decisions, while helping lenders gain insights into their customers’ spending habits and preferences, reduce risk and minimize losses from delinquent accounts, and ultimately identify potential risk factors and take proactive measures to prevent defaults.

How to offer it:

Hyper-personalized credit cards run on data, decisioning and machine learning technology to provide advanced analytics. This technology enables lenders to gather and analyze vast amounts of alternative and traditional data to gain a deeper understanding of a borrower’s financial profile and build a credit card experience just for them. Decisioning technology can also be used to automate the credit card application and approval process, allowing lenders to quickly assess a borrower’s creditworthiness and make personalized credit offers in real-time.

Go From Trending to Thriving

The credit card industry is evolving rapidly, and these three trends represent just a few of the innovative changes taking place. Alternative credit cards, BNPL functionality, and hyper-personalization are reshaping the way consumers access and use credit while helping contribute to the growth of the global industry. 

By embracing these trends, credit card lenders can reach new, creditworthy thin file or no file users, compete with rising BNPL players, and meet the exact needs of current customers. However, companies must leverage advanced analytics and alternative data sources to get the most out of these new features. As the industry continues to evolve, it’s clear that credit cards will remain an essential financial tool for consumers, and those who embrace innovation will be best positioned to thrive.

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When Were Credit Scores Invented

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When were credit scores invented and how does credit scoring work?

The History of Credit Scores

Credit scores and reports are essential components of financial services products. But do you know when credit scores were invented and how consumer credit reporting works? In this guide, we provide all the information you need to know about credit scores, including their history, and how they impact your financial life. Keep reading to learn more.

Credit Scores and Credit Bureaus: An Origin Story

Credit scores as we know them today have only been around for a few decades. However, credit reporting itself began early in the 19th century, as commercial lenders attempted to ‘score’ potential business customers to determine the risk in providing credit to them. The very first credit reporting agencies (what we know now as companies like TransUnion and Equifax), began as local merchant associations. They simply collected various financial and identification information about potential borrowers and then sold it to lenders – but these were focused strictly on commercial/business loans at the start, offered to organizations that needed funding to launch or grow their operations. The earliest credit reporting agencies in the United States were R.G. Dun & Co and the Bradstreet Company (sidenote: sound familiar? The two companies merged in 1933 and rebranded as Dun & Bradstreet Inc. in 1939), which developed an alphanumeric scoring method to determine the risk factors associated with commercial loan applications.

In the early 20th century, modern credit bureaus were formed, looking more closely like we know them today. Taking a page out of the commercial-loans book, retailers began offering consumer credit to individuals. These retailers all had individual credit managers, tasked with determining creditworthiness of applicants. In 1912, they decided to band together and formed a national association to “develop a standard method for collecting, sharing and codifying information on retail debtors.”

In subsequent years, the three major credit bureaus in the U.S. were born – today known as Equifax, TransUnion, and Experian. Through the 70s and 80s they worked together to develop consistencies in credit reporting methods and pushed for an unbiased, more automated way of determining credit scores.

Credit Score Vs. Credit Report
But what IS a credit score? And how is it calculated? And what’s the difference between a credit score and a credit report?

A credit report comes first. A detailed historical record of your financial transactions and financial status, a credit report includes everything from identifying personal information (name, address, date of birth), to consumer credit accounts (credit cards, lines of credit, auto loans, mortgages), and ‘inquiry’ information (i.e., information on the companies who have pulled your credit report to make you offers of new credit products, or pre-approvals for upsells, etc.). A credit score is then calculated based on that information. Typically a three digit number (we’ll get into regional differences later), this credit score quickly tells potential lenders how creditworthy you are. In North America, the higher the score, the lower risk you are and therefore, a more worthy applicant.

Traditional credit scoring systems are not without fault, however. They often don’t take into consideration additional factors that can influence your credit risk level (i.e., most modern credit reports don’t include rental payments, which can be a very accurate predictor of someone’s propensity to pay back debt.) And there can be a significant lag between an applicant’s activities and pulling a credit report/score – real-time data is much more valuable (and accurate) in assessing an individual’s risk.

So how do credit scores really work? A mathematical formula based on the information found in your detailed credit report, a credit score allows potential lenders to instantly assess how creditworthy you are. A higher credit score indicates that a) you are more likely to pay off your debt/repay any credit provided and b) pay off that debt both on time, and according to the agreed-upon terms. With a more favorable credit score, you are more likely to have lenders extend you credit products, such as new credit cards, auto loans, mortgages, and consumer loans. Beyond that, the higher your credit score, the more likely it is that lenders will offer you better terms, including flexible repayment schedules and lower interest rates. If you are stuck carrying a low credit score, you run the risk of not being able to access credit when you need it or having to accept higher interest rates.

Calculating Your Credit Score

A FICO score (Fair, Issac and Company) is one of the most well-known credit scores in the US. In fact, “FICO scores are used by 90% of the top US lending institutions for their risk assessment needs.” These three-digit scores, which first began in 1989, are calculated based on the information found in your credit report from one of the three major credit bureaus. There are five main factors that FICO uses to calculate your credit score, with different categories carrying different weights. (Sidenote: other credit scores are calculated much the same way but may have different weights associated with the main contributing factors.)

For FICO scores, the factors are:

  • Payment history (35%)
  • Balances owed/credit usage (30%)
  • Length of credit history/age of accounts (15%)
  • Credit mix (10%)
  • Recent credit activity and new accounts/new credit inquiries (10%)
Credit Scoring Around the World

Despite the overwhelming prominence of the United States’ three main credit bureaus, there are regional differences in credit scoring models and the use of credit scores. While each region uses the same basic premise of evaluating an individual’s credit history to determine their creditworthiness, there are variations in how that credit scoring is executed. The main variations in credit scoring methods relate to:

  • How long certain information stays on your credit report
  • Who can contribute information to your credit report
  • How many credit bureaus exist in a particular country/region
  • Whether those credit bureaus are for-profit or not-for-profit (and who owns them)
  • Whether lenders are required to use your credit report and/or credit score to determine your risk level
Here’s a handful of examples of the ways various regions handle credit scoring:
  • United States – Lenders report details of your financial situation, including credit and historical transactions, to one of the three major credit bureaus (Equifax, Experian and TransUnion) – who then either generate a credit score or provide the credit reports to a credit scoring company like FICO, which then calculates a FICO score.
  • Canada – Canada is similar to the U.S, but doesn’t use Experian as a credit bureau, and its credit scores upper limit is 900 vs 850.
  • United Kingdom – The U.K. has three major credit agencies – Equifax, Experian and Callcredit (Noddle), but each organization calculates credit scores differently.
  • France – There are no official credit reporting agencies in France; instead, credit scores are built on a bank-by-bank basis but aren’t transferable to other lending institutions.
  • Netherlands – The Netherlands has a single credit bureau, Krediet Registratie (BKR), which unpaid debts are reported to.
  • Germany – The main credit agency, SCHUFA, is a private company that tracks accounts, unpaid debts, loans, and any delinquencies. Your SCHUFA score goes down (which is positive) as you gain financial history and pay down debts.
  • Australia – Australia has four main credit bureaus (Equifax, Dun and Bradstreet, Experian, and the Tasmanian Collection Service).
  • India – India utilizes one official credit reporting agency, Credit Bureau Information India (CIBIL), which is a partner of TransUnion.
  • Japan – There is no official credit scoring system in Japan, and creditworthiness is simply determined by individual lenders, making it extremely difficult to get credit if you are a foreigner.
How does credit scoring affect consumer lending?

A credit score that is rated as ‘good’ or ‘excellent’ will save most people thousands of dollars over the course of their lifetime. If you have excellent credit, you get better rates and payment terms on everything from mortgages and auto loans to credit cards and lines of credit – essentially anything that requires any sort of financing. If you have a better credit rating, you are seen as a lower-risk borrower, with more banks and lenders readily competing for your business by offering better rates, fees, and perks. On the flipside, those with poor credit ratings are seen as higher-risk borrowers, and may either have less favorable lending terms (higher interest rates in particular), or be unable to access credit at all when they need. Apart from just accessing lending products, those with poor credit scores may find it difficult to find rental housing, rent a car or even obtain life insurance.

Lenders use credit scores as part of their risk decisioning process to determine the creditworthiness of a potential individual or business customer. So, the ripple effect of either a positive or negative credit score is significant – and it can last an incredibly long time, particularly if there are delinquencies or defaults noted on your credit report.

However, part of the issue with this is that credit scoring can often have inherent biases. This greatly impacts various demographics from fairly accessing credit. For example, immigrant communities may not have formal credit histories. No credit history = low credit score. Low credit score means they can’t easily access lending products and therefore can’t start building a credit report/score. Or they are forced to accept suboptimal terms with exorbitantly high interest rates and may have difficultly paying down that debt as a result. Which of course, is a mark against you on your credit report.

Alternative Data for Financial Inclusion

The example above is not uncommon in our global society – there are countless immigrant populations in countries all over the world, and millions more who have no access to formal financial services products. There are many terms for those who lack a traditional credit history – thin-filed, credit invisible, unbanked, underbanked – but it essentially refers to anyone who doesn’t have information in their official credit history/report to generate a credit score. This includes an estimated 62 million Americans, 200 million people in Latin America and 3.6 million in Asia having no access to formal credit. One-third of all adults globally (up to 1.7 billion people) lack any type of bank account.

How can lenders ensure equal access to credit, even for those without formal credit histories, without sacrificing their risk strategy? One way is to use alternative data. Alternative data includes anything outside of a traditional credit report that may indicate creditworthiness, including telco information, rent and utilities payment info, social media and web presence, travel data and open banking info.

Because this type of data is often missing from traditional credit reports (and thus the formulation of credit scores), they can be inherently biased towards certain minority demographics. The data that FICO scores consider (like payment history, length of credit history, etc.) is also often influenced by generational wealth and the passing of large assets like homeownership (i.e., mortgage data counts towards your credit score, rental payment usually does not). “The Black homeownership rate was 44% at the end of 2020 compared to the 74.5% rate for non-Hispanic white consumers. Since credit scoring models look at homeowners’ housing payments and ignore renters’ rental payment history, Black consumers are at another disadvantage, despite both types of payments falling under the same category of “housing.” Ensuring that lenders are supplementing traditional credit scores with alternative data helps to overcome that bias and ensures financial inclusion.

Using alternative data helps to provide a more holistic view of the financial health (both current and future potential) of customers, improves decisioning accuracy and even helps increase fraud protection with improved identity verification and KYC onboarding processes. Enabling more accurate credit decisioning allows lenders to expand their market safely, without increasing risk, and helps to encourage access to all unbanked/thin-filed individuals, setting people on the path to safely building their credit scores. Eighty-seven percent of lenders using alternative data are using it to more accurately evaluate thin/no-file customers and 64% improve their risk assessment among unbanked consumers.

Apart from individual lenders looking to alternative data sources, some credit bureaus are now offering ways to boost credit scores for thin-filed consumers:

  • Experian Boost – collects financial information that isn’t normally found in your credit report (i.e., utility payments and banking history) and includes that in the calculation of your Experian FICO score.
  • UltraFICO – free program that utilizes historical banking information to build your FICO score, looking at factors like paying bills on time, avoiding overdraft, and having savings.
  • Rental info reporting – new services that track rental payments and report that info to credit bureaus on your behalf.
How to improve your credit score
If you are struggling with a less than ideal credit score, don’t fret. There are steps you can take to improve your score over time:
  • Pay your bills on time, every time. This includes everything from mortgage payments and car loans to credit cards, utility bills and cell phone plans.
  • Reduce your overall credit utilization. Credit scores look at your credit utilization (the portion of your available credit that you use at any given time). After payment history, credit utilization is the second more important factor when calculating your credit score. Aim for 30% credit utilization or less to keep your credit score favorable and try to pay off credit card balances in full each month. (Bonus tip for a quick win – ask your credit card issuers to increase your limit slightly so your debt ratio goes down.)
  • Don’t apply for too much credit. New credit requests start with a ‘hard inquiry’ (hard inquiries include applications for new credit cards, mortgages, auto loans – too many of them can increase your credit score). Revolving credit (regularly closing old accounts and opening new ones) also has a negative impact on your credit score. Additionally, credit scores look at how long you’ve had your credit accounts – keep your old accounts open and old credit cards active but be sure to deal with any collections or delinquent accounts. If you have a lot of outstanding debt over various types of accounts, consider consolidating your loans, which results in one repayment, and possibly a lower interest rate to boot.
  • Sign up for credit monitoring services. These services can alert you to fraudulent behavior on your profile, help you keep up to date on your credit score, and often offer special tips on how to improve your credit score.

It’s clear that credit reports and credit scores have a significant impact on your ability to access credit. But as the financial services industry evolves, there are more and more innovative ways to determine creditworthiness, including the integration of alternative data, implementation of advanced decisioning solutions, and using more accurate, predictive models with artificial intelligence. And there are now more varied opportunities to access credit and financial services products, including the advancement of buy now, pay later (BNPL) solutions, and neobanks and fintechs who are taking a fresh approach to credit products.

If you’re a lender, how can you ensure that the history of credit scoring continues to evolve into something more holistic, more accurate, and more inclusive? Discover how a unified decisioning platform and easy access to a variety of data sources can help you say yes to more people, without increasing your risk.

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Further Reading:

15 Companies Changing the Landscape of BNPL

The Long, Twisted History of Your Credit Score

– Time Magazine

A History of Credit Scores

– point.app

The Fair Credit Reporting Act (FCRA)

– Investopedia

Learn more about how to improve decisioning accuracy and encourage financial inclusion with alternative data

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