TurnKey Lender

The Power of Automating and Digitalizing Your Credit-Risk Management

img_Turnkey-Lender_The power of automating and digitalizing your credit-risk management-1920-2

In Europe and North America, market-based credit-risk indicators suggest a robust “repayment recovery” is underway, with models that gauge default possibilities nearing pre-pandemic levels as of mid-June 2021, and signs of smooth sailing well into 2022. But credit-rating agency Standard and Poor’s warns that conventional risk-assessment metrics may not be adequate for particular market segments. The reason? Measurements of suitability for consumer and B2B lending have lost much of their predictive power for businesses and individuals impacted by pandemic-related work stoppages. This makes it hard to distinguish temporary setbacks from the advent of new normals for would-be borrowers in some industrial sectors. The answer to this seemingly intractable problem? Automated credit-risk management, which can process more inputs and render more decisions faster and more accurately than ever before. “Credit risk refers to the chance of loss from a borrower’s failure to repay debt,” says Dmitry Voronenko, co-founder and CEO of TurnKey Lender, a top lending software provider. “In turn, credit-risk management refers to measures taken to mitigate losses by understanding the adequacy of a bank’s capital and loan loss reserves at any given time as well as measures taken in credit ‘decisioning’ and loan origination to make applicants’ financial situations more transparent to lenders.” Learn about TurnKey Lender’s Decision Engine in detail to outperform any and all competitors and reduce credit risk. Credit-risk controls impacted by internal and external pressures on lenders Automated, or digitally enabled, credit-risk management is a form of gatekeeping that incorporates big-data inputs and artificial intelligence to help lenders make better decisions faster than ever before. Additionally, it helps lenders: Tap into unbanked and underbanked consumers — 7.7% and 17.9% of US adults respectively, according to the Federal Reserve Achieve automatic compliance around anti-money-laundering and know-your-customer regulations And while the coronavirus pandemic quickened the pace of digital adoption for the sake of social distancing, the shift to automated credit-risk management was underway before Covid-19 quickened the pace of digital adoption for the sake of social distancing. “External and internal pressures are requiring banks to reevaluate the cost and sustainability of their risk-management models and processes,” McKinsey says in a 2016 report called “The value in digitally transforming credit risk management.” The pressure came from regulators, emerging fintech competitors, company-stock holders, and the banks’ own customers, the report adds. Due to more stringent capital requirements in the wake of the 2008 Financial Crisis, higher fines for noncompliance, and lagging cost efficiency, the share of risk and compliance in “total banking costs” went from about 10% in 2012 to a projected 15% for 2017, McKinsey reported in 2016. “This puts sustained pressure on risk management, as banks are finding it increasingly difficult to mitigate risk through incremental improvements in risk-management processes,” according to the consultancy. Another trend changing the face of lending centers on evolving external and internal expectations. Externally, customers want mobile and digital solutions. The global digital lending market, valued at $4.87 billion in 2020, is expected to expand at a compound annual growth rate of 24.0% from 2021 to 2028, says Grand View Research. Already by 2018,73% of consumers were using online banking channels at least once a month, according to Deloitte. High indebtedness plus systemic disruption calls for better risk controls Meanwhile, executives and business strategists within lending organizations have come to expect timely and accurate credit-portfolio reports to help them spot emerging troubles, improve efficiencies, calibrate marketing initiatives, and inform pricing. McKinsey’s prescription is short and sweet. “Banks need to digitalize their credit processes,” the company says. “Lending continues to be a key source of revenue across the retail, small and medium-size enterprise, and corporate segments.” While most of McKinsey’s assessment still holds water, digitalized credit-risk management has emerged as a must-have not just for banks, but also for a growing array of non-bank organizations — from retailers to capital-gear providers, medical practices, and nonprofits — that seek to bypass the middleman and provide white-label, software-based lending and loan management directly to customers. And this trend was well in evidence when the pandemic took hold. Pre-Covid, lenders had become alarmed about rising debt levels in the US — $14.1 trillion in February 2020, spurred mainly by mortgages and credit cards. Now, with households under pressure from lost wages and other pandemic-related financial hardships, lenders are monitoring and identifying would-be borrowers who are under financial strain in their due diligence. Fortunately, credit-risk-management tools are more robust than ever “At the same time, however, lenders equipped with the right lending technology can now look to alternative credit scoring to get more holistic views of applicants,” according to lending-tech expert Voronenko. “In fact, lenders can use alternative scoring to safely extend credit where — using only traditional means derived from applications and credit-bureau reports — such probing wasn’t feasible before.” With artificial intelligence shedding light on otherwise impenetrable data sets to include factors established as behavioral finance “tells,” lenders can compare permission-based inputs around spending and bill-pay habits to find low-risk applicants among some that would be considered high-risk using only traditional scoring methods. Companies eager to leverage advances in integrated lending software to establish their own credit facilities may be familiar with traditional and other third-party lenders, but a close comparison of old-school processes with the existing state of the art can be impactful. Decision time Traditional underwriters can take up to nine days to collect and analyze all relevant data and make a final crediting decision. With advanced, cloud-based lending software, decisions can be made — at the barest minimum — twice as fast. Often decisions can be rendered in a matter of minutes or in many cases instantly once scoring and decisioning are finetuned. Scalability Using manual and other traditional procedures, it can be hard to scale due to operational expenses that grow as new customers are onboarded. With advanced and fully-supported lending software, risk scores and loan decisions are automatic — virtually “hands-free” from a staffing perspective. Human error Everybody makes mistakes. But in the realm of risk management, mistakes can

Ten Blockbuster Reasons You Need an Automated Solution for Commercial Underwriting

img_Turnkey-Lender_Ten blockbuster reasons you need an automated solution for commercial underwriting-1920-4

In a worldwide rush for greater efficiency in financial transactions, automated underwriting stands out for its breadth of application and for acting as a catalyst for increasing competition between online and traditional lenders. Though we’re focused here on its role in consumer and middle-market B2B lending, its impact has been felt in financial segments as diverse as mortgage lending, bond issues, and insurance policies, according to Investopedia. Functionally, automated underwriting is an algorithm-driven process for evaluating the risk of specific transactions. Effectively, it takes humans out of the loop. The result? Decisions, based on the lender’s customizable guidelines, that are more accurate, and rendered much faster than the “analog” alternative.  Why underwriting automation isn’t just for banks   Automated underwriting has spread from credit cards and mortgages in the 1990s to banks and other traditional lenders as the internet took off. “Now a host of retailers, equipment suppliers, and medical practices” encompassing not just traditional lending but also “other credit scenarios such as invoice factoring, leasing, and even pawn-shop transactions employ automated underwriting,” says Elena Ionenko, co-founder and operations chief for TurnKey Lender, a pioneer in the space. “It extends to any financial transaction aided by an assessment of a would-be borrower’s ability to repay the loan amount plus interest — and that’s true whether it’s a consumer buying a lawnmower or a civil engineering firm looking to deploy a half-dozen commercial drones for surveying inaccessible terrain.”  So what, past the availability of the technology, is behind this new surge in uptake? In a word, economics. A lender’s ability to gauge a loan applicant’s creditworthiness will increase the quality and scale of its loan portfolio and increase customer satisfaction. In an increasingly digital world, lenders mired in paper-based vetting procedures operate at a competitive disadvantage that is virtually impossible to overcome.   Book a demo to see TurnKey Lender’s AI-driven underwriting software in action. Benefits of Automating Commercial Underwriting    To show how this economic advantage plays out, here are 10 of the most important ways automated underwriting makes lending more attractive, efficient, and compliant.  Enhanced decision making: Automated underwriting isn’t just about faster decisions. It’s also more accurate than its spreadsheet-based forebears, which is, in turn, fairer to everyone involved. After all, while people are notorious for having bad days and succumbing to stress from time to time, algorithms never burn out or slip up. Crucially, automated underwriting can also take account of factors relevant to approval — such as spending habits and social-media comportment — that go beyond old-fashioned assessments based on credit scores and biographical questionnaires.  Consistency: The rules the lender sets for automated credit decisioning can be both customized to specific clients or client types and consistent with bedrock policies. Say goodbye to guesswork and interpretation.  Portfolio yield: Automated underwriting lays the groundwork for predictive models that pinpoint optimal loan rates and terms while helping lenders of all kinds improve portfolio yield by selecting the most profitable customers.  Productivity and workflows: Once again, lenders and applicants alike benefit from a credit-underwriting system that saves time for everybody involved. Faster approvals and streamlined processes for the lending lifecycle from applications to final repayment make for more accurate outcomes and more cost-effective lending.  Analytics: Robust and accurate digitalized underwriting makes for actionable lending intelligence derived from accessible data analytics that can guide operational improvements and create new marketing and UX insights.  Compliance and fraud detection: Underwriting automation strengthens fraud-detection efforts by means of predictive analytics. In addition to raising red flags, a robust automated lending platform will allow updated rules to take force across the entire system, instantly. In this way, the lender is much likelier to remain compliant and on guard against fraud.  Scalability: Automated underwriting is scalable in that an influx of new customers doesn’t necessarily call for more people to perform credit-check responsibilities around classification, analysis, stacking, and extraction. And in our context, automated underwriting is understood to be part of a loan processing system that encompasses other critical functionality around loan and loan-portfolio management for end-to-end scalability that allows companies to cover more ground without having to add headcount.  Affordability: This is especially true of automated underwriting linked to systems with a modular format. “With TurnKey Lender, you can start small and add functionality as needed,” says Ionenko. “As a reflection of our clients’ preferences, it’s as far from all-or-nothing as it gets.”  Oversight: Automated underwriting — like all elements of lending automation — leaves tracks. This analytical prowess, already mentioned, also helps managers and executives stay on top of things generally, and enables troubleshooting and internal audits.  Customer experience and marketing: As more companies in more fields employ automated underwriting, more consumers and companies eager to secure financing have come to see it as a must-have in a financing partner. They may not know that credit decisions hinge now on sophisticated algorithms and artificial intelligence with the ability to learn new lessons and make sound inferences. They may only know that their credit applications are processed faster than ever before. But that’s enough to feed into positive word-of-mouth publicity and enhance the lender’s overall marketing efforts.  Ten is a nice round number, but it wouldn’t be hard to extend the list of the benefits companies can derive from automated underwriting. To this end, terms like “Convenience,” “Ubiquity,” and “New revenue from fees” spring to mind. But you’d be hard-pressed to make the point better than TurnKey Lender’s Ionenko.  “From the lender’s point of view, underwriting is the first gate-keeping function in every loan application,” says the tech executive. “Making sure it goes as quickly, accurately, and pleasantly as possible can set the tone for the entire engagement, lead to repeat business and, overall, enhance the average value of your customers.”

Forbes Council: How AI equips lenders to avoid Covid-era pitfalls

img_Turnkey-Lender_How AI equips lenders to avoid Covid-era pitfalls-1920

Elena Ionenko, co-founder and COO at TurnKey Lender, shares her insight into real-life applications of AI in lending in a new Forbes Council piece:  The traditional approach to loan-portfolio management puts collections and overall performance on one side, and origination on the other, with decisions that should be closely coordinated made by separate departments, often deployed across distinct software systems. But that’s changing as senior managers work to strengthen ties between departments and advances in artificial intelligence allow for more nuanced — and more inclusive — procedures for vetting would-be borrowers. Putting origination on an equal footing with other parts of loan management does more than provide holistic overviews. It puts extra resources into gatekeeping, providing a crucial first step in credit-risk evaluation and fraud detection, a must-have for overall portfolio health. It also equips lenders to compete in today’s tough economic environment, a byproduct of business shutdowns, workplace furloughs and the general public’s hesitancy to congregate in a pandemic. In this context, it’s vital that alternative data inputs be uniformly formatted, easy to interpret, and available as an aid to decision making. Converting such data into a scoring model requires advanced artificial-intelligence tools and processes, tons of historical data, and years of hands-on experience. But AI-derived credit scoring is vastly more accurate than traditional approaches — which hinge on credit-bureau scores and application responses — and provides lenders with the confidence they’re getting a fuller picture of applicants and approving better-performing loan, even in hard times. The result? More good loans and better portfolio performance. Meanwhile, there are real-world consequences to sticking with outmoded scoring models. Because old-line lenders aren’t usually able to change underwriting standards without accessing flexible, easy-to-configure and easy-to-deploy technology, it’s likely banks will experience a new wave of non-performing loans in the next year, according to industry consensus. Read full article of Forbes or schedule a live TurnKey Lender demo today.

Alternative Credit Scoring for Non-Traditional Lenders in Canada

img_Turnkey-Lender_News_TurnKey Lender Becomes a Member of the Canadian Lenders Association

The Bank of Canada recently rained on hopes for a quick recovery from the economic impacts of the country’s coronavirus slowdown — a hope nurtured, many thought, by signs of economic resilience over the summer.  Alas, late in October, the Canadian central bank issued a Monetary Policy Report suggesting that hard times will continue, perhaps all the way through 2022.   “The Bank estimates that over 2020–23, persistent scarring effects of the pandemic on the labour force,” the Bank of Canada writes. The word “scarring” is a favorite of chief central banker Tiff Macklem, who has been issuing periodic warnings of tissue damage to the Canadian economy since the pandemic was declared in mid-March 2020.  Assessments like this should prompt non-traditional lenders — conceivably any business that might want to extend credit, from retailers to car dealers — to rethink how they gauge loan applicants’ creditworthiness. Why? Because businesses of all sizes in every province and territory will be looking for capital to help them through a recession made worse by:  A pandemic that isn’t over, resulting in  The need for ongoing social-distancing measures that can snag business recovery, such as expensive new workplace configurations and equipment   Pinched household budgets and other recession-related woes, leading to  Subdued consumer spending   Meanwhile, many lenders will be making credit decisions based on inputs that aren’t adequate to the times.   Credit scoring in Canada in the face of uncertainty  Applying old-school analysis where new market conditions prevail could curtail lending and stall economic activity. For lenders of this ilk, being behind the times could jeopardize opportunities to make sound and profitable loans.  Download the free white paper now: HOW-TO-WIN-KEEP-CUSTOMERS-WITH-RETAIL-FINANCING Lenders traditionally rely on credit scoring based on objective financial data and subjective views on some of the would-be borrower’s non-financial traits. In this approach, the financial data includes the prospective borrower’s credit history, and line-item comparisons of historical financial statements submitted by the applicant. Among traditional non-financial inputs are the would-be borrower’s profile (employment, status, degrees, home and car ownership), a qualitative assessment of the borrower’s previous dealings with the lender, and, for business loans, relevant business plans.  In this approach, financial data has more weight in determining how stable and efficient the applicant is when it comes to their finances.  Although recent word from drug maker Pfizer seems to bode well for a Covid-19 vaccine, the company’s claims have not been verified, and, given the logistic challenges, widespread distribution of a vaccine is unlikely before, at the earliest, mid 2021. For now, it’s prudent to remember we don’t actually know how long either the pandemic or its economic aftershocks will last.  “These uncertainties erode the rationale behind applying only traditional credit analysis,” says Elena Ionenko, co-founder and business-development head of lending-technology provider TurnKey Lender. “After all, real-time financial data can be as indicative of repayment as historical information.”  Adds Ionenko: “This analysis can be performed on a continuous basis — triggering monthly or quarterly reports — that provide dynamic updates on the loan, which helps lenders see how the borrower is coping in real time with the challenges of a recession, while comparing these results to pre-crisis data.”   Guided discretion  In a typical lending scenario, lenders start off by “scoring” loan applicants to determine the likelihood of their returning an amount owed with interest in a given period. Most use third parties such as Fair Isaac, whose Canadian FICO scores assign numerical values between 300 and 900, with 900 indicating maximum creditworthiness.  For the most part, this traditional scoring relies on factors such as:  How long the applicant has been using credit  The amount and type of debt an applicant already has  Current interest rates on outstanding accounts  Lenders use these reports to generate a risk profile of the applicant, which helps lenders determine whether to make a loan in the first place, and the terms of any loan that’s approved. Obviously, applicants with low credit scores tend to be assigned higher rates of interest than those with higher scores, though the ultimate decision is made by the lender, with FICO inputs used as guardrails.  Of course, the pandemic has eroded the credit standing of many who have lost jobs or seen wages cut, necessitating new ways to evaluate consumer creditworthiness.  Low FICOs and the unbanked  For example, a FICO score won’t tell if an applicant has lost her job or seen her income dip in the public-health crisis. One solution to this increasingly widespread problem is working with alternative data sources for determining creditworthiness.  One of the most reliable sources of information? An applicant’s bank accounts.   Read about TurnKey Lender Bank Statement Scoring on our knowledgebase. Some lending-technology providers empower lenders to examine applicants’ bank accounts and track transactions to take note of spending habits and monitor employment and non-employment income including such responses to the pandemic as stimulus payments, forgivable loans, and unemployment-insurance proceeds.   Some advanced lending-tech firms equip lenders to see these data points, and more. For example, alternative scoring can uncover normally hidden risks such as an applicant’s gambling expenditures and overdraft durations and apply them to credit decision making.  Read about TurnKey Lender’s AI-Powered Decision Engine. And for consumers who are unbanked or underbanked — 18% of Canadians, according to ACORN Canada — alternative scoring is a must. More so when you take account of LexisNexis research indicating that 51% of traditionally unscorable applicants in the US are as creditworthy as consumers with high traditional credit scores.  Augmentation, not replacement  “This doesn’t devalue traditional credit scoring,” says TurnKey Lender’s Ionenko. “For predictive power, no one alternative approach is as formidable as credit-bureau input.” Alternative data points are more numerous, more scattered, and less organized than the data that contributes to a traditional credit score, she explains. “This means neural networks and other AI-based tools are required, which is an approach we pioneered.”  Fortunately, these resources are now available to lenders, and the additional intelligence this normalized alternative data provides helps lenders understand their customers better, make better loans, and build better-performing loan portfolios.  Years using alternative data sources to assess consumer creditworthiness in the developing world has paid off for some lending-tech makers, giving

Open Banking As The Permanent Disruptor of Lending


Open banking changes everything “Open banking” is a financial-information exchange methodology and a source of innovation that’s transforming banking as we know it. It gives third-party financial-service developers and providers permission-based access to customers’ financial data from financial institutions via “application programming interfaces,” or APIs. In plainer terms, open banking has the potential to change everything about banking, from who gets to be a customer to who provides underlying services (and on what terms). Philosophically tied to the information-age principle of “open innovation,” open banking includes the “open data” concept, which holds that some data should be freely available for everyone to use as they wish, without restrictions from copyright, patents or other claims to exclusivity, according to one study. At root, open banking is based on the idea that data can be used to improve customer outcomes along the lines of faster, fairer, and more accurate service delivery — and that without it, the potential for innovation is blunted by considerations of data ownership. “Many financial institutions welcome APIs begrudgingly, as a cost of doing business,“ says Elena Ionenko, co-founder and business-development head of lending-software maker TurnKey Lender. “But we see them as powerful tools for making the most of relationships between customers and banks — or bank-like entities, keeping in mind that it’s not just banks playing a role these days.” The case for open banking In fact, lending by retailers, medical-service practices, capital-equipment providers is on the rise, and their success is as dependent on unhindered open-banking inputs as any old-line bank. Just in terms of mortgages, non-banks originated 53% of US loans in 2016, but 64% of home loans for black and Hispanic borrowers, according to a Brookings Institute report cited by the Washington Post. With open-banking coming to the forefront as an equalizer in the marketplace, fintech innovators have APIs in mind at virtually every turn. “Part of the agility you need to compete as a lending-tech provider these days is reflected in how configurable you are,” says Ionenko. “Nothing is hardcoded here because we know we have to be ready to support any lender anywhere in the world at any time. We win business because we’re API-minded, and have been from our inception.” Meanwhile, informed consumers see putting their (usually anonymized) financial information out there for use by third parties via APIs as a fair exchange for better service at better prices and, in some cases, for more accurate credit scores. Imagine paying for your daughter’s guitar teacher for this week’s Zoom-based lesson with your smartphone. That’s something you can do right now, and it’s all thanks to open banking, which allows you to buy items or services with a phone app that’s linked to your bank card or PayPal account. The fact you can pay that way involves a veritable ecosystem of permission-based data sharing, but the technology and necessary protocols are more than up to the challenge. Integration and interpretation of data In practical terms, open banking is dependent on database integration, and the mining and management of data that provide relevant customer insights. The timeliness of a loan applicant’s rent and car payments can shed light on the ability and willingness to meet additional financial obligations. This can help determine loan scores that are more nuanced than old-line credit scores — which have in turn have been criticized for perpetuating race, gender, and age disparities in lending decisions. In fact, innovations in loan-servicing software show how open banking can work to everyone’s advantage. Typically, lenders participate in open banking in one of three capacities. They seek to originate loans as a lender They want to create a proprietary service that complements their loan products, like an enhanced credit score They are partnered with such complementary service providers Whether the offering is a direct loan or another service that can help establish or improve relationships between lenders and customers, it can function as a lead generator that owes its power and durability to an open-banking environment. Open banking as a permanent disruptor The fact that customers have to “opt-in” to benefit from open-banking programs puts a constraint on lenders and related service providers because customers have to see a clear-cut benefit from participation. Incentives of this type in the lending realm include: Easier access to loans through point-of-sale loan-origination systems More nuanced loan decisioning derived from more credit-score inputs with better consumer outcomes “Favored client” status with access to offers and incentives that can help establish enduring customer-lender relationships In some jurisdictions, oversight of open-banking systems has been formalized. In this category are the European Union, the UK, Australia, and Hong Kong. Meanwhile, in most of the Americas, and in the Asian-Pacific region, open-banking protocols are on — or quite close to — near-term legislative agendas, according to news reports. And it’s safe to assume that compliance criteria will change as open-banking technologies evolve. “The future of open banking and API development is exciting to contemplate,” says TurnKey lender’s Ionenko. “The concept and the interfaces that make it real add up to a disruptor for which pre-digital legacy systems are a clear hindrance. The future of banking belongs to providers who are technologically nimble enough to align themselves organically to the brand at the front of every customer engagement.”

Seven Ways to Tell if an LOS Provider is Right for You


With hope for a quick economic recovery from coronavirus lockdowns seemingly dashed by the contagion’s resurgence around the globe, financial-service firms, retailers, and business-to-business providers are looking with renewed intensity for adaptations to the pandemic and nascent post-pandemic protocols.   For some businesses, COVID-conscious office layouts, plexiglass partitions, and staggered shifts have come into view as components of workplace social distancing. For others, remote and contactless commerce will be make-or-break, with e-lending playing a prominent role in helping businesses and consumers rebuild around an amorphous new normal.  Rising demand for loan origination systems  E-commerce has been around since the mid-1990s at least. But fully supported e-lending took wing later, during and right after the Financial Crisis of 2008. Its first iterations formed the underpinnings of web-based lending through traditional players such as banks and credit unions, along with some direct-to-consumer forays by fintechs.   Since the mid-2010s, however, online lending has emerged as a force in retail, equipping businesses to extend credit to consumers at the cash register or on the road, with decisioning analytics performed in minutes rather than hours or days — and in some cases without the need for financial intermediaries.   “The point is to give businesses more opportunities to close more sales and deepen customer relationships while creating stronger loan portfolios and providing mission-critical business intelligence,” says Dmitry Voronenko, CEO and co-founder of lending-platform provider TurnKey Lender. “We’re seeing rising demand from traditional lenders and retailers, as well as from businesses involved in capital-equipment factoring, trade facilitation, and lease lending.”  Adds Voronenko: “Boiled down, it’s at the point now where a business that wants to extend credit can do it intelligently, efficiently, and on its own terms. All you need is internet connectivity.”  That’s all great, of course, but how does a business shop for a loan-origination system, or LOS, in the midst of a pandemic?    Best practices for LOS shopping  For Voronenko, like most experts in the field, it comes down to matching needs with options in the marketplace, a process that starts with establishing a basic understanding of the lending space. To help lenders, whether novice or established, succeed in their search for a flexible and reliable LOS, we’ve compiled the following checklist.  Get a good overview. TurnKey Lender recommends that lenders, especially new ones, start getting up to speed on their understanding by visiting online resources, including its own website. Operating on the premise “an informed customer is the best customer,” an LOS’ salesforce is another great resource for prospects looking to match their needs to particular system providers. In addition, user-rating platforms like Capterra and G2 can be great sources of information about particular offerings’ real-world performance.  Every lender is different. Find an LOS provider that understands that. Effective responsiveness requires speed as well as precision. Lenders want digital capabilities they can roll out quickly to support customers in the current crisis and beyond. An LOS provider like TurnKey Lender provides solutions that are configurable for each client firm using flexible flow-building and rules-management tools that makes its time-to-market hyper-competitive.  Increased importance of data security and customer privacy. TurnKey Lender demonstrates its readiness on this front through third-party certifications. The main gauge for best practices in safeguarding the lender’s data and their customers’ peace-of-mind is the Open Web Application Security Project, or OWASP, standard. TurnKey Lender is compliant with this standard, complying with the widely recognized ISO 27001 standard of information security, and the ISO 9001 standard for its quality management. These certifications ensure TurnKey Lender meets or exceeds all statutory and regulatory requirements.  Lenders want a one-stop solution. Banks and other tenured lenders are turning away from siloed solutions for different stages of loan origination and processing, and for different credit products. TurnKey lender is at the forefront of this convergence, with the flexibility and power to support loans of every sort — all on one platform that features consolidated reporting for immediate insight on credit portfolios across product types.  An LOS should equip the lender to compete, even with the big guys. TurnKey Lender is the “Intel Inside” many large- and middle-market lending platforms, through which it has processed millions of loans. These institutions achieve fast and accurate application processing, and superior customer experiences. An LOS provider that knows how big lenders operate can make its clients competitive with established digital lenders on all fronts.  The right LOS will simplify operations, not complicate them. Does your business have the staff and the institutional knowledge to develop, maintain, and manage an advanced lending software platform on site? If not, you may take a cue from many small- to midsize lenders and opt for a cloud-based “lending as a service” model — which is also the choice these days for many large organizations eager to balance cost-savings with data security.   In the current crisis, speed to market is paramount. Because its uses flexible workflow and rules-management tools, an LOS provider like TurnKey Lender can get your lending operation up and running quickly, so you can get to work extending credit where it’s needed most.  As an additional incentive to businesses contemplating the move to e-lending, it’s worth noting that consumers’ online habits seem to have changed in the pandemic, with some assuming the transition will stick.    Lenders, welcome to your digital future  According to an early May 2020 survey of consumers by payments-industry tracker PYMNTS, 26% of generation X who shifted routines to online platforms don’t plan to move back offline once the pandemic is over or under control. Perhaps more impressive, 21.7% of boomers and seniors say the same, as do 23.8% of millennials, and 24.6% of “bridge millennials” (between age 32 and 40).  “The stage was set for an accelerating migration to e-lending before the coronavirus pandemic — as much a function of raw demand as where smart technology is taking us as a society,” says TurnKey Lender’s Voronenko. “But this unfolding event, as tragic and disruptive as it is, has significantly heightened both need and awareness of it. In short, it’s a solution whose time has come.”  Reach out to the TurnKey Lender team today to learn more.

Forbes Council: How To Approach Business Creditworthiness Assessment During A Crisis-Fueled Recession


A new Forbes article by Elena Ionenko, Head of Business Development at TurnKey Lender: It’s not clear whether Congress will trigger an additional round of stimulus to counter the economic effects of the novel coronavirus pandemic; stimulus that has included government-guaranteed lending to businesses. What is clear, according to definitive new findings, is that the US economy was already in recession a month before a contentious and patchwork approach to “social distancing” got going in March. As a result, lenders must reconsider how they assess business-loan applicants’ ability to honor the terms of the loan. Another thing that seems likely is that businesses of all sizes in every state, district, and territory will be looking for loans before and after the stimulus spigot is finally wrenched shut. Many of these enterprises will be seeking help to get them through a recession exacerbated by: ● A contagion that may not have run its course ● The need for ongoing social-distancing measures that can impede business recovery, such as less restaurant seating, and expensive new workplace configurations ● Truncated consumer spending and other recession-related woes ● The usual uncertainty that takes hold in presidential election years In this environment, many lenders will be making credit decisions based on traditional inputs that aren’t adequate to these times. In a macro view, applying old-school analysis to new market conditions could curtail lending and stall economic activity. For lenders, it could mean losing out on opportunities to make well-performing loans. Read the full article on Forbes: How To Approach Business Creditworthiness Assessment During A Crisis-Fueled Recession


Flexible loan application flow

Automated payments and loan servicing

Efficient strategies for all collection phases

AI-based consumer and commercial credit scoring

Use third-party data and tools you love.

Consumer lending automation done right

Build a B2B lending process that works for you

Offer payment options to clients in-house

Lending automation software banks can rely on


Thank you! Get in touch with any questions at [email protected]