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Industry: Loans

On-Demand: How Consumer Lenders Can Reduce Friction Without Compromising on Risk and Fraud Prevention

ON-DEMAND WEBINAR

How Consumer Lenders Can Reduce Friction
Without Compromising on Risk and Fraud Prevention

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Customer experience is incredibly important to today’s discerning consumers, whether they are looking for financial services or any other product. Reducing friction at onboarding and across the entire customer journey is critical for consumer lenders – but how can you do that without compromising your risk strategy or increasing your risk of fraud? Watch on-demand now, and hear from our panel of experts who share insights and best practices for reducing friction, so you can effectively balance risk with opportunity – and grow your business.

Key highlights include:

  • How advanced risk decisioning solutions can more effectively enable end-to-end account management
  • Why orchestrating and integrating the right data, including alternative data, is key to making more accurate decisions across the lifecycle
  • How a decision intelligence platfrom, including AI/ML, can help mitigate losses, improve fraud decisioning, and maximize portfolio performance
  • Ways to ensure frictionless, end-to-end onboarding experiences with expedited case handling for manual exceptions
  • Why dynamic, proactive customer management is key to maximizing customer value and optimizing engagement

Speakers:

  • Rob Seidman

    US Bank Chief Product Officer
  • Adam Goller

    Cross River Bank
  • John Lynch

    Avant
  • Michael Fife

    Provenir
  • Peter Renton

    Fintech Nexus

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Lending to Live: Navigating the Cost of Living Crisis for Lenders in the UK

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Lending to Live:
Navigating the Cost of Living Crisis for Lenders in the UK

  • Allison Karavos

In the wake of the ever-growing concern surrounding cost of living in the UK, consumers are finding themselves at the heart of financial turbulence, grappling to maintain stability and meet basic needs. As prices for essential goods and services continue to rise, consumers are finding it increasingly difficult to make ends meet, presenting not only a challenge but also an opportunity for lenders and credit providers to play a pivotal role in supporting these consumers, especially the underserved segments of society. 

In this transformative landscape, AI-powered, data-driven decisioning platforms can play a pivotal role in reshaping lending practices to be more responsive, inclusive, and empathetic.

Understanding the Cost of Living Crisis

Recent statistics paint a sobering picture: as of early 2024, inflation rates have soared, significantly impacting the prices of food, energy, and housing. This has resulted in a notable increase in the cost of living, outpacing wage growth and putting immense financial pressure on many households. For instance, the Consumer Prices Index (CPI) rose by 4% in the 12 months to January 2024. The cost-of-living crisis in the UK is not just a financial challenge; it is a daily struggle for individuals and families trying to navigate rising expenses, stagnant incomes, and economic uncertainties. From housing to healthcare, education to groceries, every aspect of life is impacted, putting immense pressure on consumers to make ends meet.

The Consumer-Centric Approach

In challenging times, the consumer must be at the forefront of any meaningful solution. Lenders need to reevaluate their approach and recognize the importance of a consumer-centric strategy. This involves understanding the unique financial situations of borrowers, acknowledging their challenges, and tailoring lending solutions that genuinely support their needs. And it’s not just about short-term solutions, but about offering support and solutions that go beyond traditional lending models, focusing on long-term financial well-being and stability.

Adapting to Evolving Consumer Needs: Leveraging AI and Data-Driven Decisioning

The ability to adapt quickly to changing circumstances is crucial in addressing the cost-of-living crisis. One of the most powerful tools at the disposal of lenders in addressing the cost-of-living crisis is technology, specifically AI and data-driven decisioning. 

A data-driven, decision intelligence platform enables lenders to assess and respond to evolving consumer needs in real-time, ensuring lending institutions can remain agile and responsive. 

More specifically, these technologies help lenders:

  • Better Understand Consumer Needs: By analyzing data patterns and consumer behavior, lenders can gain insights into the financial challenges that different segments of the population are facing.

  • Personalise Financial Solutions: AI can help tailor financial products and services to meet the specific needs of individual consumers, providing more relevant and effective support.

  • Improve Risk Assessment: Enhanced data analytics can lead to more accurate risk assessments, allowing lenders to offer credit to a broader range of consumers, including those who might be underserved by traditional credit scoring models.

  • Offer Proactive Financial Guidance: AI-driven tools can provide consumers with proactive and personalized financial advice, helping them manage their finances more effectively in tough economic times.

Supporting the Underserved

One of the key challenges in the lending industry is reaching and supporting underserved communities. A data-driven approach helps bridge this gap by enabling lenders to evaluate risk more accurately, extending financial support to those who might be overlooked by traditional lending methods. This inclusivity is not just a strategic advantage but a social responsibility that aligns with the urgent need for financial equity.

With the right data at the right time, lenders can support underserved groups by:

  • Developing products and services tailored to their specific needs

  • Using alternative data in credit decisioning to include those with thin credit files

  • Providing financial education and guidance to help them manage their finances

Looking Ahead: A Compassionate Future of Lending in the UK

Looking ahead, the lending industry in the UK is expected to undergo significant changes. We can anticipate a greater emphasis on responsible lending, with a focus on sustainability and long-term financial health. Technology, particularly AI and machine learning, will continue to play a critical role in shaping the future of lending. These advancements will enable lenders to offer more personalised and flexible financial solutions, making finance more accessible and inclusive.

In conclusion, the cost-of-living crisis in the UK presents both a challenge and an opportunity for lenders and credit providers. By adopting a consumer-centric approach and leveraging technology, they can not only support consumers through these difficult times but also pave the way for a more inclusive and sustainable future in lending. Lenders must evolve to meet the pressing needs of consumers. As we navigate these challenging times, the integration of technology and empathy will undoubtedly shape a future where lending serves not just the financial well-being of individuals but the resilience of the region as a whole.

Looking for more info on how a holistic, AI-powered decisioning platform can help evolve your lending strategy?

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FCA’s Consumer Duty Comes into Force: What Should Lenders Expect?

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FCA’s Consumer Duty Comes into Force:
What Should Lenders Expect?

The Financial Conduct Authority’s Consumer Duty has come into force, requiring firms to be open and honest, avoid harm, and support consumers to pursue their financial goals. The new rules for financial services firms in the United Kingdom set a higher standard of consumer protection, including better support, communications, as well as products and services that meet consumers’ needs and offer fair value.

The Finance Feeds tapped two industry experts from Provenir – Chris Kneen, Managing Director, UK & Ireland, and Frode Berg, Managing Director, Europe – for their insights on this regulatory milestone.

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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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Myths vs reality in upgrading your credit decisioning technology

Myths vs Reality in Upgrading Your Credit Decisioning Technology

Powering Up: How Banks Can Leverage Automated Credit Risk Decisioning for More Agility and Speed

Financial institutions are under pressure, and banks are feeling the heat. Consumers are even more resistant to friction in their customer experience journeys, whether they are buying appliances, vacations, vehicles, or applying for credit. So how can banks focus on growth and meeting consumer needs and expectations, while still managing risk effectively? In many cases, it means it’s time to look at your data and decisioning technology. 

Upgrading your credit risk decisioning technology sounds daunting. But we’re here to talk about some of the myths that persist around upgrading your tech – and the reality counterpoint. 

Myth #1:
Traditional Credit Data is Good Enough

Reality:
Traditional credit data is rarely enough to paint an accurate, holistic picture of a customers’ creditworthiness. Alternative data sources, including mobile/telco info, rent and utilities data, social media/web presence, and open banking info can help you gain a more comprehensive view of a potential customers’ financial health as well as their ability and willingness to pay.

The Data Challenge:
There is a ton of data out there, and it can often reside in siloed environments, making it difficult to access and costly to integrate into your decisioning. On top of that, it can be easy to assume that more data is the answer. But it’s not always what you need. The key to optimizing your data strategy is not necessarily more data but having the right data at the right time. According to IDC, in 2022“over one hundred thousand exabytes of data will [have been] generated, crossing the 100k threshold for the first time.” Yet 74% of decision-makers we surveyed said they struggle with their organization’s credit risk strategy because data is not easily accessible, and 70% say alternative data is not easily integrated into their current decisioning system. The use of alternative data to supplement traditional credit data (primarily bureau data) is critical to not only giving you a more accurate, real-time view of your customers’ creditworthiness, but it also expands your lendable market. By being more inclusive and saying yes to individuals who may have lower traditional credit scores, you’re improving financial inclusion and ensuring greater access to financial services andgrowing your business at the same time.

Myth #2:
It’s Too Costly to Upgrade Your Decisioning Tech

Reality:
It can be easy to assume that changing your decisioning tech will involve a massive amount of upfront investment (not to mention the fear of ‘wasting’ previous investments in your legacy tech). But can you afford not to upgrade? And keep in mind additional cost savings realized with self-sufficiency when changing your decisioning workflows and launching new products.

The Cost Challenge:
Cost pressures are everywhere. So it’s not surprising that sometimes banks are reluctant to consider changing technology platforms. With the hours of time and monetary investments made in implementing decisioning infrastructure, it can seem wasteful to transition away from legacy systems. But it’s important not to let the fear of past investments hold you back. Because with increased competition, demanding consumer expectations, and a shifting regulatory environment, having next generation decisioning tech is key. The cost of doing nothing will catch up to you – acquiring new customers, keeping your existing customers, preventing fraud, satisfying compliance requirements… non-action is a non-option. Upgrading your decisioning tech results in a lower total cost of ownership, thanks to eliminating product launch and iteration delays that lose you customers, the ability to automate risk decisioning workflows for more efficient processes, and improved fraud detection/prevention.

Myth #3:
It’s Too Difficult to Overhaul our Current Systems

Reality:
It’s not an all-or-nothing situation. Look for decisioning solutions that can run in parallel to your current software, or for ways to orchestrate your data more efficiently with a data ecosystem. This can create buy-in with other departments and lines of business when they see the improved efficiency and the way upgraded tech improves the overall decisioning process.

The Difficulty Challenge:
We’ve talked about the cost aspect of upgrading, which sounds daunting, but it’s about more than just money. Many people-hours are often put into choosing and implementing decisioning platforms – so why opt to do it all over again? Because the long-term benefits are worth it, and it may not be as difficult as it sounds. Rarely do you need to rip and replace all of your decisioning tech in one go. There are more flexible, agile decisioning platforms available that can integrate into or run alongside your existing workflows or you can choose to upgrade one line of business at a time. The key is choosing a technology platform that makes this easy and has experience with swapping out competitive decisioning platforms. (Provenir for example has vast amounts of experience replacing legacy, competitive decisioning systems, and can get you up and running, fast – however large the implementation may be).

How to Run the Smarter Race

One of the most common challenges banks are currently facing is competition – and the subsequent need to power risk decisions faster in order to keep up. But the key is to do this without sacrificing your risk strategy. It is possible to become more agile and self-sufficient, which allows you to make faster, more accurate risk decisions and launch new products in less than half the time – and one of the best ways to do this is upgrading to next-generation decisioning technology. Look for a partner that can offer you these key elements:

Real-time data access to hundreds of data sources through a single API

  • Advanced analytics based on your unique risk profiles
  • Integrated case management for a complete end-to-end perspective on credit applications
  • The ability to handle evolving compliance regulations and security demands
  • Low-code, business-user-friendly UI that enables self-sufficiency when changing processes and iterating workflows
  • Experience with swapping out legacy technology/competitive decisioning platforms to ensure a seamless transition
Leveraging automated, integrated data and more agile risk decisioning technology can help you increase your flexibility, accuracy, and speed. With the right tools on hand, you can keep up with new entrants in the market and also meet regulatory compliance requirements, all while making more informed credit decisions that improve the customer experience – and do it faster than the competition. Because in the race for customers… speed is everything.
Ready to improve your agility and run the smarter race?
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Digital Loan Origination in Banking: Competing with Challenger Banks

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Digital Loan Origination in Banking:
Competing with Challenger Banks

The financial industry has seen a dramatic shift in recent years with the rise of challenger banks. These digital-first establishments have emerged as serious competition to traditional banks, offering more personalized and innovative services that resonate with consumers. To compete with these new players, traditional banks must improve their digital capabilities and offer more streamlined services that provide customers with a better experience.

One area where banks can focus their efforts is digital loan origination. By automating this process and integrating it into their digital platforms, banks can provide customers with faster, more efficient loan processing. This is a crucial component in building a more competitive and innovative financial institution.

Digital loan origination allows banks to gather customer information and evaluate creditworthiness quickly and accurately. By leveraging data analytics and machine learning, banks can make better lending decisions while reducing the risk of defaults. This technology also makes it possible to offer more personalized loan products, which can increase customer satisfaction and loyalty.

Traditional banks can compete by improving their digital capabilities, and digital loan origination is a key area where they can focus their efforts. By automating loan processing and leveraging data analytics and machine learning, banks can make better lending decisions and provide customers with a better experience.

The End of the Level Playing Field

After the 2009 financial crisis, trust in traditional financial institutions took a hard hit with up to 80-90% of the public viewing them as untrustworthy, according to past studies. This led to an opportunity for challenger banks to enter the market with a clean slate and build their brand without the negative sentiment experienced by traditional banks.

Challenger banks also had a technological advantage over their established counterparts. Without the burden of legacy IT systems, challenger banks were able to adopt modern technology and offer digital services with greater efficiency and agility. As a result, challenger banks are quickly gaining ground, and the traditional banks are being forced to adapt or risk being left behind.

Challenger Banks: Reshaping the Future of Banking?

As the banking industry undergoes a transformation, many experts suggest that Challenger Banks will play a significant role in shaping the future of banking and money, despite the challenges that come with innovation. Unlike traditional banks, Challenger Banks tend to embrace a start-up mentality, leveraging a minimum viable product (MVP) approach to continually refine their product portfolio until they achieve the optimal balance.

While larger banks may struggle with operating in product silos and stretching their resources too thinly, Challenger Banks can prioritize quality and customer experience, giving them a competitive edge. But how can traditional banks compete with these innovative newcomers who are leveraging cutting-edge technology and a hyper-focus on innovative products and services?

Also, read: What is Banking as a Service?

Building Consumer Trust in Banking

Traditional financial institutions may have struggled with their reputations post financial crises, but a 2019 survey by Accenture showed extremely positive results for banks when it came to customer trust:

  • An average of 77.75% of consumers (across all persona groups) trust banks to care for their long-term financial wellbeing

Results were not so strong for non-traditional financial institutions:

  • Only 35.5% of consumers (across all persona groups) trust non-traditional institutions to care for their long-term financial wellbeing

So, while banks may be lagging behind when it comes to technology, they still outperform fintechs and challenger banks when it comes to consumer trust. Financial institutions trying to compete with their challenger competition should bank on the inherent trust that consumers still hold for brick and mortar institutions as a foundation to secure long-term loyalty with customers. Is this an obvious point to make?

Absolutely. But it’s how this trust can be used to build stronger bonds and expand product offerings that offers a huge opportunity for traditional financial institutions.

Dealing with Data: Customer Trust Expands Opportunities

In a time when data breaches are common, billions of records were stolen in 2018 alone, consumers are on high alert when it comes to sharing their information.

So perhaps one of the most fascinating results of Accenture’s study is that customer trust in traditional financial institutions extends to trusting banks to keep their data secure. 80% of consumers surveyed trusted their banks enough to share additional data to receive more relevant offers.

This gives banks an incredible opportunity to create truly personalized services using data gleaned directly from customers. But banks can go further, with many consumers sticking with the same financial institution for many years, banks have been gathering an immense amount of data on customers that can be used to personalize and pre-approve offers for individuals.

Wouldn’t it be nice if your customer’s felt like you truly understood their needs by offering the right products at the right times?

As a bank there’s a lot that can be learned from how challenger banks have approached disrupting the industry. Let’s consider a standard financial category that you may offer, and how the use of technology and data can improve that experience for your customers.

Mobile Loan Origination

Customers have an increasingly strong preference for the loan origination process to be mobile-friendly and fast.

  • Accenture found that on average 81% of consumers would share more information to get faster services and approvals

Challenger banks have greatly improved the loan origination process for consumers. They’ve removed the once long, paper-filled process and made approvals almost instant – all the while accepting nothing less than improved compliance and mitigated risk.

The smart pairing of data access and automation powers much of this process. And, while the idea of a loan being commenced and approved during an afternoon at work would be laughable 20-30 years ago, now it’s expected.

Offering this type of capability can seem daunting for both a startup with 25 employees and traditional banks, but launching a mobile or web app that can collect your customer’s application details, integrates with your systems and third-party data sources, decisions that loan, and provides an approval instantly is only a matter of starting with the right technology.

Building Data into Your Loan Origination Process: Using Data to Level the Playing Field

A common challenge banks face is being able to access, orchestrate, and use data. To get the most out of their historical data and gain access to new data, banks need to find a way to draw their data into one location as a foundation for decisioning and customer personalization.

Connecting disparate systems and data silos can provide banks with a huge advantage over their competitors as they’re able to gain much deeper insights into their customers and more easily assess associated risk. But legacy technology makes this almost impossible in many organizations.

To solve these issues, banks need to look for a solution that allows them to create a decisioning ecosystem. Technology that connects the dots between their CRM, historical data, new customer data, and their loan origination processes.

It’s only by using data to predict customer needs, pre-approve products, and personalize offerings that banks will compete with the challenger banks nipping at their heels. And, if banks can match this personalization across both physical and digital channels, banks could well disrupt the disrupters!

“Our entire approach is built on simplifying banking. One of the ways we do this is by making the customer experience fast and effortless; from the initial on-boarding process through to every subsequent interaction. The Provenir Platform gives us speed and flexibility in our lending operations, which enables a customer to apply for a loan at lunchtime, receive immediate approval, and have the money available in their account later that day.”

– CEO, Instabank

How Challenger Banks Are Capturing Customers’ Hearts (And Wallets)

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The Canadian Lending Market in 2023: Embracing Economic Uncertainty and Mitigating Risk Through Advanced Technology

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The Canadian Lending Market in 2023:
Embracing Economic Uncertainty and Mitigating Risk Through Advanced Technology

Economic uncertainty has a noticeable impact on the way financial institutions make decisions and offer products and services to their customers. While consumers may pull back on discretionary spending, on the flipside, they also require more access to credit – which financial institutions may be reluctant to give, due to more conservative risk appetites.

In this Fintech.ca article, Cheryl Woodburn, Country Manager of Canada for Provenir, shares advice on how alternative data and innovative decisioning ecosystems can help financial institutions gain more accurate insights to support their clients.

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EV Exclusive NBFC AMU Leasing Onboards Provenir’s Decisioning Platform to Accelerate Loan Decisions

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EV Exclusive
NBFC AMU Leasing Onboards Provenir’s Decisioning Platform to Accelerate Loan Decisions

With Provenir, AMU Leasing will be able to disburse loans to its end users with speed, accuracy and precision

New Delhi, India – Provenir, a global leader in AI-powered risk decisioning software, announced today that AMU Leasing, India’s leading and only woman-led, tech-driven NBFC startup exclusively serving the Electric Vehicle ecosystem. With this partnership, the Delhi-based company will be able to make faster decisions and offers to end-users, putting it ahead of its competition.

AMU Leasing’s goal is to support India’s emerging initiatives for self-employment and micro entrepreneurship for citizens across Tier 2 and 3 cities. By supporting the alternate fuel-based transportation sector, they plan to propel and sustain revenue generation for self-employed livelihoods.

The government of India is targeting EV sales to account for 30 percent of private cars, 70 percent of commercial vehicles, 40 percent of buses and 80 percent of two and three-wheelers by 2030 to help reduce carbon emissions. The combination of AMU Leasing and Provenir is ideal for new as well as existing customers seeking EV financing solutions with seamless processing and a world-class user experience.

“We are focused on helping develop an efficient ecosystem where leasing, financing and purchasing electric vehicles is one seamless process,” said Nehal Gupta, CEO of AMU Leasing. “We needed an automated decisioning solution that would enable us to make faster decisions and extend offers to end users. Provenir’s low code interface empowers our business users to easily design, build and test decisioning models themselves. The Provenir Marketplace also provides access and easy integration to new data sources, providing us with greater insights to make more accurate decisions.”

“The EV market is quickly growing and AMU Leasing is well positioned to support the entire value chain, particularly entrepreneurial businesses,” said Varun Bhalla, Country Manager, India for Provenir. “Our AI-Powered Data and Decisioning Platform provides the access to data, AI and decisioning capabilities needed to accelerate and improve their lending decisions and expand with them. We look forward to helping them meet their goal of one million EV disbursements by 2027.”

Provenir’s industry-leading AI-Powered Data and Decisioning Platform delivers smarter risk decisioning. The solution, managed through a single UI, empowers organizations to innovate further and faster than ever before, driving the continuous optimization they need to power growth and agility, without increasing risk.

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Payday Loan vs. Unarranged Overdraft: Which is More Expensive?

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Payday Loan vs. Unarranged Overdraft:
Which is More Expensive?

When it comes to borrowing money, people often think of payday loans as a costly option due to high-interest rates and fees. However, according to consumer group Which?, dipping into an unarranged overdraft can be more expensive than a payday loan.

In this no-nonsense guide, we will explore the differences between payday loans and unarranged overdrafts, including the pros and cons of each option.

Payday Loans

A payday loan is a short-term loan typically used to cover unexpected expenses or emergencies. Here are some key points to keep in mind:

Pros:

  • Quick access to cash
  • Easy to apply for
  • Fixed fees

Cons:

  • High-interest rates
  • Short repayment periods
  • Can lead to a cycle of debt if not managed properly

Unarranged Overdrafts

An unarranged overdraft is when you spend more money than you have in your bank account and don’t have an agreed-upon overdraft limit in place. Here are some things to consider:

Pros:

  • Quick access to cash
  • No need for pre-approval
  • Can cover unexpected expenses

Cons:

  • High fees and interest rates
  • Can lead to a cycle of debt if not managed properly
  • No cap on charges, can be more expensive than a payday loan

Comparing Costs

As mentioned earlier, the charge for a £100 payday loan over 28 days has been capped at £22.40 since January 2015. In contrast, going overdrawn on an unarranged overdraft for the same amount and period can cost up to £90.

While banks do offer loan services, including arranged overdrafts, these options may not be accessible to everyone. Many customers go overdrawn when they cannot get arranged borrowing or during a short-term cash flow situation. The Financial Conduct Authority introduced the cap on payday loans to protect these borrowers, but there is no similar cap on unarranged bank overdrafts.

Payday loans are often viewed as a costly way to borrow money, an unarranged overdraft can be even more expensive. It’s essential to understand the pros and cons of both options and ensure you are aware of all fees and charges before making a decision.

When considering borrowing money, always evaluate your options carefully, and only take out a loan or overdraft if you can afford to repay it on time. With the right approach, borrowing can be a useful tool to help manage short-term financial difficulties.

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The History of Lending

INFOGRAPHIC

The History
of Lending

Technology and the Democratization of Lending

Did you know that the earliest form of Buy Now, Pay Later dates back to the 19th century, when consumers were able to purchase expensive goods (like furniture and farm equipment) on installment plans? While modern lending is often thought of as, well, modern, some of the technologies that impact our current financial services landscape have much older roots. Check out the infographic for some interesting factoids on the history of lending, the rise of modern technology, and just how far we’ve come in the world of lending.

The Ultimate Guide to Decision Engines

What is a decision engine and how does it help your business processes?

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