Are you offering financial products to your customers? Do you want to verify identity quicker, detect fraud earlier, and make more accurate credit decisions? Introducing Provenir Data, offering simplified data access, fully maintained integrations, and one single API.
Discover how the right data at the right time can power more accurate decisions across identity, credit and fraud, covering everything from SME lending and auto financing, to BNPL, credit cards, telco, mortgages and more.
Addressing financial inclusion is a priority for many fintechs and financial services providers.
Today, up to one-third of all adults globally lack any type of bank account, making it difficult to evaluate creditworthiness using traditional methods. This large population of unbanked individuals represents significant growth for innovative organizations.
A major issue hindering access to credit lies in the limited types of traditional data typically used in credit scoring and risk profiles. To make financial services available to the unbanked and underbanked population, alternative data provides new insights to support credit decisions while also detecting fraud.
How can fintechs and financial services providers begin this journey to remove barriers to financial inclusion and expand their potential audiences? By pioneering accessible data and open APIs to provide credit decisions and prevent identity fraud in fast, instantaneous actions, banks can begin to lift the unbanked out of financial exclusion.
Join our panel of industry experts as they discuss the following areas:
How does the current approach to determining risk profiles impact the unbanked population?
What steps can financial institutions and fintechs take to be more financially inclusive and expand their addressable market?
What is the role of data in expanding financial inclusivity.
How can other forms of financial technology be used to open opportunities for consumers with growing portfolios?
It’s been a few months since the FCA’s Dear CEO letter, outlining their concerns with the rising cost of living. As it predicted, inflation is impacting household budgets resulting in an increased demand for credit.
Vulnerable customers are set to be hit the hardest. More of the UK population are also predicted to display characteristics of vulnerability over the coming months.
The upcoming Consumer Duty is intended to raise the bar to address the FCAs growing concern lenders may not be doing enough. One thing for sure is that traditional data sources don’t have all the answers – lenders need to understand their customers’ real-time financial position to predict future risk and put the customer at the centre of their business.
Leaders in the credit data space, DirectID and Provenir co-host this webinar with guest pannellist Jo Pearson from NewDay discussing the changing pressures on consumers. They explore and share knowledge on the alternative data sources available across the credit life cycle that lenders need to produce better customer outcomes.
How to Simplify Your Data Strategy for Smarter Decisioning
Do you struggle with your organization’s data strategy? Do you have access to the data you need to make smarter decisions? With the right technology, you can overcome any data challenge to reduce risk and grow your business.
Access any data, anywhere, on-demand through one API – read the infographic to learn how.
On-Demand Webinar
Data Your Way – Streamlining Your Data Strategy with Provenir Data
Why the right data, not more data, is key to optimizing your data strategy
Big data and the term ‘data strategy’ gets thrown around a lot – but what is a data strategy when it comes to financial services, and how can you optimize it for more accurate, smarter risk decisioning? The answer isn’t more data, it’s the right data. Read on and discover how to choose the right data for your business use case and why optimizing your data strategy is key to your decisioning success.
Make Your Data Work Smarter, Not Harder
In our increasingly digital society, it seems like everyone is focused on more. More data, more choice, more speed, more competition, more options (how many different entertainment streaming services are there now??). More, more, more. So, our rebel yell is that when it comes to your data strategy, it’s not about more data, it’s about the right data, at the right time. According to IDC, “this year alone, over one hundred thousand exabytes of data will be 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. The data is there, but it’s an incredible amount of wasted effort if you don’t know which data sources to use when.
74% of decision-makers struggle with their organization’s credit risk strategy because data is not easily accessible.
Improved customer experience: Ensure a frictionless digital experience for low-risk customers and enable data-driven actions on potential risk in real-time
Improved accuracy in your decisioning: The right data at the right steps in your decisioning processes across the customer lifecycle means more efficient, accurate risk decisions
Minimized data costs: Reduce the time/effort/resources necessary to source, build and maintain data integrations if all the data you need is right at your fingertips
Scalability:With the right data sources on both a local and global level, you can get new products to market in new regions faster by duplicating and iterating your data strategy
Types of data that are critical to optimizing your decisioning strategy across the lifecycle:
Identity Data: Verify identities and documents for better onboarding compliance, prevent identity fraud, and be sure that you are protected with ongoing due diligence data.
Includes: KYC/KYB, PEPs/sanctions, document verification, synthetic ID fraud
Fraud Data: Identify potential first-party and application fraud in real-time to proactively detect/prevent fraud and reduce losses; reduce false positives by leveraging signals from mobile, email, behavior, device, IP, social and other fraud data sources.
Includes: Email and mobile data, global fraud intelligence, social validation, device data, IP, and geolocation
Credit Data: Minimize credit exposure and loss by leveraging credit bureau, open banking, and alternative data sources. Ensure optimized credit onboarding and add value throughout the entire customer lifecycle with dynamic customer risk profiling, mitigate collections and optimize customer lifetime value.
Includes: Credit bureau data, business data, open banking and alternative data including social media, rental payments, travel info, utilities and more
Data supply chain challenges and how to overcome them
Choosing the right data can seem daunting, but it’s critical to have an optimized data supply chain, with the right data in the right place, in order to deliver the most effective products to your customers. And depending on the type of financial product you are offering there are regional regulations to consider, third-party vendors required, technology requirements and more. These are some of the most typical challenges known to slow down deployment of even the most well-thought-out data strategies:
Identifying relevant local data sources
Negotiating multiple contracts
Complying with varying regulations
Ensuring data privacy for different regional requirements
Normalizing data formats
Building and maintaining integrations
Supporting global strategies
But you can overcome these challenges by ensuring you have the right data for each and every product offering you have. How? Work with a partner that provides an all-in-one data solution. Building your own data supply chain, for whatever your use case, is possible of course, but it’s time-consuming and resource intensive. If you want to work with a partner look for a data solution that offers:
One data contract that provides access to multiple data sources
A single API to replace numerous integrations
A wide variety of data types and sources, including alternative data
Expert data source curation customized to your needs, that can be easily modified as your needs evolve
Simplified, no-code data supply chains that non-technical users can understand and control
Global data access, as well as local sources, to ensure success of both regional tactics and the ability to iterate and expand to new markets
Seamless integration into your decisioning technology to ensure accurate, smarter decisions
If you’re a Buy Now, Pay Later provider, or are thinking of diving into the fray, check out our blog highlighting specific ways to optimize your data supply chain for BNPL.
Simplifying your data supply chains (sourcing, building, integrating, and maintaining data sources and connections) and optimizing your data strategy is critical to continued success – and your competitive advantage. Don’t let yourself be overwhelmed by the immense variety of data available out there – remember, the right data is much more important than more data. Accessing the right data at the right time means enhanced risk models, strengthened onboarding processes, more accurate decisioning across the lifecycle, and optimized customer experiences.
For further reading, check out these articles that may be of interest:
What the Data-Driven Bank of the Future Looks Like
The Benefits of Unified Access to AI-Powered Decisioning & Data
How to Get Smarter With Your Decisioning Technology
How can you get smarter with your risk decisioning? Look for an all-in-one solution that functions like a smart home – one centralized platform that allows you to manage and control it all: data, AI models and decisioning.
Browse the infographic below for more info on the benefits of unified access to AI-powered decisioning and data.
Data Now, Fewer Losses Later: Optimize Your BNPL Data Strategy
Buy Now, Pay Later (BNPL) products have exploded across the globe, offering a new spin to point-of-sale (POS) financing for both consumers and businesses. From 2019 to 2021, BNPL loan originationsincreased by 970%from the top five lenders alone, and the industry continues to expand to include new verticals such as auto repair, grocery purchases, airline ticketing, and more. Consumers are beginning to rely on BNPL for everyday costs in order to help manage their cash flow. But none of this would be possible without data – more specifically, a strong data supply chain.
If you’re a BNPL provider, the data supply chain is the powerhouse for your solution. When you have the right data, you can better determine risk, protecting your business against fraud and loan default.
BNPL data strategies look beyond traditional data like credit scores and use alternative data to make credit more accessible and faster to approve without increasing your risk. While this allows you to expand your customer base in a secure way it also adds complexity to your data needs. So, how do you build a BNPL data supply chain strategy that gets the right data to the right place exactly when you need it?
Building Your BNPL Data Supply Chain
We know every potential BNPL customer must go through a process, but what does that process look like? Each step is built with different data checks that tell your decisioning engine whether to move that customer forward. An optimized data supply chain pulls only the necessary data needed for a customer at each checkpoint – data that comes from your data integrations and data partners.
An optimized data supply chain has these hallmarks:
Multiple steps with distinct requirements
Multiple checkpoints at which consumers either pass or get denied
Steps that increase in complexity and cost of data
No unnecessary data is exposed and paid for before you need it
Launching with an MVP:
Are you a startup launching your first BNPL solution? A finserv expanding your product line? Maybe you’re an online shop looking to reach more customers. Whatever the case, when building a new data supply chain for your BNPL offering or optimizing an existing one, you should begin with your minimum viable product (MVP) – the basics you know you need to launch your product.
An MVP has the least amount of checks in the process, pulling in the least amount of data. You might want to begin with an MVP if you want to:
Go to market quickly
Minimize the cost of development
Analyze basic performance to optimize more complex iterations in the future
To launch with an MVP approach you’re going to need data to support three key areas:
Regulatory compliance checks like KYC/AML
Identity verification
Credit risk
An MVP for consumer lending could look like this:
Step 1: KYC
The first step of the process is validating the most basic data to confirm the customer’s age, address, and identification. If you can’t verify a person’s ID, you certainly can’t lend to them.
Step 2: Fraud Prevention
The second step digs deeper into a person’s identity to ensure they are who they say they are and help prevent fraud. There is a wide variety of data you can pull for a fraud check, including email address verification, if a SIM card has been swapped, and other behavioral and alternative data. If not all of this information matches, it could be a sign of attempted fraud, and the person would be rejected.
Step 3: Credit Risk
The final step is to check creditworthiness. A bureau check is done through a soft credit check that grants you access to a consumer’s credit score without impacting it. With an MVP, BNPL providers would likely reject anyone with a score below a certain threshold or someone without enough credit history to have a score at all. If a person has made it through the process, the data is assessed holistically by a decisioning engine to determine whether and at what terms to grant the loan.
Beyond the MVP: Optimizing Your Data Strategy
Beyond the foundation needed for an MVP launch, you can optimize your supply chain based on your company’s risk appetite and goals. Before updating your data supply chain it will help to:
Analyze success against your goals
Identify weak points in your data strategy
While you may want to initially launch your BNPL solution using an MVP, as you grow and want to add complexity, you can incorporate new data points and data partners. Think about the kind of customer you want to capture, as well as business goals and preventative measures you may want to take, and ask yourself:
What percentage of fraudulent applications is our current process letting through? Is this in line with our business goals? If not, look to:
Add additional fraud checks on existing steps
Add standalone fraud prevention steps to the process
Amend data sources to optimize as you go
Are we offering the most competitive terms to our customers? How can we improve conversions? For competitive edge and increased personalization, use data such as:
Behavioral trends
Geolocation
Activity and usage
How effectively are we reducing defaults? Are we filtering out non-viable customers at the right point in the process? Make sure your flow features:
Prescreening
Scoring
Additional data checkpoints on existing steps
For BNPL providers that want robust data supply chains across credit, identity, and fraud while maximizing efficiency, an optimized flow could look like this:
Prescreening
Prescreening breaks down the identification verification steps even further, making sure the minimum requirements are met. It’s a faster, more efficient way to filter out unqualified applicants without using unnecessary time and resources.
What does prescreening look like in an optimized supply chain? Say you have a person under 18 – they’re not legally allowed to take out a loan, so their application would be rejected. In an MVP, someone that can’t even use the product would still have their identity verified, but it’s a waste to run those checks, since they’re not a viable customer. Optimization ensures you expose only the data you need at each step.
Scoring
Scoring pulls supplementary data that helps paint a clearer picture of a consumer’s risk. This includes mobile device data, additional fraud checks, or any other kind of alternative data you want to feed into your decisioning tech.
Why include scoring in your process? Again, it comes down to building your process for optimal efficiency and minimal cost. At this point, you would know if the customer was viable, who they are, and what their financials look like – this is all straightforward data to pull. Scoring adds behavioral information that is more time-consuming and costly to analyze and should be incorporated only when everything else checks out.
Ultimately, the more relevant data you have, the more accurate your decisions will be, the better you can predict future defaults, the easier it will be to identify upsell and cross-sell opportunities – whatever your business goals, the right data can help you get there. Optimizing your consumer BNPL supply data chain is dependent on finding the ideal number of checks and steps to accurately determine creditworthiness and risk, while keeping the process fast and efficient.
Ready to launch and expand your BNPL products? Look out for these data supply chain challenges
As BNPL products continue to grow around the world, new markets have emerged, and with them new challenges. To build a global supply chain, you have to know regional regulations, vendors, tech requirements, and more. Some of the challenges that can slow down deployment of your data strategy include:
Identifying relevant local data sources
Negotiating multiple contracts
Complying with varying regulations
Ensuring data privacy for different regional requirements
Normalizing data formats
Building and maintaining integrations
Supporting global strategies
BNPL is a fast-moving industry, so it’s also important to ensure your supply chain can be easily iterated on to incorporate evolving legislation and market demand.
Data Powers BNPL
Regardless of trend, customer type, or region, your BNPL solution is powered by data. Diverse data sources pulled at the right time in the right order is the calling card of an optimized data supply chain. And an optimized data supply chain feeds your decisioning engine the information necessary to give you a smarter decision every time.
Building a data supply chain on your own, however, can be a huge undertaking and an even bigger headache. Instead, consider choosing a data partner that can build it for you, while connecting you to the integrations you need to grow your BNPL business.
Ideal features include:
One data contract that gives you access to multiple data sources
A single API to replace numerous integrations
A wide variety of data types and sources, including alternative data
Expert data source curation customized to your needs
Simplified, no-code data supply chains that non-technical users can control
Global data access
Integrates into your decisioning technology to ensure seamless and smarter decisions
Do you want your data on-demand? Meet Provenir Data.
Life in 3D: Using Alternative Data to Power Credit Risk Decisioning
How to Grow Your Business and Improve Decisioning Accuracy
We see the world in 3D – and we should view credit risk the same way. As a lender, you’re often forced to determine credit risk using only a traditional credit score. But that leaves your perspective lacking.
Read our definitive guide and discover how using alternative data can enable you to:
Create a more agile approach to your credit decisioning process
Say yes to more customers, including those who are thin-filed or unbanked
Improve your decisioning accuracy and offer more cross-sell/upsell opportunities
Make Smarter Decisions Faster with a Risk Decisioning Ecosystem
In today’s digital-first world you know that you need to make smarter decisions that keep you ahead of risks without sacrificing your industry-leading consumer experience. You also know that saying ‘yes’ to the right people in real-time takes more than a simple decisioning tool.
To innovate, thrive, and disrupt in an increasingly competitive market you need to be able to get to market quickly, learn from your data, and iterate—all on your timeline. You need technology that empowers you to create a risk decisioning ecosystem where data, decisioning, and analytics all work together to drive business growth and agility.
Introducing the Provenir AI-Powered Risk Decisioning Platform
In our latest eBook we explore the technology that you need to supercharge your decisioning and how combining these tech features into one cohesive ecosystem will set you apart from your competitors.
Download the eBook now to learn:
how simplified integration and access to data on-demand from 600+ sources, including credit risk, fraud, open banking and alternative data, makes your risk decisioning more accurate
why a single UI with no-code UX is vital to business agility and speed to market
how real-time views of decisioning, performance and third-party data empower you to innovate faster
Ready to get the all-inclusive credit risk decisioning experience you’ve been waiting for?
The Ultimate Guide to Decision Engines
What is a decision engine and how does it help your business processes?
Transforming Financial Institutions through Data-as-a-Service
Outdated system capabilities, limited access to data and outdated decisioning engines make it difficult for many financial institutions to implement advanced credit models to gain a holistic view of the consumer and help make more equitable credit decisions.
Financial institutions will increasingly depend on data as the go-to solution to accelerate innovation and create opportunities. In this article in Financial CIO, Bharath Vellore, General Manager of Asia-Pacific at Provenir, discussed the role Data-as-a-Service (DaaS) plays in opening doors to improve credit decisioning and ensure financial inclusivity, through efforts to bank the unbanked in Southeast Asia.
