Lending is a huge market, and the streams of opportunities it presents to financial institutions aren’t drying up anytime soon. Individuals, businesses and other organizations will need loans today as they would tomorrow and centuries after.

As a result of this demand, engineering lending products from scratch has never been easier. 

Compared to the old days of complex loan structuring or infrastructure for online lending, today, with white-label financial engines, anyone can leverage software providers to create new lending offerings quickly and affordably.

Knowing what customers want out of a modern lending app and where to start developing one can take time. In this piece, we’ve summarised the best practices employed by industry lenders to guide you on the steps required to launch your lending product fast. 

 

Steps to Setting up a New Lending Product

 

#1. First, define your lending product strategy

 

You can’t build for a marker you don’t understand

First, figure out who you want to help with your lending product. Companies often pick a group of people who aren’t well-served by other businesses, like small businesses or freelancers with inconsistent earnings. Once you’ve chosen this group, understand what they need financially. 

This way, you can create a lending product that suits their specific requirements.

 

Understand the regulatory requirements of your business

The finance market is one of the most regulated industries in the world, and regulations differ from region to region. Research the regulatory requirements associated with your chosen segment and incorporate them into your business. 

Depending on the nature of your product offering, you might have to collaborate with a licensed bank to extend loans to customers or guarantee adherence to specific financial regulations.

 

#2. Partner with data providers

 

Accurate, well-informed lending decisions that rely heavily on data. Data allows you to onboard borrowers at the lowest possible risk while delivering highly personalized loan offers to customers. 

Therefore, it’s crucial to pinpoint the necessary data for lending decisions and establish access methods. 

When using this data to create your lending product, there are two segments to consider: data for customer onboarding and data for credit decisions. Let’s delve into these aspects briefly:

 

Customer onboarding data

These data are required to onboard customers and sometimes third parties you might work with to deliver your lending offering. Know-Your-Customer (KYC) and Anti-Money Laundering (AML) data make up most of the customers’ onboarding data requirements set by regulators worldwide. 

These rules mandate lenders to verify customer identities, preventing fraud and confirming legal eligibility for conducting business. It is crucial to pinpoint the specific regulations applicable to your customer base and select a suitable vendor for compliance information.  

When selecting a KYC data vendor, lenders frequently need help with coverage and accuracy to balance the two. An excellent example is the difference in the KYC offerings of TransUnion TruValidate and Experian Precise ID, two US KYC data giants. 

The first provides insights on a large share of the US population; that is coverage. The latter offers insights into a smaller population share with more accuracy. Other vendors like Onfido cover multiple industries. As a lender, the level of coverage vs. accuracy you need depends on the risk profile of customers you serve.

For obtaining AML data, lenders often consider vendors that can scan global databases for negative media, politically exposed people, sanctions lists or country-specific regulations such as OFAC in the US. Companies like ComplyAdvantage, LexisNexis WorldCompliance and RedFlag Alert lead the pack in these areas.

 

Credit data

You need credit data to make informed credit decisions. The external data sources you need to build credit data depend entirely on your customer segment. 

For example, if you want to offer loans to customers with established credit histories, you can partner with a data aggregator, such as CRS, or credit bureaus.

Suppose your customer segment is less traditional and doesn’t necessarily have established credit histories. In that case, you can leverage the services of data providers who help lenders determine the creditworthiness of their target borrowers. 

For example, Codat provides lenders with insight into SMEs’ financial data, such as accounting, banking, and e-commerce data, to help them determine the creditworthiness of SMEs.

 

Prepare for data providers’ checks

After identifying potential data sources for compliance, you might have to undergo assessments to ascertain your business’s eligibility to access the data they offer. 

Certain credit bureaus, for instance, may demand office inspections or technical acceptance tests. Opting for reputable aggregators that handle compliance internally can substantially expedite these procedures. 

Once checks are completed, establish relationships with your chosen data providers and negotiate favourable rates for their services so you keep your data costs modest. Ask your provider if they offer volume-based discounts. 

 

#3. Choose a scalable decisioning engine

 

Lending business is a business of decisions. Profit or loss depends on the correctness of your decision at multiple stages in the lending process – from KYC and AML checks to credit underwriting and debt collection. 

Automated decision engines help lenders make accurate real-time decisions and disburse loans faster. But you know what’s more important than automating your decision processes? Scalability. 

The best decision engines are platforms that allow you to continue to scale your loan offerings and customer base through integrations, platform flexibility and cloud storage.

Leveraging a beyond-banking technology partner that offers a lending engine can help you launch your product quickly and save you significant resources compared to building one in-house.

Automate your decision processes

Once you’ve partnered with a decision or lending engine provider, go on to automate your decision flows. As discussed above, major decision flows cut across two boards: customer onboarding and credit decisions.

 

Automating customer onboarding

Onboarding decision-making involves evaluating whether to allow a customer to use your platform or not based on their KYC information and AML profile to avoid accepting customers that may be fraudulent.

Now, you must decide between the number of steps customers must go through to be fully onboarded and drop-off rates. 

If you include too many steps in the onboarding process, you might increase the accuracy of a decision but may also cause customers to drop off and not come on board. 

The sweet spot is creating a decision process that lets you collect only necessary compliance data while keeping customers engaged enough to finish the process.

 

Automating credit decisioning

Here, you want to build processes that let your system assess a customer’s creditworthiness and create an individualized loan offer. 

 

The rules and models that form the basis of credit decisioning steps are called credit policy. These rules are usually created by credit experts (whom you might have to engage to design rules tailored to your loan offerings) and consist of three main parts:

 

1. Creditworthiness checks evaluate the likelihood of a potential borrower defaulting. These evaluations rely on rulesets, scorecards, or models incorporating external data from selected providers, such as credit bureaus.
2. Knockout rules exclude individuals from the process if they do not meet the lending criteria, such as minors or the unemployed. This avoids unnecessary expenses for lenders on third-party data for applicants who fall outside their risk tolerance.
3. Affordability calculations establish the highest loan amount and interest rate a customer could manage to repay while still fulfilling their regular financial commitments.

While you can build and maintain your decision engine in-house, many lenders find it easier, faster and cheaper to leverage existing lending engines by technology providers like Finslack. 

With the Finslack lending engine, they can turn their credit policies into seamless decision flows, integrate all third-party data sources, use in-built providers, and adjust their policies whenever to suit business needs. 

Now, we come to the last part.

 

4. Find Capital and a Loan Management System

A loan management system orchestrates loan origination, disbursement, accounting and, in advanced cases, debt collection. It’s the engine behind the decision engine that helps you manage the money-handling part of your lending business. 

Here’s what you should be concerned about:

 

Do you have enough capital for loans?

As a first-time lender, you’re expected to use your capital to fund originated loans. Once your loans are serviced and successfully repaid, and you prove your credit policy works, you can opt to obtain debt financing from providers.

 

Manage your loan cycle

You can build an in-house loan management system (LMS) or leverage existing LMS providers to manage the entire loan cycle from origination to debt collection.

Finslack LMS help you automate your loan lifecycle from origination and collections to reminding customers of late payments and guiding you on default loans.

 

Partner with a licensed bank

First-time fintech are not considered banks at law and therefore cannot hold money. You would need to partner with a licensed bank. 

If you align each component of your new lending product as early as possible with your partner bank, you can launch your product quickly with little interruption from your bank’s internal processes. The good thing about leveraging technology providers like Fincode is that you can speed up the engineering processes of building a loan product and go live in as little as 21 days.

Contact us to see a demo.