Bank loans in under 5 minutes instead of weeks
Sterling Specta was Nigeria's first digital lending platform from a commercial bank, and I was its only designer. I designed Specta in Sketch and wrote the HTML and CSS for every screen. The engineering team built those into the C# application.
The finding that shaped it: in early prototypes, instant approval made customers suspicious. So I designed an offer screen that explained the credit decision. In the beta, explaining the decision made more people accept the offer.
- $263Mabout ₦100bn in loans disbursed, 2018 to 2021
- 11,000+customers in the first year, 2018, with close to ₦10bn lent
- 0%non-performing loans (loans not being repaid) in the first year, 2018, as Sterling Bank reported
- Role
- Product Designer (2016 to 2018), then UX Engineer (2018 to 2020). Sole designer, covering research and design.
- Company
- Sterling Bank, a mid-tier Nigerian commercial bank when Specta began (140 branches, about 4,000 staff)
- Timeline
- About 18 months to launch: design started 2016, beta late 2017, public launch 2018. At Sterling Bank from 2014; on Specta from 2016 until I left the bank in January 2020.
- Team
- Core squad of 5: me, a retail expert, a sales expert, a financial analyst and a backend lead, with the wider backend team
- What I made
- Designs in Sketch, and the HTML and CSS for every screen. Platform: web.
- What others built
- The C# application, by the engineering team. The credit scoring model, by the bank's risk and credit team.
Summary: The short version
- Problem
- A bank loan took weeks and needed a guarantor, and rejections rarely came with a reason. The fast alternative was loan sharks with hidden fees.
- Insight
- The barrier was the process, not the price. And in prototypes, an instant yes with no explanation read as a trap.
- What I did
- Designed it in Sketch and wrote the HTML and CSS for every screen: an application that used the bank's own account data instead of paperwork, and an offer screen with a summary of the factors the system considered.
- Result
- From February 2019, Sterling Bank opened Specta to customers of every Nigerian bank, not only its own.
The problem: In 2016 there were two bad ways to borrow
Neither option worked for the people who needed credit most: small business owners who needed quick inventory funding, professionals facing unexpected expenses, anyone without a wealthy guarantor willing to co-sign.
| Bank branch | Loan shark | Specta | |
|---|---|---|---|
| Time to money | 2 to 4 weeks, several branch visits | Fast | A credit decision and money in the account in under 5 minutes, online |
| What you needed | Stacks of paperwork and a guarantor | Collateral or a personal guarantee | For Sterling customers, no guarantor or paperwork: it used their account data |
| What you could see | A black box; rejections rarely explained | Hidden fees, unrealistic repayment terms | A full fee breakdown and a summary of the decision factors |
Every bank in Nigeria already held years of customer transaction data: salary deposits, spending patterns, account history and debt coverage ratios (how much of your income already goes to repayments). The raw material for an automated credit decision was already there, but no bank had been willing to take the risk. Sterling Bank saw the same data and spotted an opportunity.
What I was working within
- Regulatory
Central Bank of Nigeria rules
Rules on KYC (identity checks), interest rate disclosure and lending. Each customer's identity was confirmed with a biometric BVN (Bank Verification Number) check. Being regulated gave Specta a trust foundation loan sharks could not match.
- Trust
Deep customer skepticism toward lending products
Years of exploitation meant even a legitimate, transparent platform would face resistance.
- Technical
Real-time credit scoring on legacy banking infrastructure
The system had to pull transaction history, run debt coverage calculations and give a credit decision and money in the account in under 5 minutes.
What research found: The barrier was the process, not the price
I ran guerrilla research in Sterling Bank branches, with fewer than 20 customers. I interviewed customers informally in banking halls and watched how they dealt with loan officers: the questions they asked and the concerns they raised. I also spent time with credit analysts and branch staff, mapping the manual loan workflow from the inside, and mapped the customer journey from application to disbursement.
Documentation burden
Customers were put off by the process itself: paperwork, guarantors, repeat visits, weeks of uncertainty.
Black-box decisions
Customers couldn't see how decisions were made. If rejected, they rarely knew why. This opacity fed distrust: it felt arbitrary, like loan shark practices.
Waiting costs money
Loan decisions weren't made in the branch, and missing documents sent applications back to the start. For customers who needed credit urgently, every day of waiting was a business cost.
What I designed: The transparency paradox
When I showed customers early prototypes with instant approval, they were suspicious.
“How can you approve me that fast? What’s the catch?”
Years of exploitation had taught Nigerian borrowers that speed meant hidden traps. I had to design a system that earned trust before it earned engagement. That led directly to the credit decision explanation screen.
Showing the factors
The loan offer screen showed a summary of the factors the system considered: salary consistency, spending patterns, debt coverage and account history. It was a transparency layer rather than a per-loan algorithmic breakdown, and it replaced the black box with visible reasoning. What the screen said, and how it said it, were my calls. The credit scoring model behind it was built by the bank's risk and credit team.
- Chose
- Transparency with speed
- Instead of
- Speed first: instant approval, minimal friction
- Because
- In a lending market built on opacity, showing customers exactly what they would pay mattered more than a fast yes on its own. In the beta, explaining the decision made more people accept the offer.
Making the case for showing the factors
The business side assumed speed was the differentiator: get the loan out fast and customers would come. My research with potential borrowers said otherwise. A loan in 5 minutes with no explanation of why you qualified felt exactly like the loan sharks customers were avoiding.
In our internal discussions I pushed for what I called the transparency paradox: showing customers how their credit decision was made. The business team was skeptical. They worried that showing the decision factors would make customers feel surveilled.
I prototyped the factor summary on the loan offer screen and tested it with beta users in late 2017. Customers did not feel surveilled. They felt respected: for the first time, someone explained why they qualified instead of just saying yes or no.
Your financial footprint instead of paperwork
I designed the application around the customer's existing account data instead of guarantors and paperwork, and pre-filled it from that data. The platform read income consistency, spending patterns and debt coverage in real time. Customers agreed to this use of their data in the terms and conditions they accepted.
- Chose
- System knowledge over customer burden
- Instead of
- Asking customers to provide documentation and guarantors
- Because
- The bank already held years of salary and spending data for its own customers.
Your ceiling, before you commit
Customers saw their ceiling before committing, not after. Making it visible was my call. Before accepting, a customer saw:
- the range they were pre-approved for, set by their own risk profile
- a summary of the factors behind the decision
- the amount they wanted, typed within that range
- interest recalculated as they adjusted the amount
- a complete fee breakdown and plain-language terms
When the answer was not a full yes
I also designed the screen for customers who were declined or only partly approved: a lower offer they could still take, what they could change to qualify later, and a way to get help. It did not list the reasons behind the decision.
From design to code
Every screen started in Sketch, and I wrote its HTML and CSS. The engineering team built those files into the C# application. So ideas were tested in HTML and CSS rather than as static screens, in a cycle:
- Sketch
- HTML and CSS prototype
- Stakeholder review
- Iteration
A customer's answer
“After being cheated by loan sharks for years, Specta showed me what honest lending looks like. Everything was clear, and I could even cancel if I changed my mind.”
Impact: Specta grew beyond Sterling's own customers
My part: the design, and the HTML and CSS, of an application that used the bank's account data instead of paperwork, and of an offer screen that explained the decision. Together with the credit scoring model, built by the bank's risk and credit team, they took the wait from 2 to 4 weeks to under 5 minutes.
What Specta achieved
$263M
About ₦100bn in loans disbursed in the first three years after the 2018 launch (2018 to 2021)
The 0% non-performing loans in the first year came from the credit scoring model, built by the bank's risk and credit team, and from existing banking relationships.
How Specta grew
Filled dot: during my time on the project, 2016 to 2020
- During my time on the project: Research and design began
- During my time on the project: Beta with selected customers confirmed the core experience
- During my time on the project: Public launch. In its first year Specta lent close to ₦10bn to over 11,000 customers
- During my time on the project: Opened to customers of every Nigerian bank, not only Sterling's, assessed with credit bureau checks plus salary information
- During my time on the project: A ₦40bn lending target for the second tranche, up 300% from ₦10bn in 2018
- During my time on the project: Sterling Bank won Innovative Bank of the Year at the CBN and NIBSS EPIS Efficiency Awards
- After I left Sterling Bank in January 2020
- PayWithSpecta (buy now, pay later) launched as a separate initiative
“In 5 minutes, I had the money in my account. No paperwork, no guarantors, no hidden charges. Specta saved my business when I needed quick inventory funding.”
Reflection: Trust is the product
In a market with a history of exploitation, trust comes before everything else. On Specta, speed on its own read as a trap, and in the beta, more people accepted the offer once the screen explained the decision.
What I'd do differently
Broader beta testing. The beta with selected customers validated the core experience, but a larger, more diverse group would've uncovered edge cases in credit assessment earlier, particularly for customers with irregular income patterns common in Nigeria's informal economy.
Earlier merchant partnerships. PayWithSpecta came later as a separate initiative. Designing the merchant credit framework into the original architecture would've made the expansion faster.
Portable principle
When the designer also writes the HTML and CSS, design decisions get tested in the browser, not only in the design file. Stakeholder reviews happen on HTML and CSS prototypes, not static screens. And the engineering team builds from the real HTML and CSS of every screen.