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FinTech · Payments · PNC

Merchant Onboarding — PNC

How a seven-stage screening pipeline cut underwriting time 38% while blocking 27% more fraud.

An enterprise screening dashboard covering the full seven-stage merchant onboarding pipeline — from pre-screening to web-content analysis — with a GenAI layer that surfaces risk in plain language and keeps payment environments secure and compliant.

Role: Product Design LeadYear: 2024Sector: Merchant Acquiring
7
Screening stages
35%
End-to-end approval
-38%
Underwriting time
+27%
Fraud blocked

Seven-stage screening process

Each stage compounds confidence in a merchant's legitimacy. The dashboard maps one-to-one onto this flow so every drop-off is traceable to a real stage.

1

Pre-screening

Businesses evaluate potential PSPs or gateways that align with their needs.

2

Identity checks

Rigorous identity verification ensures the business's legitimacy and minimizes fraud risks.

3

Underwriting

Assess the business's financial stability, creditworthiness, and risk profile.

4

Merchant history screening

Examine past performance; prevalent issues help gauge reliability and trustworthiness.

5

Business & operational analysis

Understand the business model, operations, and scalability to tailor a payment solution.

6

Compliance setup

Compliance with regulations such as anti-money-laundering and data protection is non-negotiable.

7

Web content analysis

The business's online presence is scrutinized, including website content and security protocols.

Explore the live dashboard

A working slice of the product. Switch the time range to watch the screening funnel, KPIs, live risk signals, and the AI agent assistant respond in real time. Hover any metric for a plain-language definition.

Merchant Onboarding — PNC · Live Demo

Seven-stage screening pipeline · as of May 2025

1
Pre-screening
14,210
100%
2
Identity Checks
11,840
83.3%
3
Underwriting
9,560
67.3%
4
Merchant History
8,120
57.1%
5
Business Analysis
6,940
48.8%
6
Compliance Setup
5,610
39.5%
7
Web Content Analysis
4,980
35%
Onboarding Approval Rate
35.0%
+4.1pp vs prior
Identity Pass Rate
83.3%
+2.6pp vs prior
Fraud Blocked
612
+18% vs prior
Avg. Underwriting Time
1d 09h
-4.8h vs prior

Screening Pipeline Funnel

7D · merchants per stage

Live Risk Signals

from screening engine
  • Identity mismatch

    Document vs. registry conflicts ↑

    Medium
  • High-risk merchant category

    MCC flagged for enhanced review

    High
  • AML / sanctions matches

    17 cases flagged for review

    Low
  • Adverse merchant history

    Prior chargebacks detected

    Medium
  • Website / content risk

    Insecure checkout on 4 sites

    Low
Diverse payment methods

Accept cards, digital wallets, and NetBanking so customers pay with their preferred method.

Speed & simplicity

Fast, efficient payment flows streamline transactions for both customers and merchants.

Security & trust

Robust, encrypted payment platforms give merchants confidence in every transaction.

Transaction monitoring

Real-time insights reveal sales patterns and peak hours to optimize operations.

Metrics glossary

plain-language definitions for every metric on this dashboard
Onboarding Approval Rate
Share of pre-screened merchants that clear all seven stages and are approved to transact.
Identity Pass Rate
Percentage of merchants that clear identity verification on first pass.
Fraud Blocked
Count of applications stopped by identity, AML, or history checks before approval.
Avg. Underwriting Time
Average time to assess financial stability, creditworthiness, and risk profile.
PSP / Gateway
Payment Service Provider / payment gateway — the platform that processes a merchant's card and digital payments.
Underwriting
Risk assessment of a merchant's finances, credit, and business model to decide approval terms.
AML / Sanctions
Anti-Money-Laundering and global sanctions screening to prevent onboarding prohibited entities.
MCC
Merchant Category Code — classifies a business type; some categories carry higher inherent risk.
Chargeback
A forced payment reversal initiated by a cardholder's bank; high rates signal merchant risk.
pp (percentage points)
The absolute difference between two percentages. +4pp means a rate rose from, e.g., 30% to 34%.
Case study summary

From challenge to outcome

1

The Problem

No shared view of screening. Seven mandated stages each had an owner, a tool and its own evidence trail, so legitimate merchants queued behind manual checks while risky ones surfaced late.
2

What We Learned

Every stage compounds confidence in a merchant. Weak visibility at any one of them becomes a chargeback, a fine or a fraud loss downstream.
3

The Strategy

One dashboard mapped one-to-one onto the seven stages, with live stage trends from authentic screening data so every drop-off traces to a real control instead of a black box.
4

How It Was Built

A GenAI layer accelerates without loosening: it validates identity documents, runs adverse-media and sanctions screening, summarises merchant history, and writes a ranked risk narrative linked to the signal behind it.
5

Accessibility

WCAG AA on dense screening data: risk levels carry text as well as colour, charts expose summaries, and the agent chat and review queues are fully keyboard-operable with correct labels and focus order.
6

The Impact

Underwriting time −38%, 27% more fraudulent applications blocked, 35% end-to-end approval rate across all seven stages.
7

What I Carry Forward

Compliance stages are not overhead to hide. Made visible, they become the product's credibility.

Structure, flow & fidelity

How the product was organised, the path a user actually takes through it, and how the work travelled from scratch wireframes to a working prototype.

Information architecture

Onboarding

  • Eligibility
  • Business & ownership
  • Compliance disclosures
  • Submit

Review

  • Underwriting queue
  • Risk flags
  • Document checks
  • Decision

Merchant portal

  • Application status
  • Requested items
  • Messages
  • Help

Activation

  • Terminal & gateway setup
  • Fees and terms
  • Go-live checklist
  • Support

User flow of the core task

  1. Step 01

    Check eligibility

    A short pre-qualification avoids sending merchants down a dead-end path.

  2. Step 02

    Submit the application

    Grouped, plain-language steps replace a single long compliance form.

  3. Step 03

    Respond to requests

    Requested items appear in the portal with the reason attached.

  4. Step 04

    Underwriting decides

    Reviewers work from a consolidated case with flags surfaced first.

  5. Step 05

    Go live

    Activation checklist takes the merchant to the first transaction.

Behind the work

My scope, the guardrails I worked inside, what the research changed, and how the work travelled from sketch to production.

My role & scope

Product design lead across all seven screening stages: stakeholder mapping with risk, compliance and underwriting owners, the unified funnel IA, the GenAI risk-narrative layer, and the component states for each stage. Paired with 5 engineers and a compliance SME.

Constraints & guardrails

  • AML, KYC and data-protection rules fixed the stage order — the flow could be clarified, never shortened.
  • Seven legacy tools with different data models, integrated behind one view without replacing any of them.
  • 16-week delivery window tied to an acquiring-portfolio launch.
  • Every automated decision had to remain auditable and reversible by a human reviewer.

What research changed

  • Process mapping with 9 stage owners found the same merchant evidence re-requested in 3 separate stages.
  • Queue analytics: 41% of total onboarding time sat in hand-off waits, not in the checks themselves.
  • Reviewers said the blocker was not the decision but reconstructing what earlier stages had already found.

The pivot

An early concept collapsed the seven stages into three simplified ones. Compliance rejected it — the mandated stages must stay visible for audit. We kept all seven and instead removed ambiguity between them with a shared evidence trail and a plain-language narrative.

UX metric → business impact

Duplicate evidence requests per merchant dropped from 3 to 1
Underwriting time fell 38%, releasing legitimate merchants into revenue sooner.
Risk signals surfaced at stage 2 instead of stage 6
27% more fraudulent applications blocked before onboarding cost was incurred.
Single funnel view across seven stages
35% end-to-end approval rate with an audit trail compliance could sign off on.
1Lo-fi

Service blueprint of the seven stages with owners, tools and hand-off waits marked in red.

2Mid-fi

Interactive funnel prototype with reviewer-decision states and accessibility annotations for the queue tables.

3Production

Live screening dashboard: stage funnel, KPI band, ranked risk signals and the GenAI narrative with linked evidence.

Retrospective

With more time

Run a moderated study with sub-merchant applicants, not just internal reviewers — the outside-in view of the wait would have sharpened the pre-screening stage.

Biggest takeaway

Compliance stages are not overhead to hide. Made visible and legible, they become the product's credibility — and the speed comes from removing ambiguity between stages, not controls.

“The screening story used to live in seven different places. Putting it in one narrative changed how fast we could say yes — and how confidently we could say no.”
— Risk & Compliance Lead, acquiring bank (name withheld under NDA)