Strategic Account Manager, Consumer Lending

Overview

You're splitting time between closing new consumer lending customers and managing a small book of existing accounts. You sell Nova Credit's platform (Credit Passport, Income Navigator, Cash Atlas) to banks, fintechs, and credit unions who want to approve more thin-file consumers, immigrant borrowers, or people with limited traditional credit history. You're running full-cycle sales - prospecting, demos, proof-of-concepts, negotiations - while also ensuring your existing customers expand usage.

Role Snapshot

Company Context

Stage: Series B/C (109 employees suggests late-stage startup)

Size: 109 employees

Growth: Hiring for multiple account management roles suggests they're scaling the sales team and focusing on market penetration

Market Position: Niche player solving specific problems (thin-file lending, immigrant consumers) rather than broad credit bureau replacement

GTM Reality

Pipeline Sources:

• 50% Outbound prospecting to consumer lenders with relevant use cases (fintech lenders, challenger banks, credit unions with immigrant-focused strategies)
• 30% Partner referrals from existing banking customers or industry consultants
• 20% Inbound from industry events, content marketing, and product reputation

SDR/AE Structure: Likely no dedicated SDR support - you're doing your own prospecting and qualification

SE Support: Shared data science consulting team for POCs and technical evaluation, but you lead the sales process

Competitive Landscape

Main Competitors: Traditional credit bureaus (Experian, TransUnion, Equifax) for core data; alternative data providers (Plaid for banking data, Pinwheel/Argyle for payroll data); international credit data aggregators; "do nothing" and manual processes

How They Differentiate: Unified platform combining international credit files, bank transaction data, and income verification - solving thin-file problem with multiple data sources in one integration

Common Objections: "Our current credit data is sufficient," integration complexity concerns, compliance risk perception, cost vs. incremental approval volume, data quality skepticism

Win Themes: Access to previously unreachable consumer segments, faster time-to-value than multi-vendor approach, CRA compliance expertise, proven approval rate lift

What You'll Actually Do

Time Breakdown

New Business Prospecting (30%) | Active Deal Management (35%) | Existing Account Management (20%) | Internal Coordination (15%)

Key Activities

• Prospect into consumer lending organizations: You build target lists of fintechs, challenger banks, credit unions, and regional banks that have thin-file challenges or serve immigrant populations. You're reaching out cold via LinkedIn, email, and warm intros to get meetings with risk leaders or product owners.
• Run discovery and position the business case: You need to understand their current credit decisioning process, approval rates, target segments, and pain points. Then you build a hypothesis for how Nova Credit's data would improve their metrics - this requires understanding credit modeling and underwriting.
• Coordinate proof-of-concept projects: Most deals require a 4-8 week technical POC where your data science team analyzes their historical loan data and proves ROI. You're project managing this, keeping it on track, and managing stakeholder expectations.
• Navigate multi-stakeholder buying processes: You're selling to product/business owners (budget), risk/compliance teams (technical evaluation), legal (contract review), and executive sponsors (final approval). Deals stall when any one group has concerns.
• Manage existing customer relationships: You run QBRs, monitor usage, identify expansion opportunities, and handle renewals for 4-6 existing accounts alongside new business hunting.
• Work cross-functionally internally: You're pulling in data science consultants for technical work, product teams for feature questions, legal for compliance discussions, and finance for contract negotiations.

The Honest Reality

What's Hard

• Financial services sales cycles are long and unpredictable - legal and compliance reviews add months, risk committee approvals get delayed, budget cycles dictate timing you can't control
• You're often educating the market - many lenders haven't considered international credit data or alternative data sources, so you're selling the category not just your product
• Proof-of-concept logistics are complex - getting access to customer loan data requires NDAs, privacy reviews, and data transfer logistics that slow everything down
• You're balancing new business pressure with account management responsibilities - existing customers have urgent needs that compete with closing new deals
• Integration concerns kill deals - if a prospect's engineering team pushes back on implementation complexity, the deal stalls even if the business case is strong
• You need technical credibility to sell data products - if you can't discuss API integration, data schemas, and credit modeling intelligently, you lose credibility with buyer technical evaluators

What Success Looks Like

• Close 4-6 new consumer lending customers per year at $100K-$500K ACV each
• Existing accounts expand usage or renew without significant price erosion
• POCs convert to closed deals at 40-50% rate (high conversion because POCs are resource-intensive and only done with qualified prospects)
• You build a repeatable sales process and can articulate clear ROI for different lender profiles

Who You're Selling To

Primary Buyers:

• VP Consumer Lending / Head of Lending Products (budget owner, business case owner)
• Chief Risk Officer / Head of Credit Risk (technical evaluator, compliance gatekeeper)
• Product Management leaders focused on underserved segments or growth

What They Care About:

• Incremental approval volume without increasing default risk ("Can we safely approve 5-10% more applicants?")
• Competitive positioning ("Are we losing good customers to competitors with better data?")
• Speed and ease of integration ("How long until this is live? What's the engineering lift?")
• Compliance and regulatory risk ("Is this CRA-compliant? What's our audit exposure?")
• Cost per incremental approval ("What does this cost per additional approved loan?")

Requirements

• 3-5 years in B2B sales, account management, or business development in financial services or fintech
• Experience selling to banks, credit unions, or lending fintechs - you need to understand their buying process
• Familiarity with credit risk concepts (credit scores, underwriting models, approval rates, default risk)
• Ability to build business cases and ROI models - you're selling on data-driven value propositions
• Comfort navigating complex, multi-stakeholder sales processes with long cycles
• Self-sufficient prospecting skills - you'll be doing significant outbound without SDR support
• Willingness to learn technical concepts around data integration, APIs, and credit modeling