Full-Time

Secured Credit Risk Manager

Lendable

Lendable

501-1,000 employees

UK fintech marketplace lending for consumers

No salary listed

London, UK

Hybrid

Hybrid role requires three days in-office weekly.

Category
Finance & Banking (2)
,
Required Skills
Python
SQL
Data Analysis
Requirements
  • Deep experience in secured lending credit risk — you've worked on second charge mortgages or similar secured products (bridging, buy-to-let, specialist residential) and understand the product inside out
  • Strong knowledge of risk scoring and pricing — you've built or materially contributed to scorecards, pricing frameworks, or credit policy in a secured lending environment
  • Understanding of funding and capital constraints — you know how loan-to-value covenants, property valuations, and investor criteria shape what you can lend and to whom
  • Commercial awareness and growth mindset — you understand that credit policy exists to enable lending, not prevent it. You think about accept rates, broker conversion, and competitive positioning alongside risk metrics
  • Familiarity with the end-to-end secured lending process — from quote through to completion, including how valuation, legal, and land registry processes interact with credit decisions
  • Analytical rigour — you're comfortable with data. Structured query language is required and Python experience is a plus, but what matters is that you think in numbers and can interrogate management information to drive decisions that lead to more good quality lending
  • Regulatory awareness — working knowledge of Mortgage Conduct of Business and Financial Conduct Authority requirements for second charge lending
  • Experience designing for scale and automation — you understand how to structure underwriting policy as decision logic, scorecards, and rules that can be executed programmatically. You think in terms of tens of thousands of applications, not manual case-by-case review
Responsibilities
  • Define credit policy and underwriting strategy for second charge mortgages, including affordability, eligibility, and decisioning frameworks
  • Own risk scoring and pricing — develop and refine scorecards, risk segmentation, and pricing models that balance volume with portfolio quality
  • Drive growth whilst balancing risk — use analytic and credit judgment to drive growth through credit policy, work with the commercial team to hit volume targets, and all whilst maintaining portfolio quality
  • Own the IRR/NPV/cashflow models - ensure we understand the economics of the asset we’re booking, and drive changes where needed
  • Design automated decisioning logic — translate credit policy into executable rules and decision trees that can be embedded in the platform, working with engineering to build the quickest, most automated secured product on the market
  • Help shape funding strategy — collaborate with the Capital Markets team to inform investor parameters around LTV limits, property valuations, and portfolio concentration, translating these into practical credit policy
  • Inform the property valuation and security process — ensure credit policy accounts for valuation methodology, panel management considerations, and charge registration requirements
  • Monitor portfolio performance — track early indicators, refine strategy based on outcomes, and report to senior stakeholders
  • Collaborate cross-functionally — work daily with product and engineering to embed credit decisioning into the platform, and with legal and compliance to ensure regulatory alignment (MCOB, Consumer Duty)
  • Get stuck in — this is a small team building something from scratch. You'll be hands-on across the full credit lifecycle, not managing from a distance
Desired Qualifications
  • Experience with loan servicing — settlements, collections, arrears management, and recoveries in a secured lending context
  • Exposure to broker distribution models and how credit policy interacts with intermediary channels
  • Experience working in a startup or scale-up environment, or a desire to move from a large organisation into one
  • Experience with decisioning platforms or rules engines

Lendable is a UK fintech that funds unsecured personal loans by connecting borrowers with institutional investors. It operates a two-sided marketplace; capital from pension funds and hedge funds funds the loans rather than using its own balance sheet, while customers get quick, digital loans. The platform uses AI/ML driven credit scoring to automate decisions and funding, with instant approvals and funding often within hours; eligibility checks do not impact credit scores. It offers loan amounts £1,000-£25,000 for 1-5 years and also provides Autolend car finance and Zable credit products (including in the US); its goal is to expand access to consumer credit across a broad UK audience by scaling its platform and product suite.

Company Size

501-1,000

Company Stage

Growth Equity (Venture Capital)

Total Funding

$986.6M

Headquarters

London, United Kingdom

Founded

2014

Simplify Jobs

Simplify's Take

What believers are saying

  • Zable Mobile partnership with Gigs expands revenue streams beyond core lending.
  • Debt facilities to Metafin, LendMN, Leasy, and Alami establish fintech lending leadership.
  • Profitable since 2017 with unicorn valuation above £4.5 billion by 2024.

What critics are saying

  • Zable Mobile faces intense competition from established MVNOs like Giffgaff and Voxi.
  • UK consumer lending demand contracts as interest rates remain elevated above 4.5%.
  • FCA regulatory scrutiny on AI credit scoring biases threatens instant decision advantage.

What makes Lendable unique

  • AI-powered instant credit decisions via open banking data, disbursing funds within hours.
  • Two-sided marketplace model funds loans from institutional investors, not balance sheet.
  • Global impact focus with origination teams across 73 countries in emerging markets.

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6 month growth

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-2%
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