Kreditz

Alternative credit scoring platform
Last updated:
February 1, 2026
Company details
HQ
HEADCOUNT
25-99
ORG TYPE
Startup
SECTOR
Finance
About the company
Kreditz is a Swedish fintech that sells real-time credit and risk decisioning using open banking and PSD2 data. The company’s public materials position the product as “next-gen” credit scoring for banks, financial institutions, and other regulated industries. Kreditz says the company was founded in 2018 and lists 33 co-workers alongside 2024 turnover figures on the careers site. Current hiring is centred on Danderyd, Stockholm, with an office-first setup described in at least one technical posting.
Locations and presence
Kreditz lists Danderyd, Stockholm as the active hiring location on the careers site. Some job filters also reference other European cities, but the locations page itself only surfaces Danderyd as a selectable site.
Palpable Score
52.6
/ 100
Kreditz offers a real entry route via internships, but early-career access into permanent junior roles is not very visible in the current open roles list. The hiring flow is structured enough to apply through an ATS, yet public candidate feedback about interview conduct and follow-up creates a trust gap that matters most for first-time applicants.
Pillar 1: Early-career access

Score

10.3
/ 20
  • The company has previously advertised an “Internship (open application)” role, which is a clear early-career door.
  • Kreditz has publicly celebrated multiple interns across different teams and positioned internships as meaningful contributions rather than shadowing only.
  • The company’s current open roles list is entirely mid-senior and leadership (for example Product Manager, Marketing Manager, Senior Cloud Security Engineer, CFO), which limits entry-level access right now.

Pillar 2: Hiring fairness and transparency

Score

10.7
/ 20
  • The company uses a consistent applicant tracking system flow (with role pages, locations, and a standard application entry point) rather than informal inbox hiring.
  • Kreditz frequently describes recruitment as “ongoing selection” without publishing stage-by-stage steps, assessment expectations, or feedback timelines, which leaves early-career candidates guessing.
  • The company has a public interview account describing an unpleasant interview tone followed by ghosting, which is a concrete fairness risk even if it is a small sample.

Pillar 3: Learning and support

Score

12.0
/ 20
  • The company lists tangible wellbeing supports on the careers site such as private health insurance, wellness allowance, and on-site gym access, which helps early-career employees sustain pace.
  • Kreditz has a public employee review describing knowledgeable colleagues who share expertise and help each other, which is one of the most useful day-to-day learning signals for juniors.
  • The company does not publish onboarding details, mentoring expectations, manager 1:1 cadence, or a ramp plan in job descriptions, so learning support stays mostly implicit.

Pillar 4: Pay fairness and stability

Score

9.3
/ 20
  • The company describes roles as permanent employment in multiple postings, which supports early-career stability compared with repeated short contracts.
  • Kreditz repeatedly uses “competitive salary” language without publishing ranges for most roles, which makes pay fairness hard to judge before interviews.
  • The company mentions option incentives in at least one senior role, but the company does not explain equity norms or compensation bands in a way that helps early-career candidates compare offers.

Pillar 5: Early-career outcomes

Score

10.3
/ 20
  • The company has publicly stated that most interns receive offers to continue, which is a positive conversion signal if consistent over time.
  • Kreditz has only a very small amount of public review data, so it is hard to verify early-career retention, promotions, or manager quality patterns.
  • The company does not publish early-career progression outcomes such as typical time-to-promotion, internal mobility examples, or a career framework, which caps confidence in outcomes.

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