Risk Analytics & Insights Lead

Company Overview

SMB Money has evolved from a traditional unsecured consumer lender using mixed manual and technological processes into a fully digital fintech company, renowned for its automated credit decisioning platform. It is now expanding into mainstream personal loans with a commitment to responsible lending and superior customer care, providing longer-term credit options tailored for everyday New Zealanders.

Role Summary

The Risk Analytics & Insights Lead will own the end-to-end analytics and reporting associated with SMB Money's lending portfolio. This includes transforming data from loan origination through account lifecycle and collections into comprehensive metrics, early-warning signals, and actionable insights that guide lending strategies, pricing decisions, and risk management. Reporting directly to the Chief Risk, Data and Analytics Officer, this high-impact position plays a critical role in steering credit strategy and board-level reporting.

Key Responsibilities

• Manage and maintain SMB's comprehensive risk and credit reporting suite covering applications, loan funnel conversion rates, account performance, and delinquency or collections trends, ensuring accuracy and timeliness.
• Develop and automate dashboards and analytics pipelines using R and Python on AWS, replacing manual reporting processes with scalable, reliable systems.
• Monitor portfolio health metrics such as vintage curves, roll rates, arrears categories, cure rates, and recovery rates, proactively flagging emerging risks before losses occur.
• Assess and track the performance of application and behavioral scorecards and models (metrics like PSI, KS, gain/lift, override analysis), coordinating with the credit risk modeling team to maintain their effectiveness.
• Translate data related to origination, pricing, and channels (including intermediaries) into insights that shape underwriting policies, risk-based pricing, and growth strategies.
• Collaborate with Collections and Underwriting teams to identify early-warning indicators and support data-driven decisions for collection treatments and hardship approaches.
• Build the analytical framework to support regulatory and compliance reporting, including obligations under CCCFA and responsible lending requirements.
• Present and communicate findings and strategic recommendations to a diverse audience ranging from operations teams to executive leadership.
• Ensure high data quality for all risk reporting by investigating and resolving anomalies at their source rather than applying downstream fixes.
• Enhance quantitative and analytical capabilities across Risk and Operations teams via coaching and by developing intuitive, documented self-service reporting tools.

Required Qualifications and Skills

• Proficient hands-on experience with R and/or Python for data analysis, automation, and production-quality reporting.
• Demonstrated experience working with cloud data platforms, preferably AWS technologies such as Redshift, S3, Athena, QuickSight, and Glue, or an equivalent modern data stack.
• Strong SQL skills with experience handling large, real-world lending datasets.
• Practical knowledge of monitoring predictive models and scorecards in production environments, including detecting data characteristic shifts and population stability issues.
• Experience creating clear, decision-ready dashboards and reports suitable for both technical users and business stakeholders, comfortable with tools like QuickSight, Power BI, or Tableau.
• Exceptional communication skills to interpret technical analysis into accessible insights for underwriting, collections, and leadership teams.
• Highly self-motivated with attention to detail, capable of autonomously managing an entire analytics domain with minimal oversight.

Preferred Experience

• Background in consumer or SME lending, fintech, or regulated financial services within New Zealand or Australia.
• Understanding of core credit risk concepts such as application funnels, account and portfolio performance metrics, delinquency, collections, vintage and roll-rate analysis.
• Familiarity with loan management systems (e.g., Mambu) and credit bureau data providers (Equifax, Centrix, Experian/Illion).
• Exposure to affordability assessments, IFRS 9 provisioning frameworks, and behavioral scoring models.
• Experience reporting on broker or intermediary loan origination channels.
• Knowledge of CCCFA and other responsible lending regulation requirements.

Work Environment and Benefits

• A prominent role with direct interaction with the Chief Risk, Data and Analytics Officer and substantial influence over SMB’s credit and risk strategy.
• Opportunity to design and develop state-of-the-art automated risk analytics infrastructure from the ground up using green-field AWS technology.
• Flexible hybrid work setup based in Christchurch or Melbourne, with remote work possible for candidates in New Zealand or Australia.
• High degree of ownership and autonomy within a lean, collaborative fintech team known for its responsible lending ethics.
• Competitive remuneration combined with performance-based incentives.