Associate Director, Financial Risk & Modelling

TNG Digital; Kuala Lumpur; Sur place; MYR 180 000 - 320 000; Plein temps

Avantages offerts par ce poste

Medical coverage

Extra leave

Lifestyle allowance

Mobile reimbursement

Broadband reimbursement

Discounts

Wellness perks

Résumé du poste

TNG Digital is a leading payments technology company in Malaysia, powering eWallet and financial services. You will lead credit and fraud risk analytics across digital channels, aligning to BNM expectations and fintech operating models.

You will drive model development, risk appetite, and real-time decision systems while overseeing a high-impact analytics team and collaborating with Product and Technology.

Qualifications

• Bachelor’s degree required in a quantitative field.
• 7–10 years of experience in credit risk, fraud risk, analytics, and modelling in fintech/banking.
• Hands-on data analysis and modelling skills (SQL, Python or R).
• Knowledge of regulatory requirements for digital financial services and AML/CFT.

Responsabilités

• Lead credit and financial risk analytics, including consumer credit, merchant exposure, and counterparty risk.
• Design and govern credit assessment models and decision engines.
• Lead fraud risk strategy execution across account takeover, transaction, and merchant fraud.
• Monitor risk metrics and propose mitigations; collaborate with product and tech teams.
• Develop and scale risk analytics teams; mentor analysts and communicate insights to leadership.

Connaissances

SQL

Python

R

Statistical methods

Credit scoring

Decision engines

Fraud analytics

Machine learning

Formation

Bachelor’s degree in Finance, Economics, Statistics, Mathematics, Actuarial Science, Computer Science, or related quantitative discipline

Outils

SQL

Description du poste

At TNG Digital, part of TNG Digital Group, we build the tech behind TNG eWallet, one of Malaysia’s most used apps for payments and everyday life.

Millions of people rely on us daily, not just to pay, but to manage money, access financial services, and get things done faster and simpler.

Behind it all is a team that likes to question how things are done, move quickly, and try new ideas. If you enjoy solving real problems and seeing your work used at scale, you will feel right at home here.

What You'll Do:

• Lead the design and execution of credit and financial risk frameworks aligned with BNM regulatory expectations, internal risk appetite, and fintech operating models
• Set and enforce credit risk appetite parameters — default rates, charge-off thresholds, exposure limits by product and counterparty
• Monitor portfolio risk metrics (approval quality, portfolio performance trends, loss rates, concentration exposure) and proactively recommend mitigation actions
• Conduct scenario analysis and stress testing on credit exposures; surface tail-risk concentrations and diminishing-return points in risk-reduction strategies
• Ensure the Group maintains current knowledge of BNM regulatory requirements for electronic money, digital financial services, and AML/CFT; lead gap assessments and remediation programmes where required
• Require first-line adherence to credit and risk policy; issue binding risk findings where breaches are identified

Financial Risk Analytics & Modelling

• Lead fraud risk strategy execution — covering account takeover, application fraud, transaction fraud, merchant collusion, and social engineering typologies
• Design, calibrate, and govern fraud detection rule sets and machine-learning models across digital channels, including real-time transaction monitoring and post-event investigation
• Establish fraud risk appetite metrics and KRIs; monitor loss rates, false-positive ratios, and investigation throughput against thresholds
• Lead credit and financial risk analytics — consumer credit products (BNPL, micro-lending), merchant credit exposure, and counterparty risk from payment partners
• Develop and govern credit assessment models and decision engines — alternative data scoring, behavioural risk profiling, and dynamic limit management
• Drive advanced analytics adoption (machine learning, graph/network analysis, anomaly detection) for both fraud detection and credit scoring
• Partner with Technology and Data Engineering to ensure risk analytics pipelines are production-grade, auditable, and scalable
• Leverage alternative data sources (e.g., telco, e-wallet usage, transactional data, behavioural signals) to improve thin-file customer underwriting
• Support the design and optimization of automated, real-time credit decision systems for seamless digital onboarding
• Drive continuous improvement of risk models to balance growth, customer experience, and portfolio quality
• Keep abreast of emerging fintech trends (AI/ML, open banking, embedded finance) and evaluate applicability to risk strategy

Stakeholder Management & Leadership

• Act as a key risk partner to Product, Business, and Technology teams to support responsible growth; embed risk-by-design principles into new product launches and channel expansions
• Translate complex analytical outputs into clear, actionable insights and strategy recommendations for senior stakeholders, including the Board Risk Committee
• Present portfolio performance, model outcomes, and risk recommendations at leadership forums and board level
• Build, lead, and retain a high-performance analytics team across fraud and credit domains; set performance standards tied to measurable outcomes — loss reduction, model quality, risk appetite adherence
• Foster a data-driven risk culture within the organisation; mentor analysts on statistical methods, regulatory interpretation, and strategic communication

Role Requirements:

• Bachelor’s degree in Finance, Economics, Statistics, Mathematics, Actuarial Science, Computer Science, or related quantitative discipline
• 7–10 years of experience in credit risk, fraud risk, analytics, and modelling within banking, digital banking, or fintech environments
• Hands-on proficiency in data analysis and modelling — SQL, Python or R, statistical methods, credit scoring, decision engine design, or fraud analytics
• Working knowledge of BNM regulatory requirements for digital financial services, e-money, and fraud/credit risk management
• Experience translating complex quantitative analysis into strategy and presenting to senior stakeholders (board, C-suite, regulators)
• Experience building and scaling risk analytics teams; performance management tied to outcomes, not activity
• Hands-on big data analytics, AI model, feature engineering, time-series and forecasting
• Agentic AI experience is a plus
• Proven ability to collaborate and influence cross-functional teams

What you get

Work your way

• Medical coverage, with option to include dependants
• Extra leave for family and caregiving needs

Rewards that grow with you

• Monthly lifestyle allowance via TNG eWallet
• Long-term rewards for your contributions

Everyday support

• Mobile and broadband reimbursement
• Discounts and wellness perks

What it’s like to work here

We care about people who take ownership, speak up, and want to make things better. Titles matter less than impact. Good ideas can come from anyone.

You will be working with people who are curious, practical, and not afraid to challenge each other in a good way.

Note: Only shortlisted candidates will be contacted.