Model Validator IRRBB & ICLAAP

ing; Amsterdam; On-site; EUR 90,000 - 130,000; Full time

Job summary

ING is seeking an energetic Model Validator to support the Chapter IRRBB & ICLAAP within Model Validation Financial Risk in Amsterdam. You will safeguard the quality of ING's models and validate IRRBB & ICLAAP models used across ~40 countries, spanning technically advanced and judgement-based approaches.

As part of a cross‑domain framework, you will challenge model risk, prepare comprehensive validation reports, and contribute to automation and innovative validation methods.

Qualifications

• MSc or PhD in (Financial) Econometrics, Financial Mathematics, Quantitative Financial Economics, Mathematics, Statistics, Physics or similar with relevant experience.
• Solid programming experience with Python and/or R.
• Excellent communication skills to explain complex topics to diverse stakeholders.

Responsibilities

• Conduct timely, high-quality model validations in line with external regulations and internal policies.
• Challenge 1st MLoD on their level of model risk.
• Prepare validation reports and present findings to committees and stakeholders.
• Participate in thematic reviews and provide expert advice on model risk issues.
• Support development and implementation of innovative validation frameworks and automation initiatives.
• Collaborate with colleagues across chapters/locations to ensure consistency and share best practices.
• Maintain constructive relationships with internal teams and external regulators/auditors.
• Contribute to continuous improvement of validation processes and frameworks.

Skills

Python

R

Communication skills

Attention to detail

Stakeholder management

Education

MSc or PhD in quantitative field

Job description

We are looking for an energetic, naturally collaborative, and hands‑on Model Validator to support the Chapter Lead IRRBB & ICLAAP within Model Validation Financial Risk.

The team

ING's global Model Validation IRRBB & ICLAAP chapter is an energetic, diverse and collaborative international team consisting of about 15 highly qualified professionals of various quantitative backgrounds, located in Amsterdam.

As model validators we safeguard the quality of ING's models, which are used for all kinds of decision‑making purposes.

We are responsible for validating IRRBB & ICLAAP models used by ING in about 40 countries all over the globe. We cover an interesting, wide and evolving model scope aimed to measure the impact of interest rate risk on expected earnings and economic value as well as various ALM models used in balance sheet management. These models vary from those having a technically advanced quantitative orientation to those displaying strong expert judgment (in case of e.g. limited data availability). Our core business consists of independently assessing whether a particular model is fit for the purpose it was designed for, based on the business context, academic theories, empirical evidence, regulations, best practices & technological innovations. Effective challenge is key in our role. Herewith we contribute to sound business practices, supporting a healthy, sustainable ING and global financial stability.

Specific Function

Model Risk Management (MoRM) in a nutshell; Models are an imperfect reflection of reality. Models impact our business and we use models for decision making throughout ING. We need to manage uncertainties and shortcomings in our models, as there are risks involved. Are we sure that the output leads to the right decision? Models are a great asset but come with a risk that needs to be managed. The purpose of the Model Risk Management department is to ensure the models can add business value safely. That's why we've created a cross‑domain Model Risk Management Framework helping us identifying, classifying, recording and validating models we use across ING. For example, Credit, Market, KYC, Operational and Pricing models. Together with our stakeholders in e.g. Model Development and COO Risk we try to obtain the best models for ING.

Roles and responsibilities

• Conduct timely, high-quality model validations in line with external regulations, internal policies, and model validation frameworks.
• Challenge 1st MLoD on their level of model risk
• Prepare validation reports and present findings to committees and stakeholders, ensuring transparency and clarity.
• Participate in thematic reviews and provide expert advice to internal stakeholders on model risk issues.
• Support the development and implementation of innovative validation frameworks and contribute to automation initiatives.
• Collaborate with colleagues across chapters and locations to ensure consistency and share best practices.
• Maintain constructive relationships with internal teams (Model Development, Risk Management, Audit) and assist with external stakeholder management (regulators, auditors).
• Contribute to continuous improvement by suggesting enhancements to validation processes and frameworks.

How to succeed

In particular, as a member of our team, you have:

• A quantitative background, i.e. a MSc or PhD degree in e.g. (Financial) Econometrics, Financial Mathematics, Quantitative Financial Economics, Mathematics, Statistics, Physics etc. combined with significantly relevant professional experience in a comparable role
• Adequate technical and regulatory expertise in quantitative modelling and risk management.
• Solid programming experience (preferably in Python and/or R).
• Attention to detail and commitment to delivering high-quality work.
• Excellent verbal and written communication skills, with the ability to explain complex quantitative and regulatory topics clearly and convincingly to a broad range of stakeholders, including senior management, auditors and regulators.
• Ability to challenge 1st MLoD on their Model Risk and to manage multiple priorities in a fast‑changing environment.
• Continuous improvement mindset and openness to innovation.

Specific Knowledge and Experience

• Behavioral: Modelling of mortgage & other loan prepayments and non‑maturity deposits, as well as other embedded options in retail and wholesale products.
• Interest rate: Market models (e.g. Hull-White model).
• Valuation: Models used for calculating the economic value of a loan or deposit portfolio with embedded options.
• Pricing: Models used for product pricing.
• Replication: Models used for risk transfer.
• Risk measurement: Models used for risk management and reporting (NPVaR, RRaR, NIIaR).

As part of the chapter, you will contribute to further building and developing the team by sharing knowledge, coaching more junior staff and by embracing ING's Agile way of working.

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