Vacatures in Riskmanagement

What’s in the box? Useful findings on black box models

Bron: Laurant Dupont, on The Actuary - 15 december 2021

Machine learning (ML) models are used across the financial industry for a variety of purposes. To take two examples from the insurance sector, they can be used to replace traditional pricing approaches – using artificial intelligence (AI) to generate premiums, instead of traditional generalised linear models – or as a decision support tool to direct claims handlers towards cases featuring higher levels of complexity. However, these tools are often perceived as ‘black boxes’.

This summer, the ACPR (the French supervisory authority for the banking and insurance sector) held its first TechSprint. The challenge: generating explanations to understand the behaviour of credit risk predictive models based on AI.

Machine learning, artificial intelligence and regulation

Explainability is critical for building trust in processes based on ML and AI more generally, as it facilitates the validation of an algorithm, comprehension of its output, and its monitoring over the course of its lifecycle. Explainability is also a key factor in firms’ selection of appropriate techniques – it empowers boards and senior management to review and sign off models, and ensures AI-driven decisions are transparent enough to explain to customers.

Lees verder >>

Wil je dit nieuwsbericht verder delen?


Postbus 60184
1320 AE Almere

Tel: 036 - 7440 136

KvK 32090652
ING Bank NL91INGB065.42.67.456
BTW NL.8106.57.041.B01

Wie we zijn is onderdeel van het platform van CareerGuide, 25 vacaturebanken voor specialisten!
Onze vacaturebanken (geen bemiddeling) bieden professionals relevante vacatures binnen hun expertise.

Ook een vacature plaatsen? Neem contact met ons op of stuur hem in via dit formulier.