CSRSA Live Webinar: Building Trust in Credit Risk Data with DBT (Data Build Tool)
Title: Building Trust in Credit Risk Data with DBT
Date: March 26, 2026 @ 11AM-12PM Eastern Time
Presenter: Lucas Peinado Bruscato, Data Science Lead at Riverty
Session Description:
In an era of rapid economic change and rising uncertainty, financial institutions are under pressure to make faster, more accurate credit risk decisions. The ability to trust the underlying data behind credit loss models has become more critical than ever, especially in the context of IFRS 9 and forward-looking risk frameworks.
While advanced credit risk models offer powerful predictive capabilities, their reliability is only as strong as the quality, transparency, and governance of the data that feeds them. The COVID-19 pandemic exposed just how vulnerable financial institutions can be when their data pipelines are opaque, overly dependent on historical assumptions, and difficult to adapt during disruptions.
In this session, Lucas Peinado Bruscato will explore how dbt (data build tool) can be leveraged to bring transparency, auditability, and agility to credit risk data pipelines. He will walk through practical strategies for:
1. Building lineage-aware, testable data models to trace the source of risk inputs
2. Implementing automated quality checks and documentation that regulators and auditors can trust
3. Enabling faster iteration and overrides when responding to novel or emerging risk factors
4. Supporting governance and model validation through modular, version-controlled transformations
Whether you're building Expected Credit Loss (ECL) models or supporting scenario-based risk simulations, this session will provide actionable insights for enhancing trust in the data that drives your decisions.
Presenter Profile: Lucas Peinado Bruscato
Lucas has over a decade of experience in data science, engineering, and analytics. He is currently a Data Science Lead at Riverty, where he manages a team of data scientists focused on credit risk and fraud prevention. Previously, he oversaw the architectural foundations of analytics engineering at Trade Republic. Before that, Lucas held key roles at Klarna, leading data science teams responsible for credit modeling and risk assessment across multiple markets.
He brings deep technical expertise in Python, SQL, AWS, Snowflake, dbt, Terraform, and related technologies, with a strong emphasis on building scalable data infrastructures that enable machine learning and advanced analytics.
Price: Free for members
