Field Examination- Data & Analytics-Analyst

Asset Based Lending (ABL) is a form of financing that provides asset-based loans to a wide range of companies, particularly those with asset-rich balance sheets and working capital needs.

ABL supports businesses across diverse industries such as Consumer & Retail, Industrials, Metals & Mining, Oil & Gas, and Tech/Media/Telecom, etc.

ABL offers full-service solutions including originations, syndications, portfolio management, collateral monitoring, and loan servicing for both syndicated and sole-lender transactions.

As a Field Exam Data & Analytics Analyst in Risk Management and Compliance, you will be dedicated to standardizing processes, automating workflows, and leveraging AI and automation capabilities (e.g., automated data ingestion from disparate sources, AI-assisted workpaper review, etc.) to achieve measurable results for clients and internal stakeholders.

The role of an ABL Field Exam Analyst, Data & Analytics focuses on generating structured data capture, trend analyses, and operational reporting inputs that enable centralized insights and improved risk identification.

The team foster.

s an environment that values intellectual curiosity, critical thinking, and a passion for enabling analytics-driven decision making.

You will be a founding member of the Field Exam D&A team, responsible for assisting in the design and development of the data model, building centralized data storage, and creating the AI-augmented analytics layer from the ground up.

Job Responsibilities


* Build and maintain operational and strategic KPI dashboards


* Analyze client accounts receivable, inventory, and accounts payable data and historical performance datasets to identify trends, anomalies, and performance drivers


* Support standardized data capture and consistent documentation to improve downstream reporting and insights


* Automate recurring reports and improve reporting efficiency


* Build and maintain client's collateral monitoring model


* Support the creation/testing of standardized LLM prompt packs for examiner workflows to drive targeted risk identification and efficiency.


* Collaborate on AI-assisted reconciliation and exception-triage workflows


* Evaluate and prototype agentic automation use cases (e.g., multi-step data extraction from Excel files, cross-system validation, anomaly surfacing)


* Build QA and feedback loops for AI-generated outputs to ensure explain ability, accuracy, and compliance with model risk and audit standards


* Collaborate with various platform, product, and process owners across the ABL ecosystem to creatively integrate data and insights


* Establish data quality, validation, and governance standards

Required Qualifications, Skills, and Capabilities


* SQL or SQL-like languages proficiency


* Foundational understanding of data modeling and data pipeline concepts (how data moves from source to reporting layer)


* Comfort working with AI-assisted tools and will...