VP Credit Risk Management

Regional Finance•Plano, TX

3d•Hybrid

About The Position

Take your career to the next level! In the last few years our goal has been expansion, creating growth opportunities for many of our team members. Not only are we serious about growth, but we are also serious about helping our customers during hard financial times. We take pride in providing solutions and offering a helping hand, not only to our customers but also to the communities we serve. As we continue to expand and grow into a national leader in consumer financing, we invite you to consider joining our team. If you're passionate about making a meaningful impact in people's lives and bringing a personal touch to finance, we'd love to have you on board! Regional Finance (NYSE: RM) is leading financial company, proudly serving millions of customers with safe, affordable, and transparent installment loans. Our customers turn to us every day—online and across hundreds of branches in multiple states—to help them take control and improve their financial lives. The VP, Credit Risk is a senior leadership position responsible for portfolio analytics, CECL/Loss Reserve modeling, business performance reporting/initiatives, and business unit support for the Credit Risk Management organization within Regional Management. This position will utilize advance skills to develop strategies to drive growth in our consumer portfolios that are within RM’s risk targets. The leader will deliver rigorous analytically derived recommendations driven from detailed understanding of risk and reward dynamics across RM’s lending products. They will drive the vision, strategy, and innovation for credit management. You will be part of a fast-paced and dispersed team responsible for creating the best-in-class customer experiences while modernizing our omni-channel credit platforms. This role will lead the effort around end-to-end methodology design, modeling choices, execution and documentation for Regional’s reserving process and will contribute to designing and implement the end state operating model, which requires proven partnership, leadership and credit risk expertise as the team will coordinate across multitude of stakeholders in Risk, Finance, Marketing, Technology and Internal Audit.

Requirements

Master’s degree in Statistics, Data Analytics, Economics, Math, or similar
10+ years of consumer finance, risk analytics, or relevant experience
Experience in data mining, modeling, and analyzing analytic findings using SAS/R/Python.
Moderate to Expert level skills in Microsoft Office Suite (Excel, Access, and Outlook a must)
Must pass pre-employment screenings.

Nice To Haves

Experience in Financial Services with consumer credit data utilizing SAS/R/Python.
Experience analyzing marketing data in a financial environment.
Experience developing risk models for a financial institution.

Responsibilities

Key member and Risk representative/technical expert in Loan Loss Reserve/CECL, capital-modeling process. Interface with accounting and external counterparts.
Day-to-day portfolio management duties include leading a team to perform data analysis, vintage monitoring and forecasting, creating the logic for and implementing credit risk rules and strategies and communicating with stakeholders to ensure we deliver the best possible customer experience while meeting loss rate targets.
Proactively monitor credit exposure, and provide recommendations and approvals to breaches in the credit process
Leverage credit risk data experience and business acumen to observe key trends / threats / inaccuracies and drivers of those observations. Identify areas of opportunity and spearhead initiatives to enable profitable growth while minimizing credit risk exposure.
Identify business opportunities.
Run credit tests to optimize risk strategies, balancing risk, and return.
Mine, model, analyze large datasets, and utilize predictive modeling techniques with an emphasis on optimizing credit risk and marketing campaign performance using the following predictive modeling techniques: linear/logistic regression, factor analysis, decision trees, clustering, segmentation, etc.
Quantitative analysis of custom score models including, validation, ongoing- performance monitoring, and documentation.
Forecast performance of marketing campaigns and tracks actual campaign performance versus the forecast.
Conduct ad hoc research projects incorporating project design, data collection and analysis, summarization of findings, and presentation of results.
Handle data while utilizing interpretive and problem-solving skills with the ability to process large volume of transaction level data and efficiently derive actionable results.
Interact with stakeholders to understand their business questions, crafting the methodology, to mine/analyze datasets utilizing SAS/R/Python and ultimately delivers a final insightful recommendation to stakeholders.