Credit Risk Analytics Resume Samples

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JE
J Erdman
Jerome
Erdman
750 Herman Light
Detroit
MI
+1 (555) 785 2570
750 Herman Light
Detroit
MI
Phone
p +1 (555) 785 2570
Experience Experience
Dallas, TX
Credit Risk Analytics
Dallas, TX
Shanahan, Marvin and Windler
Dallas, TX
Credit Risk Analytics
  • Masters Level or higher qualification in quantitative finance (e.g. MSc Finance)
  • Strong derivatives product knowledge
  • Proactive and positive approach
  • The role will also be responsible for providing analytics support across credit risk lifecycle initiatives: originations, line management, portfolio/customer risk management, capital risk management, and collections & recovery
  • This includes leading and/or overseeing credit scoring/risk rating model development and BB transformation projects in support of key risk strategies
  • Performing granular analysis with attention to details overcoming small data sample challenges is important to the success of this position
  • The analyst will lead and work as part of cross-functional teams (product, credit operations and finance) across the Bank and deliver quality results working in multiple projects and assignments at the same time
Los Angeles, CA
SVP, Credit Risk Analytics & Modeling
Los Angeles, CA
Marvin, Raynor and Hartmann
Los Angeles, CA
SVP, Credit Risk Analytics & Modeling
  • Develop models and oversee model development, validation, and deployment efforts
  • Work with large datasets and complex algorithms to solve data science challenges
  • Ensure the compliance of development and validation of models with respect to internal and external guidelines
  • Support the development of training curriculum and standards
  • Partner with Risk and Decision Management organizations to understand the source of new data and continue to improve the process of defining, extracting and utilizing the new data
  • Provide leadership and guidance for junior modelers
  • 3+ years managing staff (direct or indirect)
present
Phoenix, AZ
VP-wholesale Credit Risk Analytics
Phoenix, AZ
Nolan-Anderson
present
Phoenix, AZ
VP-wholesale Credit Risk Analytics
present
  • Project manage assignments from rating development to system implementation
  • Thorough knowledge of financial theory, economic capital modeling and decision support and performance measurement models and methodologies
  • Position manages, on a project basis, a number of domestic and off-shore analytic resources in formulating recommendations
  • Acts as manager for Wholesale CRAOC and other committees as assigned
  • Off Balance Sheet Credit Exposure US$ X tn
  • On Balance Credit Exposure US$ XXX bn
  • Extensive knowledge of the Basel Capital Accord and US regulatory guidelines
Education Education
Bachelor’s Degree in Statistics
Bachelor’s Degree in Statistics
Georgetown University
Bachelor’s Degree in Statistics
Skills Skills
  • Develop both risk and financial models to further enhance the Portfolio Risk Ratings and improve International Banking assessment of risk appetite
  • Analyze country and product P&L to optimize asset allocation based on risk appetite, while providing insightful recommendation to senior executives on portfolios outlook
  • Collaborate with cross-functional teams in Canada and Latin America to define best-practices on financial reporting and integration of financial and risk metrics
  • Evolve the management reporting process for Executives and the Board, to promote consistency and efficiency, while allowing flexibility in providing timely and relevant analytics based on current performance and/or specific strategies for each market
  • Solicit feedback to ensure reports are not only providing information, but also insight that is valued by our business partners and/or executives
  • Support the Global Reporting and Analytics department in preparing both on-going and ad hoc reporting requests
  • Leads and contributes to team projects and continuous improvement initiatives
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11 Credit Risk Analytics resume templates

1

Manager, Credit Risk Analytics Resume Examples & Samples

  • Providing leadership in credit risk strategies and performance with proposed action
  • Lead and develop a team of 2-4 quantitative analysts
  • Delivering innovative quantitative analytics and statistical modeling solutions that drive enhanced credit risk strategies
  • Implementing step change improvements in reporting and MIS capabilities
  • Partnering with enterprise risk colleagues to enhance loss forecasting, reserving, and economic capital processes and output
  • Advanced degree in statistics, mathematics, economics or other quantitative field
  • 8+ years quantitative analysis experience in the financial services industry
  • Analytical problem-solving and statistical modeling skills
  • Prior people management experience
2

Senior Credit Risk Analytics Analyst Resume Examples & Samples

  • Minimum of five years proven and progressive credit and financial services experience or equivalent, including experience in advanced credit risk management, credit risk modeling and economic credit risk capital or equivalent
  • Minimum of a masters degree in statistics, business, related field or equivalent experience
  • Solid understanding of commercial and retail credit processes, including credit risk assessment and systems, as well as econometrics, statistics and simulations
  • Thorough knowledge of complex financial risk modeling and analysis, including credit risk and economic capital
  • Strong understanding of credit products
3

Credit Risk Analytics Resume Examples & Samples

  • Masters Level or higher qualification in quantitative finance (e.g. MSc Finance)
  • Knowledge of risk models (credit or market risk) preferable
  • Very good organisational and communication skills
  • Proactive and positive approach
4

Manager of Credit Risk & Analytics Resume Examples & Samples

  • At the minimum must have a Bachelor’s Degree preferred within a quantitative discipline
  • Must have 3-6 years of experience pulling data and analyzing customer data utilizing SQL, R, Python, or SAS is a MUST
  • Experience developing statistical predictive / propensity models using R, Python, SAS is a MUST
  • Must have 3-6 years of extensive hands-on experience working on analytical studies from: crafting the methodology, to data mining utilizing SQL, R, Python, or SAS, and ultimately delivering final insightful recommendations to move the business forward
  • Prior experience within Financial Services in particular Credit / Risk Management is a MUST!
  • Experience with test design and preparing testing scenarios on marketing campaigns using R or SAS is a PLUS
  • Will transfer existing H1 Visa and potentially some Relocation assistance may be available. Recruiter: Sunil Sud
5

Senior Manager Credit Risk Analytics Resume Examples & Samples

  • Provide frequent communication of portfolio trends and insights to credit life cycle and regional management teams
  • Review the divisions loan portfolios at each phase of the credit life cycle (acquisition to collection) and ensure alignment to risk appetite / plan
  • Identify areas of opportunity to consolidate and streamline reporting activities and infrastructure
  • Strong analytical and credit risk or financial analysis background, including the ability to apply standard statistical techniques using SAS to extract and analyze data
  • At minimum four years’ experience in the Financial Services industry with particular experience in various analytical techniques for loan account origination and portfolio performance measurement and evaluation
  • Ability to innovatively and prudently manage portfolio risks through the development of controls systems that maximize profitability with an appropriate balance between growth and credit risk
  • Advanced level of experience with SAS and an ability to manage and organize information from a diverse range of data environments in order to interpret for management presentation purposes
  • Advanced level of experience with Excel
  • People management capabilities
6

Manager Credit Risk Analytics Resume Examples & Samples

  • Provide recommendations and support for strategic initiatives based on portfolio trends and insights, while collaborating with local business partners and IB retail risk teams
  • Deliver project based portfolio analyses that provide actionable insights to improve portfolio understanding and identify opportunities to improve risk/reward tradeoff
  • Influence business partners opinion towards strategic direction (growth/mitigation) by effectively communicating our risk appetite, risk tolerances, and early warning trends
  • At minimum four years’ experience in the Financial Services industry with particular experience in various analytical techniques for retail loan account origination and portfolio performance measurement and evaluation
  • High level of business acumen, with ability to do financial modelling and assess product profitability
7

Senior Manager, Credit Risk Analytics Resume Examples & Samples

  • Recommendations regarding stress testing and risk frameworks, polices and standards to govern stress testing in accordance with Senior Management, Board and regulatory requirements from multiple jurisdictions
  • Advising Senior Management and possibly the Board on the progress of the US credit stress testing program and the use of stress testing as a risk and business tool
  • Information Access: The job has the authority to access and use confidential data as it relates to the Enterprise’s Strategy, Risk Reporting and actual and plan Risk/Financial information. Information is detailed as well as synthesized for reporting to Senior Management committees and Board (BFC STSC, BFC CMC, RMC, & RRC)
  • Topical skills and knowledge
8

Credit Risk Analytics, Analyst Resume Examples & Samples

  • Strong analytical skills; ability to isolate and solve issues using large amounts of data
  • Ability to work effectively across organization lines
  • Basic understanding of financial loan system(s) and credit products
  • Undergraduate degree in accounting or finance
9

Director Counterparty Credit Risk Analytics Resume Examples & Samples

  • Providing overall exposure calculations (aggregation / collateral modelling), back testing methodology, on-boarding new trade types to the regressor framework
  • Improving the modelling sophistication to a level where the firm gains IMM approval from the US regulators
  • PhD in Maths / Physics or relevant topic (or potentially a good MSc)
  • Strong stochastic calculus, coding in C++ and preferably in Python
  • Good knowledge of general arbitrage theory and detailed knowledge of at least one asset class (Rates, FX, Credit, Equity or Commodities)
  • Experience in a CVA quant team would be ideal as the overlap would be substantial but knowledge of FO pricing models would be desired either from a FO quant perspective or from a Model Validation perspective
  • Ability to work well in groups, within and across functions
  • Ability to share information and adopting ideas of others when appropriate
  • Ability to express yourself clearly in written and spoken English
  • Experience from working in large C++ libraries, writing production code in both C++ and Python
10

Senior Manager Credit Risk Analytics Resume Examples & Samples

  • Working with other team members, support International Retail Risk reporting deliverables to ensure that all reporting is delivered on a timely basis with a high degree of accuracy
  • Develop both risk and financial models to further enhance the Portfolio Risk Ratings and improve International Banking assessment of risk appetite
  • Collaborate with cross-functional teams in Canada and Latin America to define best-practices on financial reporting and integration of financial and risk metrics
  • Evolve the management reporting process for Executives and the Board, to promote consistency and efficiency, while allowing flexibility in providing timely and relevant analytics based on current performance and/or specific strategies for each market
  • Provide input and support the development of on-going and new reporting and analysis. Lead analytical activities to create new reports to communicate insight effectively and support ongoing business requirements
  • Solicit feedback to ensure reports are not only providing information, but also insight that is valued by our business partners and/or executives
  • Support the Global Reporting and Analytics department in preparing both on-going and ad hoc reporting requests
  • Leads and contributes to team projects and continuous improvement initiatives
  • Minimum 5 years of proven experience in financial services role, with accounting and analytics experience for retail portfolios
  • Excellent communication and presentation skills – both verbal and written
  • Strong risk management knowledge and ability to succinctly communicate key priorities to stakeholders
  • Demonstrated ability to develop financial reporting, communication memos and interactive presentations
  • An understanding of accounting, performance and risk measurement concepts and methodologies
  • Excellent analytical skills and ability to interpret results for the business and derive insight
  • Intellectually curious, with strong business judgment
  • Solid interpersonal and organizational skills combined with the ability to readily adapt to rapidly changing business environments
11

Manager\senior Manager Credit Risk Analytics Resume Examples & Samples

  • Make recommendations on improvement of existing strategies, procedures and policies. Work closely with partners in Toronto and various countries to identify opportunities and drive changes to improve performance
  • Experience with credit risk policies and governance framework
  • Strong knowledge with statistical software packages (i.e. SAS, Angoss or equivalent) to perform data mining and to build credit risk strategies
  • Experience with credit risk decision systems (i.e. TRIAD, OMDM, TS2 or equivalent) is preferred
  • Proficient with use and/or development of credit risk scores and their applications
  • Project management skills to prioritize, manage and implement a variety of competing initiatives on a concurrent or staggered basis
  • Strong financial skills complemented with solid deductive reasoning, sound judgement, and creativity
  • Ability to communicate effectively, both oral and written in English/Spanish a must
12

VP Wholesale Credit Risk Analytics Resume Examples & Samples

  • The jobholder will implement measures to contain compliance risk across the business area. This will be achieved by liaising with Compliance department about business initiatives at the earliest opportunity. Also and when applicable, by ensuring adequate resources are in place and training is provided, fostering a compliance culture and optimising relations with regulators
  • Strong academic background with MS/PhD in a quantitative discipline such as Statistics, Econometrics, Mathematics
  • Solid understanding of commercial and counterparty derivative credit processes, including credit risk assessment and systems
  • Extensive knowledge of the Basel Capital Accord and US regulatory guidelines
13

Credit Risk Analytics Resume Examples & Samples

  • Masters in a math finance/ Masters in quantitative discipline with Derivatives math knowledge & experience. Working experience in a quantitative role in financial/consulting services with good understanding of derivatives' modelling/pricing, is a plus
  • Some Knowledge of unix & programming languages (e.g. C++ & Perl etc.)
  • No direct experience of counterparty risk calculations needed, but some knowledge of market risk management techniques are desirable
  • Knowledge of a wide range of derivative products (FI, Eqty, cmdty, FX, Credit) would be ideal but not a pre-requisite
  • Good communication skill is essential as the position requires quatifying risks and explaining them in a quick decision making enviornment
  • Eagerness & ability to grasp the complexity of structured derivatives quickly
14

VP-wholesale Credit Risk Analytics Resume Examples & Samples

  • Position functions as a technical expert at an individual contributor level
  • Aug 2010
  • On Balance Credit Exposure US$ XXX bn
  • Off Balance Sheet Credit Exposure US$ X tn
  • Strong communications, analytical, decision-making, lateral thinking and interpersonal skills
15

Team Lead, Credit Risk Analytics Resume Examples & Samples

  • Managing the CCAR Coporate and Institutional (C&I) Credit Stress Testing Modeling function
  • Managing a team with team members in multiple locations (global)
  • Developing, maintaining and executing statistical models related to the C&I credit segments in support of the quarterly capital adequacy assessment process at Northern Trust
  • Managing and executing the ongoing model performance monitoring of credit stress testing models
  • Ensuring quality control of the model development process
  • Working closely with the Model Validation, Model Governance functions and Audit function to address all modeling validation findings or Audit issues by deadline
  • Interacting with the Data Analytics team to request and ensure high quality data is utilized in the model development process
  • Communicate regularly with key business partners, management, and oversight committees and regulators by acting as a subject matter expert
  • 5+ years of experience developing and managing statistical models in banking or related industry
  • 3+ years of experience developing and managing CCAR C&I PD and LGD models including rating transition model at a Large and Complex bank
  • 2-3 years of experience managing a quantitative team
  • 3+ years of experience in CCAR regulatory examination to present quantitative model results to examiners and address regulatory questions and findings
  • Experience in Vendor stress testing models for C&I such as Credit Edge is a plus
  • Experience in Vendor Data such as S&P CreditPro and Moody’s DRD
  • Excellent analytical skills that include statistical analysis, model development and execution and attention to detail
  • Excellent experience using statistical programming languages such as SAS, SQL and R
  • Excellent oral and written communication skills, including presentation skills, the ability to create concise model documentation, as well as the ability to critically review and edit documents; a writing sample may be requested
  • Ability to effectively communicate with peers, senior management and overseas partners
  • Ability to work under pressure and organize, manage and prioritize multiple deliverables
  • Advanced degree (PhD is preferred) in statistics or equivalent quantitative field
16

Director, Credit Risk Analytics Resume Examples & Samples

  • Perform detailed analysis of consumer credit operations across industries such as financial services, power and utilities, and telecom
  • Analyze large datasets using econometric modeling and other business analysis tools such as SAS
  • Develop loan portfolio stress testing models using economic variables
  • Create consumer credit loss forecasting methodologies for clients and evaluate analytical models and methodologies used in consumer credit lending, account management, and collections
  • Identify and communicate technical matters to both clients and upper management
  • Write and present clear and concise reports and presentations to clients containing meaningful recommendations
  • Oversee engagement personnel
  • Regularly communicate with project sponsors and other interested client parties
  • Manage various facets of engagement including risk management, project acceptance, billing, delivery, and collections
  • Eight years of work experience with at least two years of experience at a major consulting firm
  • Quantitative academic background in Engineering, Operations Research, Physics, Mathematics, or Statistics from an accredited college/university; MBA, MS, or PhD from an accredited college/university preferred
  • Experience with complex multivariate modeling techniques used in the financial services industry
  • Knowledge of credit scoring, credit analytics, and loan loss reserving for retail and/or credit
  • Familiarity with underwriting and behavior scoring models, prepayment and loan account attrition models, loss forecasting, economic risk analysis, and other business analysis tools used in consumer and small business lending
  • Ten years of related work experience in a financial services or consulting firm
  • Well-established understanding of business dynamics and regulations
  • Established network of industry contacts and development opportunities
17

Credit Risk Analytics Internship Resume Examples & Samples

  • Pursuing an advanced degree in a quantitative discipline (e.g. Economics, Finance, Statistics, Mathematics)
  • Strong analytical and problem solving skills, coupled with thoroughness and attention to detail
  • Ability to work independently and proactively to address issues in a timely manner
  • Experience with MS Word, Excel, and PowerPoint
  • Programming experience in SAS (Base, STAT, and/or Enterprise Guide), R, MATLAB or another statistical programming package is a plus, but not required
18

Credit Risk Analytics Resume Examples & Samples

  • Responsible for developing and optimizing BB lending (product includes term loans, working capital line of credit- secured and unsecured, business credit card, equipment financing, SBA, etc.) risk strategies and evaluating their performance continuously and make adjustments as needed
  • The role will also be responsible for providing analytics support across credit risk lifecycle initiatives: originations, line management, portfolio/customer risk management, capital risk management, and collections & recovery
  • This includes leading and/or overseeing credit scoring/risk rating model development and BB transformation projects in support of key risk strategies
  • Responsible for applying credit risk expertise and analytical skills to drive sustainable and profitable growth strategies across Business Banking client continuum (covering micro businesses to medium businesses up to $25MM sales turn over) ensuring that they are operating within the boundaries of the credit risk appetite and bank's credit policy and standards
  • Performing granular analysis with attention to details overcoming small data sample challenges is important to the success of this position
  • The position requires application of quantitative and qualitative methods taking into consideration of Business Banking Risk dynamics and provides effective challenges on credit performance, emerging risks and business conformity with Bank's credit policy and standards
  • The analyst will lead and work as part of cross-functional teams (product, credit operations and finance) across the Bank and deliver quality results working in multiple projects and assignments at the same time
  • The ideal candidate will have demonstrated experience with any and all of the following: credit decision engine packages, statistical techniques, statistics software packages, small business/commercial risk assessment, retail and wholesale capital calculations, and data mining techniques
  • The candidate will be engaged in the implementation of credit decision engine projects (origination and portfolio management), ensuring all credit risk strategies are implemented in line with expectations
  • Responsible for supporting business intelligence initiatives in risk reporting and MIS capabilities. Responsible for supporting for Model Risk, Loss Forecasting, Capital Optimization/Management and ERM framework
  • Ad-hoc analytics support including tracking and managing portfolio risk performance in line with Bank's credit policy and stated Risk Appetite objectives
  • Developing and deploying BB credit risk predictive solutions and market leading strategies to improve automation, efficiencies and lending experience for the entire customer risk life cycle
  • Masters or Ph.D. or equivalent experience with emphasis in data science or rel quant or stat/data analysis or op research or decision mgmt
  • 5 - 7 Years Specialized Knowledge
  • Ability conceptualize and execute analytical work based on broad business objectives
  • Ability to work with large scale data to derive insights through data analysis, optimization or risk classification algorithms
  • Exceptional problem solving, organizational and process improvement skills. Knowledge of logistic regression, classification algorithms, credit risk scoring, decision management in banking or credit card industry
  • Knowledge of retail and commercial credit policy, capital risk (PD, LGD and EAD) modeling in retail or commercial portfolio preferred
  • Predictive tools including regression, optimization/decision tree algorithms, SAS, Scoring/Decision Support System, Credit Risk, Capital Calculations, BASEL framework. Strong analytics background with attention to details to deliver quality results
19

Business Banking Credit Risk Analytics Internship Resume Examples & Samples

  • Currently Enrolled in an accredited degree program (strong preference for Economics/Statistics/Mathematics or other quantitative discipline); will be a senior next August
  • Cumulative GPA is 3.0 or above (preferably 3.5 or above)
  • Highly motivated and results oriented with a desire to exceed expectations
  • Excellent communication skills with the ability to express facts and ideas clearly both verbally and in writing, interacting professionally, transparently and effectively with people at all levels
  • Intellectual curiosity ; a desire to understand the drivers behind business problems and challenge the status quo
  • The ideal candidate will have demonstrated experience with one or more programming languages (For example, HTML/VBA/SQL/Java/C++ etc.)
  • Basic proficiency in Microsoft Excel (e.g. pivot tables/filtering/sorting/charting)
20

Modeler, Credit Risk Analytics Resume Examples & Samples

  • Monitors and validates current scores regularly; documents results
  • Makes recommendations regarding when scores should be redeveloped
  • Documents modeling and analysis processes and results for internal and regulatory purposes
  • Researches industry trends in analytical approach and new techniques to enhance predictive modeling capability
  • Tests/analyzes new methodologies
  • May evaluate new scores from vendors by performing cost/benefit analysis
  • May evaluate new products from vendors by performing cost/benefit analysis
  • Translates analytical results into useful recommendations that increase bottom line profit
  • Provides support for implementation of solutions
  • Monitors impact of solutions that are implemented
  • 1-2 years of hands-on experience with statistical techniques such as generalized linear models, clustering, segmentation, multivariate analysis, and time series required
  • 3-5 years experience in gathering and/or analyzing financial data required
  • Master Degree in Statistics, Math, or other Quantitative fields required
  • Experience in the credit card or finance industry preferred
  • Underwriting, Collections and/or Fraud experience preferred
  • 2-5 years experience with SAS and SQL preferred
  • Ability to organize tasks and meet established deadlines
  • Ability to research and analyze and provide recommendations
  • Ability to identify and resolve problems with statistical models
  • Thorough knowledge of statistical software and techniques
  • Ability to organize/manage multiple projects simultaneously
  • Good presentation skills
  • Proficient in MS Office
  • Enjoys collaborative efforts and maintains a positive attitude
21

Manager of Credit Risk Analytics Resume Examples & Samples

  • Partners with the Credit Risk Executive and other business leaders to evolve Credit Risk Analytics strategies
  • Lead statistical modeling team in start-to-finish development/assessment of credit loss and other forecasting models, including Allowance for Loan and Lease Losses and Dodd-Frank Stress Testing
  • Work with multiple complex data sources, and identify new data sources for business insights and significant improvements in predictive capabilities
  • Collaborate with the internal technology and project management teams to implement and deploy solutions for real-time decisions
  • Support business requests which require statistical analysis from management team and other departments within the company. Seek out and evaluate appropriate methods and techniques for translating data into information, insights and strategies
  • Designs project plans with clear objectives, detailed tasks, accountabilities and timelines
  • Provide training, guidance, and assistance to team members, which include Model Development, Allowance for Loan and Lease Losses, and Documentation roles
  • Interact with external and internal auditors, regulators, and model risk management staff
  • Lead the quarterly Allowance for Loan and Lease Losses process and committee meeting including interfacing with the Bank’s Loan Loss Reserve Committee members and making recommendations for quarter end reserve levels
  • 7-10 years of experience in analytics with progressive leadership experience in leading cross­functional programs
  • Strongly preferred: Degree in a quantitative subject, such as mathematics, computer science, statistics, economics or a related field
  • Fluent in variety of statistical and machine learning approaches, including regressions, and loss estimation techniques
22

Lead Credit Risk Analytics Manager Resume Examples & Samples

  • You will have lots of experience in the financial services and a depth of knowledge in credit risk, having previously worked in a bank within Risk
  • You will be proficient in a statistical program language i.e. SAS, SQL, R, Matlab, SPSS and VBA as well as Microsoft office
  • An experienced and confident leader, the ability to support and guide colleagues on all matters relating to credit risk and modelling
23

SVP, Credit Risk Analytics & Modeling Resume Examples & Samples

  • Develop models and oversee model development, validation, and deployment efforts
  • Work with large datasets and complex algorithms to solve data science challenges
  • Leverage big data to develop innovative deployable solutions
  • Help introduce best-in-class, cutting edge machine learning techniques to drive profitability through innovation
  • Ensure timely model performance tracking, and assist in process automation to drastically improve process/operation efficiencies (where possible) that will enable the business to make rapid credit decisions against market condition changes
  • Support the development of training curriculum and standards
  • Partner with Risk and Decision Management organizations to understand the source of new data and continue to improve the process of defining, extracting and utilizing the new data
  • Interact with senior levels of management to facilitate understanding of usage of credit risk models and inform critical decisions
  • Provide leadership and guidance for junior modelers
  • Bachelor’s Degree required in statistics, mathematics, engineering, physics, economics, or related quantitative discipline (Masters or Ph’d degrees preferred)
  • 8+ years experience in risk management, statistical modeling, model management or other relevant field (or 7+ years experience with Master’s Degree or PhD). People management experience preferred but not required
  • 3+ years managing staff (direct or indirect)
  • Sound knowledge of statistical modeling concepts and industry best practices; experience with econometric and statistical modeling or application risk scoring
  • Experience with analytical or data manipulation tools (e.g. SAS, SQL, R, C Programming in UNIX)
  • Ability to deliver compelling presentations and influence executive audiences
  • Excellent communicator; ability to engage and inspire team forward
  • Ability to drive innovation via thought leadership while maintaining end-to-end view
  • Effective cross-functional project, resource, and stakeholder management; effectively engage with internal audit and external regulators
  • Understanding of key drivers of decisioning, such as Strategic Plan, CCAR and Risk Appetite Framework (RAF), as well as in-depth knowledge of the Cards business P&Ls and risk management concepts and practices a plus
  • Prior experience in using advanced machine learning tools etc. in any data intensive role (Financial services experience not required)
  • Experience working in Big data environments; Intellectual curiosity to stay abreast of technological advances
24

Avp-small Business Credit Risk Analytics Resume Examples & Samples

  • This position may act as a first level manager or as the most senior level individual contributor/ subject matter expert
  • This position may also work with other support teams such as Vendor Management and/or Technology Services
  • Five years proven statistical analysis and/or MIS experience, or equivalent. Management experience as well as knowledge and understanding of financial services preferred
  • Well-developed organizational, analytical, problem-solving, project management and verbal and written communication skills
  • Proficiency with personal computers as well as pertinent mainframe systems and software packages. Strong programming skills to include knowledge of statistical programs (i.e. SAS, SAP) and/or advanced database programs
25

Senior RCA Manager Enterprise Credit Risk Analytics Resume Examples & Samples

  • Responsible for leading a team of professionals to oversee risk management of the Bank’s wholesale credit portfolio, including the identification and ongoing monitoring of current and emerging risks, and escalation to key stakeholders where appropriate
  • This individual ensures that credit concentrations are effectively identified and monitored, and associated board-reportable risk limits are reported in a timely manner
  • The team led by this individual is responsible for emerging risk monitoring and reporting which entails extensive collaboration with internal partners in Credit Risk Management as well as subject matter experts in the various Lines of Business, along with responsibility for developing research and insightful analysis of current macro and micro economic trends, industry risks and geographic risks
  • As the leader of this group, this individual will need to ensure that the team leverages appropriate data sources and maintains data integrity, and is audit-ready with regard to data governance policies and procedures
  • Expert knowledge of applicable regulatory and internal policy requirements and identification of gaps as applicable is essential, along with the ability to recommend action(s) to be taken to remedy any issues identified
  • Also responsible for frequent ad hoc, and often highly visible projects to assess risk on a bankwide basis from current or emerging risk issues
  • The analyses and reports maintained by the team are distributed widely throughout the bank to ensure lenders and credit approvers effectively manage credit portfolios in line with the Bank’s risk appetite, and that senior and executive management is apprised in a timely manner of key portfolio risks
  • 15 or more years of experience in an applicable risk management environment
  • Considerable knowledge of applicable laws, regulations, financial services, and regulatory trends that impact their assigned line of business
  • Considerable knowledge of the business line’s operations, products/services, systems, and associated risks/controls
  • Expert knowledge of Risk/Compliance/Audit competencies
  • Ability to manage job scope and complexity of assigned business at the departmental and/or division level
  • Strong leadership and management skills of processes, projects and people
  • Strong analytical, problem-solving and negotiation skills
26

Senior Mgr, Credit Risk Analytics Resume Examples & Samples

  • Monitor risk performance of specific clients and complete required analysis; ensure the organization maximizes profit within the contractual terms for each client by managing analysis of portfolio trends and forecasting performance concerning score cut-offs, profitability, bad debt losses, general portfolio dynamics, and bureau scoring criteria
  • Ensure accurate and complete analysis, including interpreting data and communicating results and recommendations to management, for on-going projects such as cut-off review, champion/challenger programs, and risk-based pricing update (supervisory responsibility)
  • Develop Credit Risk Analysts by setting up processes for training, reviewing work, and providing feedback to enhance their analytical skills. Ensure analysts have the tools, skills, and knowledge to access required data
  • Design and develop risk management policies to maintain maximum protection of the organization’s assets. Consult with other Credit Risk Managers to determine best practices regarding analytics, risk criteria, and policies/procedures
  • Manage day-to-day client inquiries and communicate risk management role, processes, policies, and procedures to internal stakeholders like Client Sales, Marketing, and Operations
  • Educate analysts on the big picture of the credit card business and Credit Risk’s role in its success
  • Ensure monthly reporting necessary to understand changes in application and portfolio risk mix is effectively completed and presented to senior management and internal partners
  • Bachelor’s Degree in Finance, Statistics, Accounting, Business and/or equivalent knowledge or experience
  • Minimum of five years of experience performing portfolio analysis of credit card files
  • 2+ years of experience leading or supervising other team members
  • Initiate, coordinate, & implement department-wide projects
  • Thorough knowledge of credit card business (operation, regulatory, sales/marketing, etc.) & understanding of what drives profit
  • Thorough knowledge of P&L calculations
  • Knowledge of current technologies and practices associated with credit risk management
  • Strong SAS, SQL, and Essbase skills
  • Ability to creatively solve problems with innovative solutions
  • Management and leadership abilities
  • Ability to analyze data trends, form conclusions and recommendations based on those analyses
  • Intermediate proficiency in Excel; basic level of Word and PowerPoint
  • Presentation (both written and oral) skills to provide analysis results to upper management
  • Ability to communicate results and risk concepts to groups that may not be as data savvy
  • Ability to provide constructive and consistent feedback to analysts to develop their skills