Christopher Moore has over 15 years of experience in risk management, data analytics, and portfolio monitoring. He currently leads a model risk management team at JP Morgan Chase responsible for model validation, governance, and performance monitoring. Prior to this role, he managed teams and led projects related to Basel capital requirements, fraud prevention, and risk strategy. Moore has a strong technical background and experience implementing predictive models, scorecards, and automated reporting solutions.
Daniel Kocis provides quantitative advisory services and statistical modeling for consumer financial industries using large datasets and advanced analytics. He has developed risk models, reports, and strategies for several large financial clients to optimize processes like new customer acquisition, cross-selling, and default analysis. Kocis also builds statistical models to analyze consumer credit behaviors and predict future risks using credit bureau and payment data.
Mark Frank has over 15 years of experience in business intelligence, analytics, and strategy roles. He currently works as a Business Intelligence/Analytics Manager at Wells Fargo Bank, where he manages an analytical team supporting the Wealth Management division. Previously, he held BI and strategy roles at Wells Fargo in their Wealth and Home Equity divisions. He has expertise in SQL, data modeling, analytics for marketing, risk management, and more.
Credit Audit's Use of Data Analytics in Examining Consumer Loan PortfoliosJacob Kosoff
Written by Jacob Kosoff and published in September 2013 by the RMA Journal. This article describes banks in 2012 & 2013 were modernizing their Credit Review functions.
This document provides a summary of John Lazcano's expertise and experience in risk analysis and regulatory compliance. It lists his areas of expertise as structured credit, stress testing, validation, compliance, audit, CCAR, regulatory issues, and Dodd-Frank/Basel regulations. It then gives an overview of his background in credit risk analysis and comparative risk assessment across industries. Finally, it outlines his extensive experience in model validation, risk reporting, stress testing, data management, and ensuring regulatory compliance at financial institutions.
Adopting a Top-Down Approach to Model Risk Governance to Optimize Digital Tra...Jacob Kosoff
Model risk management programs often began their journey by first creating a definition of a model. Then model risk groups would perform model risk activities on each item that met the definition of a model. These model risk activities include classifying risk, assessing current uses, evaluating ongoing monitoring results, validating conceptual soundness, testing model changes, and so forth. This approach was an important beginning for the field of model risk management as it helped identify existing models, discover fundamental errors in existing models, and prevent inappropriate use of models. However, model risk teams often focused only on processes that already include models and did not identify processes that would be significantly improved by using models. This results in model risk teams overlooking modeling capabilities that a process truly needs. However, model risk teams can go on the offensive and use their model inventory as a source of crucial business intelligence. Model risk teams can start to identify processes that do not include models and could recommend the use of existing models to improve those processes. Furthermore, model risk teams can reduce expenses at a bank by guarding against the development or purchase of models with redundant capabilities. Model risk management teams can ultimately be a champion for the extensibility and efficient use of models at an institution. The article was written by Jacob Kosoff, Aaron Bridgers, and Henry Lee. The article was published by the RMA Journal in September 2020.
Scoring technology analyzes historical client data to identify links between client characteristics and behaviors. It uses these links to predict how clients will act and help microfinance institutions (MFIs) make more reliable loan, marketing, and collections decisions. Scoring develops scorecards that loan officers use to assign scores predicting client behaviors like default risk. Scoring improves decision-making efficiency, allows for pricing loans based on individual risk, and lays the foundation for advanced risk management. While beneficial, scoring requires significant data, staff time, and expenses to develop properly and ensure effective implementation and monitoring. Several MFIs have implemented scoring successfully with the help of consultants.
This document discusses considerations for building out model risk management (MRM) frameworks for qualitative models at banks. It begins by defining qualitative models as those where the functional specification is determined primarily by expert judgment or assumptions rather than quantitative methodologies.
It notes that while qualitative models pose model risk, approaches to managing this risk may differ from quantitative models due to different risk sources. Specifically, staffing, scheduling, scope and inventory size of MRM programs may vary significantly between large global banks and regional banks based on factors like resources. Regional banks especially may need to validate qualitative and quantitative models using the same team.
The document provides examples of how existing risk management processes at regional banks could take on aspects of qualitative model validation to
Daniel Kocis provides quantitative advisory services and statistical modeling for consumer financial industries using large datasets and advanced analytics. He has developed risk models, reports, and strategies for several large financial clients to optimize processes like new customer acquisition, cross-selling, and default analysis. Kocis also builds statistical models to analyze consumer credit behaviors and predict future risks using credit bureau and payment data.
Mark Frank has over 15 years of experience in business intelligence, analytics, and strategy roles. He currently works as a Business Intelligence/Analytics Manager at Wells Fargo Bank, where he manages an analytical team supporting the Wealth Management division. Previously, he held BI and strategy roles at Wells Fargo in their Wealth and Home Equity divisions. He has expertise in SQL, data modeling, analytics for marketing, risk management, and more.
Credit Audit's Use of Data Analytics in Examining Consumer Loan PortfoliosJacob Kosoff
Written by Jacob Kosoff and published in September 2013 by the RMA Journal. This article describes banks in 2012 & 2013 were modernizing their Credit Review functions.
This document provides a summary of John Lazcano's expertise and experience in risk analysis and regulatory compliance. It lists his areas of expertise as structured credit, stress testing, validation, compliance, audit, CCAR, regulatory issues, and Dodd-Frank/Basel regulations. It then gives an overview of his background in credit risk analysis and comparative risk assessment across industries. Finally, it outlines his extensive experience in model validation, risk reporting, stress testing, data management, and ensuring regulatory compliance at financial institutions.
Adopting a Top-Down Approach to Model Risk Governance to Optimize Digital Tra...Jacob Kosoff
Model risk management programs often began their journey by first creating a definition of a model. Then model risk groups would perform model risk activities on each item that met the definition of a model. These model risk activities include classifying risk, assessing current uses, evaluating ongoing monitoring results, validating conceptual soundness, testing model changes, and so forth. This approach was an important beginning for the field of model risk management as it helped identify existing models, discover fundamental errors in existing models, and prevent inappropriate use of models. However, model risk teams often focused only on processes that already include models and did not identify processes that would be significantly improved by using models. This results in model risk teams overlooking modeling capabilities that a process truly needs. However, model risk teams can go on the offensive and use their model inventory as a source of crucial business intelligence. Model risk teams can start to identify processes that do not include models and could recommend the use of existing models to improve those processes. Furthermore, model risk teams can reduce expenses at a bank by guarding against the development or purchase of models with redundant capabilities. Model risk management teams can ultimately be a champion for the extensibility and efficient use of models at an institution. The article was written by Jacob Kosoff, Aaron Bridgers, and Henry Lee. The article was published by the RMA Journal in September 2020.
Scoring technology analyzes historical client data to identify links between client characteristics and behaviors. It uses these links to predict how clients will act and help microfinance institutions (MFIs) make more reliable loan, marketing, and collections decisions. Scoring develops scorecards that loan officers use to assign scores predicting client behaviors like default risk. Scoring improves decision-making efficiency, allows for pricing loans based on individual risk, and lays the foundation for advanced risk management. While beneficial, scoring requires significant data, staff time, and expenses to develop properly and ensure effective implementation and monitoring. Several MFIs have implemented scoring successfully with the help of consultants.
This document discusses considerations for building out model risk management (MRM) frameworks for qualitative models at banks. It begins by defining qualitative models as those where the functional specification is determined primarily by expert judgment or assumptions rather than quantitative methodologies.
It notes that while qualitative models pose model risk, approaches to managing this risk may differ from quantitative models due to different risk sources. Specifically, staffing, scheduling, scope and inventory size of MRM programs may vary significantly between large global banks and regional banks based on factors like resources. Regional banks especially may need to validate qualitative and quantitative models using the same team.
The document provides examples of how existing risk management processes at regional banks could take on aspects of qualitative model validation to
William B. Matthews has over 15 years of experience in business analysis, project management, risk assessment, and data analysis in the insurance and financial services industries. He holds an MBA in Finance and a BS in Marketing. His technical skills include Tableau, SharePoint, SAP, Microsoft Office, Oracle, and Crystal Reports. Currently he is a Business Information Analyst at Wells Fargo where he develops reports and conducts analyses to support various teams. Previously he held data analyst roles at Sedgwick and Allstate Insurance where he prepared reports, evaluated claims coding, and conducted pricing and risk analysis.
Stress testing has long been used in risk management but post-financial crisis regulations require more stringent stress testing programs. Banks must assess capital needs to withstand deteriorating economies or shocks. Navigant assists clients in meeting stress testing and capital planning requirements through risk identification, scenario analysis, loss projection, data quality reviews, model validation, and technology selection and implementation. Navigant's services help financial institutions improve planning, risk assessment, and regulatory reporting capabilities.
Scott Schaumburg is a senior risk data analyst with over 20 years of experience in risk mitigation and analysis for large banking institutions. He has extensive experience leading complex risk analysis projects, developing risk models, managing large data sets, and ensuring regulatory compliance. Most recently, he worked as a consultant automating a bank's risk processes and as Vice President of CCAR Management and Risk Management at BBVA Compass Bank, where he successfully led critical projects to improve reporting and risk analytics.
Understanding and validating the uses of machine learning modelsJacob Kosoff
WHILE MACHINE LEARNING (ML) CAN OFFER THE BENEFIT OF IMPROVED MODEL RESULTS, A BANK SHOULD CONSIDER WHETHER IT IS APPROPRIATE TO ACCEPT THE ADDITIONAL COMPLEXITY, AS WELL AS THE TESTING AND MONITORING, INVOLVED. THIS ARTICLE DISCUSSES BEST PRACTICES IN PERFORMING VALIDATIONS OF MACHINE LEARNING MODELS.
Written by Shannon Kelly of Zions Bank, Jacob Kosoff of Regions Bank, Agus Sudjianto of Wells Fargo, and Aaron Bridgers of Regions Bank.
Vishal Raj Addigi is seeking a challenging role in business analysis and client servicing. He has over 4 years of experience in roles like business analyst for wealth management, investment banking, and asset servicing. He has expertise in areas like requirements gathering, documentation, testing, and change management. Some of his achievements include initiating and enhancing applications for regulatory risk projects at UBS. He is proficient in applications like Charles River trading system and has experience in trade life cycles and software development processes.
Prometeia distinguishes its approach by consistently
pursuing state of the art methodologies, with a fully
dedicated team of econometricians and financial
specialists with broad experience in developed and
emerging markets.
Our internally developed methodologies are constantly
updated with the best practices and entirely integrated
into the ERMAS Suite, enabling banks to take a
proactive approach towards risk management and
increasing profitability.
This document contains the resume of Debbie Wolford, which summarizes her experience in project management, business analysis, quality assurance, and technical skills. She has over 20 years of experience in the mortgage industry, working with companies like Citizens Bank, Citigroup, and HSBC. Her areas of expertise include project management, business process modeling, testing, and working with offshore teams.
This resume summarizes the experience of C.S. Ganti as an applied statistician and predictive modeler. Over his career, Ganti has developed statistical models for various insurance and government organizations to help reduce costs and improve business operations, including models to track commercial losses, define risk profiles, and estimate subrogation recoveries. His models have achieved cost savings ranging from 75-88% by improving efficiency. Ganti has extensive experience applying techniques like regression analysis, probability distributions, and simulations to solve business problems in insurance and other industries.
John Lazcano has over 15 years of experience in credit risk analysis and financial modeling. He has worked at large financial institutions such as Citibank, GE Capital, and JP Morgan Chase assessing credit risk and modeling loan performance. Currently, he is pursuing his MBA in finance from NYU Stern School of Business with a focus on further developing his analytical and modeling skills.
Moderating the Churn: Retaining employees in the quantitative banking spaceJacob Kosoff
This article describes strategies on how to attract, develop and retain data scientists and other individuals with strong quantitative and data skills. Regions Model Risk Management and Validation has benefited from under 10% external turnover for the past five years and the article discusses how we at Regions has reached that success. Written by Jacob Kosoff and Irina Pritchett.
This document provides a summary of a business analyst with over 7 years of experience. The summary highlights the following key points:
- Experienced business analyst with skills in requirements gathering, documentation, process analysis, quality assurance, and system testing.
- Technical skills include SAP, Oracle, SQL Server, UML, Agile/Scrum methodologies, and Microsoft development tools.
- Industry experience includes insurance, healthcare, retail, banking, and finance. Has worked on projects involving systems integration, financial reporting, and portfolio management.
- Current role involves requirements analysis, documentation, testing, and project management for financial software projects at a bank. Previous experience includes similar roles in the insurance and financial industries
A Review of BCBS 239: Helping banks stay compliantHEXANIKA
Although the challenge to comply with BCBS 239 is vital, the scope is immense. Now that the Jan 2016 deadline for the G-SIBs is up, the rule is expected to extend to other financial institutions and banks. The principles will also apply to all key internal risk management models including market, credit, and counterparty risk. Establishing the principle guidelines and putting core capabilities in place has its merits.
The clarity that effective risk data aggregation provides will help banks streamline their businesses, and can allow banks to make better judgments through more accurate risk analysis. Aggregated information across all channels will enable to provide comprehensive support and services to existing customers. The robust data framework also helps banks supervise and anticipate future problems, giving them a clear view for data analysis.
It can lead to gains in efficiency, reduce probability of losses and enhance strategic decision making, ultimate benefiting a bank’s profitability.
This document contains the resume of Debbie Wolford, which summarizes her experience in project management, business analysis, quality assurance, and technical roles over 20 years. She has extensive experience working with mortgage lending platforms, global banking systems, and offshore teams on various improvement projects. The resume lists her areas of expertise and provides details on her contract work and full-time positions.
This document provides a summary of Ahmed Alsharit's skills and experience. It outlines his 6 years of experience in business intelligence, report development, and database development. It also lists his technical skills in Microsoft technologies, databases, designs, interfaces, and electronic health records. His educational background includes a Doctorate in Health Administration and a Master's in Health Informatics. His professional experience includes roles in payor contracting, coding data analysis, business technology analysis, data analysis, and claims support.
Anita Sands has over 20 years of experience in financial services, technology, and local government. She has a proven track record of leading strategic initiatives, improving processes, and implementing enterprise systems. Her strengths include business analysis, project management, financial planning, and developing policies and procedures.
FACT is a flexible credit risk management solution with three core elements: framework, data, and models. It integrates efficiently with existing workflows and can integrate and map data from multiple internal and external sources. Users can create their own scoring and analytical models or use FACT's integrated models. FACT provides a scalable, secure, and reliable solution to manage credit risk through financial analysis, ratings, modeling, and credit application workflow configuration. Expert teams customize and configure FACT to a user's specific needs and requirements.
The document provides details on Jason Hah's professional experience in financial planning and analysis, project management, systems implementation, and business process reengineering in the banking industry. It highlights his extensive experience in areas such as financial forecasting, budgeting, revenue analysis, activity-based costing, and financial modeling. It also summarizes his proven track record in Oracle ERP implementation and customizing systems to automate financial data reconciliation and reporting. His expertise includes Basel II credit risk calculations, mergers and acquisition integration planning, and creating automated dashboards for management.
Karyn Lentz is an accomplished risk manager with over 20 years of experience developing risk models, scorecards, and strategies. She is relocating to the Dallas/Fort Worth area and is seeking a new position. She has extensive experience developing models using both traditional and alternative data sources to evaluate risk across the customer lifecycle for auto lending. Her background includes positions at several large auto finance companies where she led teams and delivered significant results in model development, strategy implementation, and decision system programming.
The document provides a profile summary for an individual with over 14 years of experience in operations management, project management, resource management, mortgage underwriting, data analysis, and risk management. Key experiences include managing mortgage operations at Morgan Stanley, loan validation and underwriting at TCS for Citigroup, and sales experience. Educational background includes an MBA in Finance and Bachelor's in Mechanical Engineering. Skill sets include mortgage underwriting, operations management, process optimization, data analysis, risk analysis, and team leadership.
Nielson 2013 MS NUCE Thesis - Thorium Fuel CycleRyan Nielson
This document discusses the advantages and challenges of thorium fuel cycles compared to uranium fuel cycles. Thorium presents several advantages including larger reserves than uranium, increased proliferation resistance due to producing lower quantities of weapons-usable material, and potential reductions in fuel cycle costs and nuclear waste. However, the thorium fuel cycle also faces challenges as it has not yet been commercially adopted due to a lack of development and higher associated economic costs compared to established uranium fuel cycles.
This document discusses models for understanding disease causation. It begins by defining disease and the concept of disease causation. It then describes the traditional epidemiological triad model comprising a susceptible host, disease agent, and environment allowing host-agent interaction. Living and non-living disease agents are categorized. The document continues by exploring factors that determine host susceptibility and the properties of disease agents. Finally, it introduces the wheel of causation and causal web models, emphasizing the complex interplay between multiple factors in disease development.
William B. Matthews has over 15 years of experience in business analysis, project management, risk assessment, and data analysis in the insurance and financial services industries. He holds an MBA in Finance and a BS in Marketing. His technical skills include Tableau, SharePoint, SAP, Microsoft Office, Oracle, and Crystal Reports. Currently he is a Business Information Analyst at Wells Fargo where he develops reports and conducts analyses to support various teams. Previously he held data analyst roles at Sedgwick and Allstate Insurance where he prepared reports, evaluated claims coding, and conducted pricing and risk analysis.
Stress testing has long been used in risk management but post-financial crisis regulations require more stringent stress testing programs. Banks must assess capital needs to withstand deteriorating economies or shocks. Navigant assists clients in meeting stress testing and capital planning requirements through risk identification, scenario analysis, loss projection, data quality reviews, model validation, and technology selection and implementation. Navigant's services help financial institutions improve planning, risk assessment, and regulatory reporting capabilities.
Scott Schaumburg is a senior risk data analyst with over 20 years of experience in risk mitigation and analysis for large banking institutions. He has extensive experience leading complex risk analysis projects, developing risk models, managing large data sets, and ensuring regulatory compliance. Most recently, he worked as a consultant automating a bank's risk processes and as Vice President of CCAR Management and Risk Management at BBVA Compass Bank, where he successfully led critical projects to improve reporting and risk analytics.
Understanding and validating the uses of machine learning modelsJacob Kosoff
WHILE MACHINE LEARNING (ML) CAN OFFER THE BENEFIT OF IMPROVED MODEL RESULTS, A BANK SHOULD CONSIDER WHETHER IT IS APPROPRIATE TO ACCEPT THE ADDITIONAL COMPLEXITY, AS WELL AS THE TESTING AND MONITORING, INVOLVED. THIS ARTICLE DISCUSSES BEST PRACTICES IN PERFORMING VALIDATIONS OF MACHINE LEARNING MODELS.
Written by Shannon Kelly of Zions Bank, Jacob Kosoff of Regions Bank, Agus Sudjianto of Wells Fargo, and Aaron Bridgers of Regions Bank.
Vishal Raj Addigi is seeking a challenging role in business analysis and client servicing. He has over 4 years of experience in roles like business analyst for wealth management, investment banking, and asset servicing. He has expertise in areas like requirements gathering, documentation, testing, and change management. Some of his achievements include initiating and enhancing applications for regulatory risk projects at UBS. He is proficient in applications like Charles River trading system and has experience in trade life cycles and software development processes.
Prometeia distinguishes its approach by consistently
pursuing state of the art methodologies, with a fully
dedicated team of econometricians and financial
specialists with broad experience in developed and
emerging markets.
Our internally developed methodologies are constantly
updated with the best practices and entirely integrated
into the ERMAS Suite, enabling banks to take a
proactive approach towards risk management and
increasing profitability.
This document contains the resume of Debbie Wolford, which summarizes her experience in project management, business analysis, quality assurance, and technical skills. She has over 20 years of experience in the mortgage industry, working with companies like Citizens Bank, Citigroup, and HSBC. Her areas of expertise include project management, business process modeling, testing, and working with offshore teams.
This resume summarizes the experience of C.S. Ganti as an applied statistician and predictive modeler. Over his career, Ganti has developed statistical models for various insurance and government organizations to help reduce costs and improve business operations, including models to track commercial losses, define risk profiles, and estimate subrogation recoveries. His models have achieved cost savings ranging from 75-88% by improving efficiency. Ganti has extensive experience applying techniques like regression analysis, probability distributions, and simulations to solve business problems in insurance and other industries.
John Lazcano has over 15 years of experience in credit risk analysis and financial modeling. He has worked at large financial institutions such as Citibank, GE Capital, and JP Morgan Chase assessing credit risk and modeling loan performance. Currently, he is pursuing his MBA in finance from NYU Stern School of Business with a focus on further developing his analytical and modeling skills.
Moderating the Churn: Retaining employees in the quantitative banking spaceJacob Kosoff
This article describes strategies on how to attract, develop and retain data scientists and other individuals with strong quantitative and data skills. Regions Model Risk Management and Validation has benefited from under 10% external turnover for the past five years and the article discusses how we at Regions has reached that success. Written by Jacob Kosoff and Irina Pritchett.
This document provides a summary of a business analyst with over 7 years of experience. The summary highlights the following key points:
- Experienced business analyst with skills in requirements gathering, documentation, process analysis, quality assurance, and system testing.
- Technical skills include SAP, Oracle, SQL Server, UML, Agile/Scrum methodologies, and Microsoft development tools.
- Industry experience includes insurance, healthcare, retail, banking, and finance. Has worked on projects involving systems integration, financial reporting, and portfolio management.
- Current role involves requirements analysis, documentation, testing, and project management for financial software projects at a bank. Previous experience includes similar roles in the insurance and financial industries
A Review of BCBS 239: Helping banks stay compliantHEXANIKA
Although the challenge to comply with BCBS 239 is vital, the scope is immense. Now that the Jan 2016 deadline for the G-SIBs is up, the rule is expected to extend to other financial institutions and banks. The principles will also apply to all key internal risk management models including market, credit, and counterparty risk. Establishing the principle guidelines and putting core capabilities in place has its merits.
The clarity that effective risk data aggregation provides will help banks streamline their businesses, and can allow banks to make better judgments through more accurate risk analysis. Aggregated information across all channels will enable to provide comprehensive support and services to existing customers. The robust data framework also helps banks supervise and anticipate future problems, giving them a clear view for data analysis.
It can lead to gains in efficiency, reduce probability of losses and enhance strategic decision making, ultimate benefiting a bank’s profitability.
This document contains the resume of Debbie Wolford, which summarizes her experience in project management, business analysis, quality assurance, and technical roles over 20 years. She has extensive experience working with mortgage lending platforms, global banking systems, and offshore teams on various improvement projects. The resume lists her areas of expertise and provides details on her contract work and full-time positions.
This document provides a summary of Ahmed Alsharit's skills and experience. It outlines his 6 years of experience in business intelligence, report development, and database development. It also lists his technical skills in Microsoft technologies, databases, designs, interfaces, and electronic health records. His educational background includes a Doctorate in Health Administration and a Master's in Health Informatics. His professional experience includes roles in payor contracting, coding data analysis, business technology analysis, data analysis, and claims support.
Anita Sands has over 20 years of experience in financial services, technology, and local government. She has a proven track record of leading strategic initiatives, improving processes, and implementing enterprise systems. Her strengths include business analysis, project management, financial planning, and developing policies and procedures.
FACT is a flexible credit risk management solution with three core elements: framework, data, and models. It integrates efficiently with existing workflows and can integrate and map data from multiple internal and external sources. Users can create their own scoring and analytical models or use FACT's integrated models. FACT provides a scalable, secure, and reliable solution to manage credit risk through financial analysis, ratings, modeling, and credit application workflow configuration. Expert teams customize and configure FACT to a user's specific needs and requirements.
The document provides details on Jason Hah's professional experience in financial planning and analysis, project management, systems implementation, and business process reengineering in the banking industry. It highlights his extensive experience in areas such as financial forecasting, budgeting, revenue analysis, activity-based costing, and financial modeling. It also summarizes his proven track record in Oracle ERP implementation and customizing systems to automate financial data reconciliation and reporting. His expertise includes Basel II credit risk calculations, mergers and acquisition integration planning, and creating automated dashboards for management.
Karyn Lentz is an accomplished risk manager with over 20 years of experience developing risk models, scorecards, and strategies. She is relocating to the Dallas/Fort Worth area and is seeking a new position. She has extensive experience developing models using both traditional and alternative data sources to evaluate risk across the customer lifecycle for auto lending. Her background includes positions at several large auto finance companies where she led teams and delivered significant results in model development, strategy implementation, and decision system programming.
The document provides a profile summary for an individual with over 14 years of experience in operations management, project management, resource management, mortgage underwriting, data analysis, and risk management. Key experiences include managing mortgage operations at Morgan Stanley, loan validation and underwriting at TCS for Citigroup, and sales experience. Educational background includes an MBA in Finance and Bachelor's in Mechanical Engineering. Skill sets include mortgage underwriting, operations management, process optimization, data analysis, risk analysis, and team leadership.
Nielson 2013 MS NUCE Thesis - Thorium Fuel CycleRyan Nielson
This document discusses the advantages and challenges of thorium fuel cycles compared to uranium fuel cycles. Thorium presents several advantages including larger reserves than uranium, increased proliferation resistance due to producing lower quantities of weapons-usable material, and potential reductions in fuel cycle costs and nuclear waste. However, the thorium fuel cycle also faces challenges as it has not yet been commercially adopted due to a lack of development and higher associated economic costs compared to established uranium fuel cycles.
This document discusses models for understanding disease causation. It begins by defining disease and the concept of disease causation. It then describes the traditional epidemiological triad model comprising a susceptible host, disease agent, and environment allowing host-agent interaction. Living and non-living disease agents are categorized. The document continues by exploring factors that determine host susceptibility and the properties of disease agents. Finally, it introduces the wheel of causation and causal web models, emphasizing the complex interplay between multiple factors in disease development.
This document provides a lesson plan on Newton's First Law of Motion for 5th grade students (ages 10-12). The lesson aims to help students understand the concept of force and differentiate between balanced and unbalanced forces. Key objectives are for students to remember prior knowledge, know Newton's First Law, and give examples of balanced and unbalanced forces. The lesson defines important terms, provides assessments, and illustrations to explain the concepts in an active way for students.
The document discusses different types of energy, dividing energy into potential energy which is stored energy that can later be used, and kinetic energy which is the energy of motion. It specifically describes gravitational potential energy as energy due to an object's position, calculated using mass x gravity x height, and kinetic energy as energy due to an object's motion, calculated using half mass x velocity squared. The document emphasizes that energy is never created or destroyed, but only changes form, so the total energy in a system remains conserved as potential energy changes to kinetic energy and vice versa.
The document discusses credit risk management for Chinese banks. It outlines several challenges facing banks in 2008, including improving processes to avoid bad debt, managing data and loan origination/collection processes, and balancing compliance and business performance. It also discusses the need to integrate management information and improve staff awareness of risk management. The document proposes building a credit risk management architecture that includes establishing governance over credit data and building a credit risk data mart. It emphasizes the importance of pricing loans correctly to capture both risk and the value of customer relationship management.
This document provides a summary of David G. Burna's professional experience and qualifications. He has over 10 years of experience in data analytics, risk management, and compliance roles within financial services organizations. Currently he is the Director of Risk Analytics at Fiserv, where he oversees machine learning risk models and client relationships to improve fraud prevention performance. Prior experience includes data quality and analytics leadership roles at Wells Fargo, Bank of the West, and BMO Harris, where he developed risk models, led analytics teams, and implemented strategic initiatives.
This document is a resume for David G. Burna. It summarizes his experience in data analytics, risk management, and compliance roles in the financial services industry. Over 15 years, he has implemented database, risk modeling, fraud prevention, and strategic initiatives at companies including Fiserv, Wells Fargo, Bank of the West, BMO Harris, and HSBC. He is seeking a role using big data to improve organizational effectiveness and performance.
Iftikhar Ahmed has over 20 years of experience in business analysis, financial analysis, project management, and database design. He is a certified Project Management Professional with a background in business intelligence systems, financial systems analysis, and database technologies like SQL, Oracle, and IBM Cognos. Currently he works as a Senior Business Intelligence Analyst at Robert Half, where he leads teams in requirements gathering, system impact analysis, and project management.
Chanda Monroe-Williams is a senior-level executive with over 15 years of experience in program/project management, process improvement, and strategic initiatives. She has led teams to successfully complete projects in collections, customer service, risk management, and new product development. Her background includes experience developing strategies, managing projects, and improving processes to drive business results for companies like GE Money and GAFRI. She is a certified Project Management Professional and Lean Six Sigma professional.
This document summarizes the experience and qualifications of Jae DaSilva as a risk and compliance consultant with over 15 years of project management experience in financial services. It lists roles managing projects up to $50 million at various banks and financial institutions, including managing teams of 10+ to 550+ resources. Key areas of expertise include anti-money laundering, regulatory compliance, risk management, data analysis, and project/program management. Technical skills include Microsoft Office, SharePoint, and various financial software.
Surender Reddy Donthi has over 18 years of experience in project and functional management roles in the banking and IT industries. He currently works for Tata Consultancy Services as a subject matter expert on risk projects, with expertise in compliance/governance frameworks like Basel III and CCAR. Some of his key responsibilities and experiences include managing teams on projects, requirements gathering, testing, and acting as a liaison between clients and development teams. He has extensive experience working on risk data aggregation and capital calculation projects for banks like JP Morgan Chase, Bank of America, and Silicon Valley Bank.
Risk assessment usually involves complicated digital lending journeys of creating complex predictor and indicator models through multiple fragmented platforms. Siloed data across systems and spreadsheets delay risk reporting, updates to existing risk modelling system, increases costs and decreases operational efficiency.
This makes it difficult to keep pace with dynamic models, regulatory changes and emerging best practices. ORIGINATIONNEXT RAM represents a generational leap in risk assessment and rating by creating tighter integration between risk model developers, risk management teams.
This document summarizes the career experience of a senior level risk manager with nearly 10 years of experience in risk management, compliance, operations, audit, credit, and policy formulation. They currently serve as a senior risk manager at Bajaj Finserv Lending, where they establish risk frameworks, develop policies, implement risk management tools, conduct risk analysis and reporting, ensure compliance, and provide staff training. Prior experience includes roles as a credit analyst at Development Credit Bank and Axis Bank, where responsibilities involved credit analysis, financial assessment, and risk profiling of corporate clients. Additional experience was gained in business intelligence, product development, and technical support roles.
Chandresh Giriraj is a data management professional with over 12 years of experience in data analysis, governance, warehousing, quality assurance, and reporting. He has extensive experience implementing frameworks around capital data quality assurance and data stewardship. His most recent roles involve managing financial reconciliation projects and ensuring data quality and compliance standards.
Kamal Sanghani has over 15 years of experience leading global programs, projects, and portfolios in various industries including banking, financial services, insurance, retail, healthcare, and telecom. He has a track record of successfully managing transformations, transitions, and IT implementations involving hundreds of resources across multiple countries. Some of his skills include program management, PMO leadership, business analysis, relationship management, and delivering projects on time and on budget. He currently works as a senior program manager on identity and access management projects for Wells Fargo.
The document provides a summary of a professional's experience in strategy, delivery management, and transformation as well as account, program, and project management. Over 20 years of experience is highlighted across various industries including healthcare, pharmaceuticals, insurance, telecom, financial services, and e-commerce. Recent experience includes managing a large digital transformation program for a healthcare PBM client and delivering application development services for healthcare organizations. Technical skills include Angular, .NET, Java, and experience across the software development lifecycle from requirements to delivery.
This document provides an overview of BCBS 239 principles for effective risk data aggregation and risk reporting. It discusses how most large banks historically managed risks through Excel and Access databases, which were inadequate. BCBS 239 principles address issues with risk management processes, including risk IT infrastructure, data quality, strategy, governance, and reporting. All in-scope banks must implement BCBS 239 guiding principles by 2016. Key impacted areas include market, credit, liquidity, and operational risk management. The approach involves understanding BCBS 239 requirements, gap analysis, a program implementation plan, detailed divisional analysis and projects, an IT solution, data governance, and regulator agreement.
SD Basel process automation seminar presentationsarojkdas
The document discusses key considerations for financial institutions in establishing a sustainable process for automating Basel III capital adequacy requirements. It emphasizes the need for a golden source of data, unified data management, and computational flexibility to implement complex models and regulatory changes. A reference information architecture is proposed with shared ownership of data and active collaboration between risk, finance, regulatory, and IT functions. Effective data governance and change management processes are necessary to ensure ongoing validity, consistency and completeness of data.
An experienced executive provides a summary of his career experience spanning over 20 years in senior management roles across industries including financial services, technology, and sports/fitness. He has expertise in areas such as IT, security, compliance, vendor management, risk management, strategic planning, and project/program management. Recent roles include Director of Procurement at Aetna, SVP of Security and Risk Management at Columbia Bank, and Senior Manager of Global Sourcing and Vendor Management at Russell Investments.
Daniel Kocis is the president of Applied Multivariate Algorithms Inc. He has extensive experience developing SAS models and reporting systems to support regulatory risk reporting and credit risk management at a large bank. Some of his work includes:
1) Developing a model risk management tool for consumer credit cards that automated model building, validation, and tracking.
2) Creating risk reporting and data governance processes across multiple lines of business.
3) Developing models and reports to track credit performance, delinquency rates, and risk exposures across all of the bank's consumer credit products.
4) Using credit bureau data to profile auto and specialty loan portfolios and track their credit risk characteristics.
1. 1
Christopher Moore
Chris.m.moore@hot mail.c om
726 Covered Bridge Drive Delaware, OH 43015 Cell:(614) 557-1405
EXECUTIVE PROFILE
High-energy, results-oriented Risk Management leader creating innovative business solutions needed to monitor and
manage the overall risk portfolio performance. Accomplished leader with demonstrated ability to deliver mission-critical
results and establish key business partnerships across multiple cross functional areas needed to support overall
initiatives. Builds and retains high performance teams by hiring, developing and motivating skilled professionals.
KEY QUALITIFICATIONS
Risk Management Portfolio Analysis & Monitoring Data Management & Migration
Strategic Analytics Budget & Loss Forecasting Data Analytics & Governance
Model Validation, Policy &
Oversight
Financial & Operational
Analysis
People Leadership,
Development & Motivation
Fraud Prevention &
Investigation
Performance Management/
Scorecards
Customer Focused/Hard-
worker/Out-of-Box Thinker
CORE ACCOMPLISHMENTS
Currently lead a Centralized Model Risk Management Team responsible for Model Validation & Governance
Frameworks across User Testing & Monitoring consistent with SR11 7 Standards. Manage modeling portfolio
solution with automated model validation, alert rules management; and consistent model health reporting.
Led the large scale complex project execution across the Basel Committee on Banking Supervision (BCBS) Data
Management & Migration (DM&M) workstream with responsibility for providing strategic direction and execution of
Model Data Requirements and Decomposition.
Managed the teams that designed, implemented, and executed the Business Banking Risk BCBS 239 Program
establishing the data & reporting requirements. Accountable to the sub LOB CRO, led a mixed team of 15+
professionals on end to end execution defining the current state data & reporting infrastructure.
Credit Risk Strategy professional implementing predictive and analytic strategies directly impacting business risk
appetite. Designed, implemented and managed Business Banking Scorecards across account management,
acquisition strategy, decision management, collections and marketing analytics.
Fraud Risk Management professional implementing fraud analytics, custom rules generation, and Operations
management to reduce Fraud Losses. Led analytics team responsible for custom rules design and
implementation across Falcon Model and visa authorization engine. Dropped Fraud losses by 35% across Card
Not Present, Lost Stolen, and Non Receipt portfolios.
Experienced Capital & Loss Forecasting Analytics leader with demonstrated delivery success across BASEL and
CCAR. Designed and executed the Business Banking CCAR data, analytics, and reporting infrastructure
leveraged for Quarterly FRY-14Q submission. Led the team on the required segmentation and data requirements
to the FFIEC submission website.
Led the team that designed and implemented the RWA Quarterly Attestation process for Business Banking.
Validated the Scored Retail Portfolio methodology in the Consumer Data Wharehouse (EDW) and Wholesale
methodologies in Credit Risk Infrastructure (CRI).
Designed & implemented the Business Banking Basel II Treatment Methodology Model which reduced capital
holdings of $500MM annually in loan loss reserve assignments. Solution implemented in loan service system and
Consumer Enterprise Data Warehouse.
2. 2
PROFESSIONAL EXPERIENCE
JP Morgan Chase, Columbus, Ohio 5/2015 - Current
Executive Director – CCB Risk Management Modeling Analytics
Responsible for CCB Risk Management 1st line of defense around model governance, performance management and
controls. Key workstream areas include: CCB User Testing & Monitoring Model Validation Program, Firmwide Model Risk
Governance & Review (MRGR), and CCB Risk Modeling. Cross functional vertical and horizontal leadership across CCB
including CCB Governance Leads, Model Managers, Model Heads, and Executives.
Model Risk Management Director accountable for strategic direction and implementation of a centralized model
validation and governance platform. Implemented FICO Model Central Platform with 30+ model performance
metrics across scorecard and non-scorecard models.
Designed and executed CCB Tier 3 User Testing & Monitoring Framework moving 200 models to target state
Athena Platform. Created Program communications & tracking guidance for model methodology, performance
metrics, sensitivity and frequency standards.
Manage staff of VP/AVPs responsible for model performance data extracting, centralized Model Health
Reporting, Custom Model Validation Reports, and centralized Model Health.
Strategic design & execution of CCB Risk Model Monitoring Framework consistent with SR 11-7 expectations
Automated delivery of CCB Model Validations including integrated rules management system, Model Health
Reporting, and Model User workflows.
Custom SAS CCAR Platform, Unix front end and Oracle Relational database with subversion monitoring.
JP Morgan Chase, Columbus, Ohio 2/2013 - 5/2015
Executive Director – CCB Risk Management – Risk Architecture
Vice President - CCB Risk Management – Risk Strategy & Analytics
BCBS Risk Lead for Business Banking – Drove the successful creation, socialization and implementation of the Business
Banking strategy to execute the roadmap across Data, Reporting and Modeling compliance for the BCBS 239 Program.
Successfully planned the identification and execution of Report Pages in Scope, led the data lineage exercise, and fully
decomposed the identified models in Scope. Planned, negotiated and led the consultant plus heritage LOB support staff
across all BCBS Master Plan and Program milestones.
Strategic execution across BCBS Risk Data Migration and Management Modeling Decomposition and Requirements.
Leader integrated across vertical and horizontal teams including Risk & Finance Technology, CCB Data Management
Program, and CCB Risk and Technology. Primary activity was the successful identification and migration of required
model Inputs/Outputs necessary for documentation in MRDX and certification in MDR. Promoted from VP to Executive
Director.
Supported the required major program Business Banking milestones against the following deliverables:
Designed the System of Record RoadMap and procurement from the Investment Review Committee
Completed and Submitted the current state Basel Questionnaire across Risk, Finance, and Technology
Managed the Data & Reporting Requirements framework identifying current state required Reports & Data
Managed the full lineage decomposition of atomic & derived elements across the current state data infrastructure
Managed the population & program presentation of Business Requirements Document (BRD)
Executed the population of Ab Initio (Basel Risk Tool) for Data Requirements and CapMat for Reports
BCBS initiative required building strong horizontal and vertical business partnerships along with effective
communications skills to keep a broad team of stakeholders and experts aligned and synchronized, moving
towards a number of key objectives and deadlines in support of the BCBS regulatory initiative
JP Morgan Chase, Columbus, Ohio 7/2008 - 2/2013
Vice President – Consumer Risk Strategy & Analytics – Business Banking
Assistant Vice President – Consumer Risk Strategy & Analytics – Business Banking
Responsible for supporting the Business Risk Management Group activities for strategic analytics across $50 Billion
portfolio. Risk strategy and analytic professional providing portfolio management solutions for optimized portfolio risk
exposure. Developed automated MIS to monitor and minimize credit losses and control of key risk indicators. Program
development, implementation and reporting responsibility across account management scorecards, acquisition strategy,
and marketing risk appetite. Promoted from Senior Risk Analyst to Risk Manager VP in 2010. Key activities included:
3. 3
Responsible for Business Banking Behavior System (Early Warning System) including Information Ownership,
Account Management, Model Review, and Operational Risk Oversight.
Account Management Program including segmentation, score-cutoffs, Line Management; and opportunity upsell.
Acquisition Strategy Scorecard enhancements on Borrower debt cash flow, non member deposits, and alternative
data sources resulting in 15% volume increase and reduced risk appetite.
Designed & Implemented Basel Wholesale Loan Loss Reserve Methodology saving the Firm $500MM.
Accountable and responsible from model design to Authoritative Source Data Wharehouse implementation.
Program management including interaction with Sales Channel & Risk Organization, Operational Processing, and
ownership/enhancement of Customer Applications.
Business Banking Governmental Reporting including Quarterly CCAR, Off Balance Sheet, FAS 107, and
Graded Collateral Dependent Criticized & Classified Losses.
Lead Risk Analyst responsible for Marketing Campaigns Risk Appetite and waterfall decisioning selection.
SAS Foundation Skills including Base SAS 9.2, Enterprise Guide 4.3, Enterprise Miner, Knowledge Studio
Huntington National Bank, Columbus, Ohio 3/2006 - 7/2008
Corporate Risk – Senior Risk Analyst
Reporting to the Enterprise Chief Risk Officer with responsibilities for creating the Enterprise Wide Risk (ERM) reporting
framework across Credit, Operational, Legal, Compliance, and Investment Risk Organizations. Automated the manual
reconciliation and production of ERM report to an automated solution utilizing SNL Financial and Hyperion Reporting.
Additional roles included Corporate Risk Secretary duties for the production and delivery Meeting Materials including
Agenda, Risk Reports, and Meeting Minutes for Risk and Operational Risk Committees. Additional highlights included:
Credit Risk Assessment included reporting of loan asset quality, portfolio management, reserve methodology, and
credit risk adjusted returns.
Development and verification of key risk indicators to measure and monitor Board risk appetite. Implementation of
SNL product to perform peer industry reviews to increase benchmarking capability.
Development of automated tracking system to improve compliance with internal and external audits.
Pro-forma valuation of Huntington & Sky Risk analysis including credit, operational, market, and compliance
indicators.
Responsible for maintaining a data mapping utility to track mapping progress of seven source systems to the
target system of SNL Financial.
Discover Financial Services, Riverwoods, Illinois - 5/2004 to 3/2006
Credit Card, Fraud Risk Manager
Responsible for $350MM Credit Card/Checking Loss Budgets for Card Not Present, Non Receipt, and Lost Stolen Fraud
Portfolios. Development and implementation of predictive fraud analytics driving down false positive rates, increased
fraud prevention dollars, and increased fraud recovery dollars. Created custom based rules algorithms implemented in
VISA Authorization Engine. Instrumental policy and procedural enhancements providing key reductions in social
engineering, account takeover and mitigation responses. Additional analysis and executive management highlights:
Quarterly Portfolio presentations to Executive Management including Card member Services President, Loss
Director, and Marketing President.
Increased Recovery Rate to over 99% on Card Not Present Fraud Type through acceptance and automation of
affidavits and chargeback policy. Authored 2 sections of the Discover Network Chargeback Rules & Guidelines.
Worked with key Industry partners including Yahoo, Hotels.Com, and Amazon to develop anti card sequencing
and online testing protocols.
Developed Business Strategy to identify & mitigate Bulk Theft and Hot Zip & MSA List to reduce Non Receipt bulk
theft losses. Annual Fraud budget reduced by 35% over 2 years with minimal profitability disruption.
Developed Strategy to optimize recovery on Lost Stolen Portfolio by focusing Investigations on reduction of
Family/Familiar fraud. Initiate Investigator cross – examinations of potential suspects.
Optimized Falcon Scoring fraud model through enhanced business rule strategy derived from Teradata & Oracle
data analysis.
Additional Work History:
Verizon Wireless, Columbus, Ohio - 5/2002 to 4/2004
Corporate Support Business Analyst
First USA, Columbus, Ohio - 6/2000 to 4/2002
Fraud Risk Specialist II/Supervisor
4. 4
EDUCATION/TRAINING
Bachelor of Arts in Interdisplinary Studies, Michigan State University
Masters in Finance and Business Administration, Franklin University
Technology – SAS, SQL, UNIX, Teradata, DB2, Oracle, Toad, Putty, Ab Initio, Informatica
Reporting & BI – Microsoft Reporting Services, Business Objects, Tableau, Cognos, Essbase
Strategy & Predictive Analytics – SAS Enterprise Miner, Angoss Knowledge Seeker/Studio, FICO Model Central
JPMorgan Chase – Art of Leadership Training
JPMorgan Chase – Consumer Risk Management Training Program