19 Cecl Jobs

You are an experienced Senior Quantitative Analyst (Model Developer/Validator) with extensive expertise in credit risk modeling, particularly focusing on Internal Credit Risk Rating modeling. Your role involves leading the development and validation of advanced credit risk models, including PD, EAD, LGD, with a special emphasis on Expert judgment-based PD models for Corporate, Specialized Lending, and Financial Institutions. Your responsibilities include conducting thorough data preparation and preprocessing using tools such as SAS, Python, R, and SQL. Collaborating with various stakeholders to analyze, interpret, and communicate complex model results and insights is crucial. You are expected to develop detailed technical documentation for regulatory compliance, test plans, validation reports, findings reports, and Business Requirements Documents (BRD) where applicable. Continuous improvement of models is key, which involves identifying optimization opportunities, implementing advanced modeling techniques, and enhancing model performance and predictive accuracy. Additionally, you will provide mentorship and technical guidance to junior team members to foster a culture of knowledge sharing and professional development. To qualify for this role, you need to have 5-10 years of hands-on experience in credit risk model development and validation, along with proven expertise in modeling across retail and wholesale credit portfolios. Advanced proficiency in SAS, Python, R, and SQL is essential, as well as a deep understanding of IFRS9 and CECL regulatory frameworks and guidance. Excellent analytical and problem-solving skills are required, complemented by strong written and verbal communication abilities. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or a related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning, and advanced statistical modeling techniques, as well as knowledge of Basel regulatory guidance. Your technical skills should encompass model development (PD, LGD, EAD, Qualitative PD Models), programming (SAS, Python, R, SQL), regulatory knowledge (IRB, IFRS9, CECL), statistical modeling, data preprocessing, and machine learning techniques.,

The Senior Risk Analyst, Loss Forecasting will be an organized and motivated team player with a strong sense of ownership. As a key member of the credit risk management team, you will be responsible for creating and tracking appropriate KPIs, developing and maintaining forecasting frameworks and processes, and serve as an active team player in credit reviews. You will develop and maintain forecasting, CECL, and Stress Testing models for fintech products and will be expected to find opportunities to enhance and automate existing processes. Craft dashboards to track KPIs around portfolio performance, including deep diving into credit strategies and their impact on it. Extend analytical support to advance fintech collections strategy and build forecasting frameworks for key collections KPIs. Use analytical techniques to mine loan characteristics/performance data to extract valuable insights for the business. Use data visualization techniques to develop relevant reports for Senior Management. Track industry environment and competitor landscape to support the business. Correlate Macro-Economic conditions with fintech internal loan performance to support recession readiness and long-run planning. Leverage forecasting outputs in the monthly allowance process (CECL) and identify areas where qualitative adjustment is needed. Support planning and budgeting exercises within the company by leveraging forecasting assumptions and outputs. Work closely with key partners to ensure forecast and allowance assumptions are accurate. About You 4+ years of experience in credit, analytics, IFRS9 and CECL, risk management, data science, or information management. Bachelors or masters degree with a quantitative background (e.g. Statistics, Math, Engineering, Economics). Strong technical skills such as SQL, SAS, R, and Python. Experience with BI/data visualization tools (like Tableau or Excel to create dashboards). Excellent written and verbal communication skills, including the ability to communicate project scope in documentation and presentation format. Experience in the Financial / FinTech industry is a plus. Previous experience with loss forecasting and collections analytics, allowance.,

Are you seeking an exciting opportunity to join a dynamic and growing team in a fast-paced and challenging environment This unique role offers you the chance to collaborate with the Business team to provide a comprehensive view. As a Loss Forecasting Modeling Analytics Associate in the Consumer Credit Risk Management team, your primary responsibility will be to execute credit loss forecasting models. You will diagnose model accuracy and lead analyses to evaluate relationships and patterns that impact the loss performance of our product portfolio. Your role will involve spearheading the control framework within our function and executing processes through analytical insights, predictive analysis, and newer technology applications. This position presents an exciting opportunity for skill development in a fast-paced setting. The Loss Forecasting team within Consumer Credit Risk Management is tasked with providing reasonable forecasts of delinquencies, charge-offs, and recovery of charged-off assets throughout the year. These forecasts are essential for regulatory exercises such as CCAR, capacity planning, and budgeting in collaboration with P&A, collections, and recovery teams. Additionally, the team monitors the portfolio's health and communicates emerging trends to stakeholders and senior management. **Job Responsibilities:** - Execute credit loss forecasting models to predict credit losses and allowance for the product portfolio, supporting regulatory exercises like CCAR, CECL, firmwide Risk Appetite, and Budget. - Present the results and levers of loss forecasting to senior management and internal stakeholders. - Diagnose model parameters and collaborate with the modeling team to propose changes for accuracy at granular segments. - Engage in cross-functional communications with Risk Management, Finance, Marketing, and Collections to incorporate strategic initiatives into the forecast. - Conduct macro sensitivity analytics, loss, and allowance attribution, deep dives, and storyboarding. - Lead advanced analyses to evaluate relationships and patterns driving loss performance. **Required Qualifications, Capabilities, and Skills:** - Bachelor's or Master's Degree in a quantitative discipline (Finance/Stats/Econ/Math/Engineering) or equivalent work/training. - Minimum of 4 years of banking analytics, product/revenue analytics, FP&A, and/or consulting experience for a senior Associate role. - Minimum of 2 years of banking analytics, product/revenue analytics, and/or consulting experience for an Associate role. - Proficiency in Microsoft Office suite of products (Advanced Excel, VBA, and PowerPoint). - Strong analytical and problem-solving skills with the ability to interpret large amounts of data and understand its operational and financial implications. - Well-organized and structured with excellent communication and presentation skills. **Additional Qualifications:** - Working knowledge of regulatory modeling (IFRS9/CECL/CCAR). - Credit risk experience in one or more US consumer credit portfolios. - Working knowledge of P&A, product analytics, statistical modeling, and model execution. - Actual work experience in Python/SAS/SQL/Alteryx/Cloud application architecture. In summary, this role offers a challenging yet rewarding opportunity to contribute to credit loss forecasting models and play a crucial role in the Consumer Credit Risk Management team.,

PLEASE DO NOT APPLY ON NAUKRI PORTAL, APPLY ON BELOW LINK https://crowe.wd12.myworkdayjobs.com/External_Careers/job/Noida-Uttar-Pradesh-India/Model-Risk-Senior-Consultant_R-47692 Your Journey at Crowe Starts Here: At Crowe, you can build a meaningful and rewarding career. With real flexibility to balance work with life moments, you’re trusted to deliver results and make an impact. We embrace you for who you are, care for your well-being, and nurture your career. Everyone has equitable access to opportunities for career growth and leadership. Over our 80-year history, delivering excellent service through innovation has been a core part of our DNA across our audit, tax, and consulting groups. That’s why we continuously invest in innovative ideas, such as AI-enabled insights and technology-powered solutions, to enhance our services. Join us at Crowe and embark on a career where you can help shape the future of our industry. Job Description: The Model Risk Senior Consultant will be responsible for performing consulting projects for a variety of financial services clients. This primarily includes consulting with clients about model risk management practices and providing model validation services, primarily for credit risk and treasury management (ALM)/finance related models. In addition, the role will also perform the following: Complete key aspects of client service projects from planning to completion. Become a trusted advisor to client management by providing appropriate recommendations and solutions. Able to make and sustain meaningful client relationships. Support proposal and business development activities by identifying new target clients, building business relationships with key executives, and developing and presenting proposals. Qualifications: Bachelor’s degree in Finance, Statistics, Financial Engineering, or Economics or equivalent combination of education and experience. 4+ years’ of experience of working in financial institutions, Big 4 or equivalent, or regulatory supervisory of financial institutions. Working knowledge of: Model risk management regulatory guidance (SR 11-7, OCC 2011-12, FDIC FIL-22-2017). Credit risk model types (e.g., CECL, PD/LGD, Roll Rate, Scorecards, Stress Testing, etc.). Other model types (e.g., Asset Liability Management, Pricing, Mortgage Servicing Rights, etc.). Direct experience performing model validations or model development, including concepts such as back testing, stress testing, sensitivity testing, and benchmarking. Technical knowledge about data processing, data storage, and data visualization. A self-starter who can prioritize multiple tasks, be resourceful and able to research and find solutions. Write and present to clients clear and concise reports and presentations containing meaningful recommendations. Direct and deliver significant engagements that deliver value to clients through project management, creation of deliverables and knowledge transfer. Manages engagement to ensure quality and is delivered within budget. Engagements are frequently conducted remotely. This position requires travel up to 30%. Additional skills desired: Solid analytical background and knowledge of econometrics. Knowledge of risk ratings, risk rating /scorecard methodology, model governance, model development, CECL, DFAST, CCAR and capital allocation methodology would be a plus. Experience with statistical packages such as SAS, Matlab, Stata, Python, and R. Experience with database management, such as SQL. Experience with data visualization tools such as Microsoft Power BI, Tableau, QlikView. Working towards or having professional certification preferred (e.g., RMA CRC, CFA, FRM). We expect the candidate to uphold Crowe’s values of Care, Trust, Courage, and Stewardship. These values define who we are. We expect all of our people to act ethically and with integrity at all times. Our Benefits: At Crowe, we know that great people are what makes a great firm. We value our people and offer employees a comprehensive benefits package. Learn more about what working at Crowe can mean for you! How You Can Grow: We will nurture your talent in an inclusive culture that values diversity. You will have the chance to meet on a consistent basis with your Career Coach that will guide you in your career goals and aspirations. Learn more about where talent can prosper! More about Crowe: C3 India Delivery Centre LLP formerly known as Crowe Howarth IT Services LLP is a wholly owned subsidiary of Crowe LLP (U.S.A.), a public accounting, consulting and technology firm with offices around the world. Crowe LLP is an independent member firm of Crowe Global, one of the largest global accounting networks in the world. The network consists of more than 200 independent accounting and advisory firms in more than 130 countries around the world. Crowe does not accept unsolicited candidates, referrals or resumes from any staffing agency, recruiting service, sourcing entity or any other third-party paid service at any time. Any referrals, resumes or candidates submitted to Crowe, or any employee or owner of Crowe without a pre-existing agreement signed by both parties covering the submission will be considered the property of Crowe, and free of charge.

Your journey at Crowe starts here. At Crowe, you can build a meaningful and rewarding career with real flexibility to balance work with life moments. You are trusted to deliver results and make an impact. We embrace you for who you are, care for your well-being, and nurture your career. Everyone has equitable access to opportunities for career growth and leadership. Over our 80-year history, delivering excellent service through innovation has been a core part of our DNA across our audit, tax, and consulting groups. That's why we continuously invest in innovative ideas, such as AI-enabled insights and technology-powered solutions, to enhance our services. Join us at Crowe and embark on a career where you can help shape the future of our industry. The Model Risk Senior Consultant will be responsible for performing consulting projects for a variety of financial services clients. This primarily includes consulting with clients about model risk management practices and providing model validation services, primarily for credit risk and treasury management (ALM)/finance related models. In addition, the role will also perform the following: - Complete key aspects of client service projects from planning to completion. - Become a trusted advisor to client management by providing appropriate recommendations and solutions. Able to make and sustain meaningful client relationships. - Support proposal and business development activities by identifying new target clients, building business relationships with key executives, and developing and presenting proposals. Qualifications: - Bachelor's degree in Finance, Statistics, Financial Engineering, or Economics or equivalent combination of education and experience. - 4+ years of experience of working in financial institutions, Big 4 or equivalent, or regulatory supervisory of financial institutions. - Working knowledge of model risk management regulatory guidance (SR 11-7, OCC 2011-12, FDIC FIL-22-2017). - Credit risk model types (e.g., CECL, PD/LGD, Roll Rate, Scorecards, Stress Testing, etc.). - Other model types (e.g., Asset Liability Management, Pricing, Mortgage Servicing Rights, etc.). - Direct experience performing model validations or model development, including concepts such as backtesting, stress testing, sensitivity testing, and benchmarking. - Technical knowledge about data processing, data storage, and data visualization. - A self-starter who can prioritize multiple tasks, be resourceful and able to research and find solutions. - Write and present to clients clear and concise reports and presentations containing meaningful recommendations. - Direct and deliver significant engagements that deliver value to clients through project management, creation of deliverables, and knowledge transfer. - Manages engagement to ensure quality and is delivered within budget. - Engagements are frequently conducted remotely. - This position requires travel up to 30%. Additional skills desired: - Solid analytical background and knowledge of econometrics. - Knowledge of risk ratings, risk rating/scorecard methodology, model governance, model development, CECL, DFAST, CCAR, and capital allocation methodology would be a plus. - Experience with statistical packages such as SAS, Matlab, Stata, Python, and R. - Experience with database management, such as SQL. - Experience with data visualization tools such as Microsoft Power BI, Tableau, QlikView. - Working towards or having professional certification preferred (e.g., RMA CRC, CFA, FRM). We expect the candidate to uphold Crowe's values of Care, Trust, Courage, and Stewardship. These values define who we are. We expect all of our people to act ethically and with integrity at all times. Our Benefits: At Crowe, we know that great people are what make a great firm. We value our people and offer employees a comprehensive benefits package. How You Can Grow: We will nurture your talent in an inclusive culture that values diversity. You will have the chance to meet on a consistent basis with your Career Coach that will guide you in your career goals and aspirations. More about Crowe: C3 India Delivery Centre LLP, formerly known as Crowe Howarth IT Services LLP, is a wholly-owned subsidiary of Crowe LLP (U.S.A.), a public accounting, consulting, and technology firm with offices around the world. Crowe LLP is an independent member firm of Crowe Global, one of the largest global accounting networks in the world. The network consists of more than 200 independent accounting and advisory firms in more than 130 countries around the world. Crowe does not accept unsolicited candidates, referrals, or resumes from any staffing agency, recruiting service, sourcing entity, or any other third-party paid service at any time. Any referrals, resumes, or candidates submitted to Crowe, or any employee or owner of Crowe without a pre-existing agreement signed by both parties covering the submission will be considered the property of Crowe, and free of charge.,

Job Description: As an Analyst/Sr Analyst for Model Monitoring and Implementation at Northern Trust, you will play a vital role within the Model Strategy & Data Analytics team. Your primary responsibility will be to monitor and implement various models such as PPNR, Credit Risk, Operational Risk, and Market Risk models. This individual contributor role will involve tasks throughout the model lifecycle, including monitoring, recalibration, and implementation. You will also be involved in developing and maintaining monitoring tools using SAS for CCAR, Basel, and CECL purposes. Your key responsibilities will include monitoring, recalibrating, and implementing models such as CCAR models (PD/EAD/LGD), CECL models (PD/EAD/LGD), Basel models (PD/EAD/LGD), operational risk analytics models, and PPNR models. You will evaluate existing monitoring tools, assess development needs, and ensure compliance with different regulations such as CCAR, CECL, Basel, and IFRS9. Additionally, you will conduct analysis, interact with committees and senior management, and provide technical expertise to enhance the overall risk framework. To qualify for this role, you should have a Master's degree in Statistics, Economics, Mathematics, or an advanced degree in a quantitative area. You must possess strong knowledge of BASEL, CCAR, DFAST, CECL, and SR-11/7, along with at least 1 year of hands-on experience in monitoring, validation, or model building. Proficiency in R, SAS, Matlab, advanced Excel techniques, and VBA programming is required, with SAS being preferred. Strong quantitative skills, multitasking abilities, organizational skills, and excellent communication skills in English are also essential. Joining Northern Trust means being part of a flexible and collaborative work culture that encourages movement within the organization and offers opportunities for professional growth. As a company committed to serving the communities it operates in, Northern Trust provides a workplace with a greater purpose. If you are excited about this role and the prospect of working with us, we encourage you to apply today and discuss your flexible working requirements to achieve greater success together.,

You are an experienced Lead Model Developer/Validator with a strong background in credit risk modeling, particularly focusing on Internal Credit Risk Rating modeling. Your main responsibility will involve leading the development and validation of advanced credit risk models, including PD, EAD, LGD, with a special emphasis on Expert judgment-based PD models for Corporate, Specialized Lending, and Financial Institutions. Your role will require you to conduct thorough data preparation and preprocessing using tools such as SAS, Python, R, and SQL. You will collaborate with various stakeholders to analyze, interpret, and communicate complex model results and insights. Additionally, you will be responsible for creating technical documentation including regulatory compliance model documentation, test plans, validation reports, findings report, and business requirements documents where applicable. Continuous improvement of models will be a key aspect of your job, involving identifying optimization opportunities, implementing advanced modeling techniques, and enhancing model performance and predictive accuracy. Moreover, you will be expected to provide mentorship and technical guidance to junior team members, promoting a culture of knowledge sharing and professional development. To qualify for this position, you should have 5-10 years of hands-on experience in credit risk model development and validation, proven expertise in modeling across retail and wholesale credit portfolios, and advanced proficiency in SAS, Python, R, and SQL. A deep understanding of IFRS9 and CECL regulatory frameworks and guidance, exceptional analytical and problem-solving skills, as well as excellent written and verbal communication abilities are essential. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or a related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning/advanced statistical modeling techniques, and knowledge of Basel regulatory guidance. Your technical skills should encompass model development (PD, LGD, EAD, Qualitative PD Models), programming (SAS, Python, R, SQL), regulatory knowledge (IRB, IFRS9, CECL), statistical modeling, data preprocessing, and machine learning techniques. If you meet these qualifications and are looking for a challenging opportunity to leverage your expertise in credit risk modeling, this role offers a platform to lead and drive sophisticated credit risk modeling initiatives across various portfolios.,

This position requires a seasoned professional as a Senior Manager with specialized knowledge of credit risk management. You will be overseeing the development, enhancement, and validation of credit risk models, ensuring compliance with regulatory standards, and driving innovation in risk management practices. The ideal candidate should have hands-on experience in Credit Risk Model Validation or Development with SAS and Python. You should also possess good hands-on experience in Regulatory Models such as AIRB, CECL, CCAR, Basel, IFRS9. You will primarily work as a consultant for the centralized advanced analytics team of a banking or financial firm focusing on Credit Risk Model Development/Validation and Researcher Specialist. Your responsibilities will include interacting with various business units including risk, finance, controllership stakeholders, and coordinating with auditors and model development or validation teams to ensure adherence to Enterprise Modeling Governance standards. Your activities will involve providing thought leadership, developing and executing modeling strategies, designing, developing, and validating predictive models, conducting testing and validation methodologies, providing analytical support for risk mitigation, assessing data quality, leading and mentoring junior team members, proposing monitoring system improvements, conducting in-depth research on credit risk modeling policies, and contributing to white-paper creation. Minimum Qualifications: - Experience in developing, validating models and risk management of credit risk models. - Knowledge of various statistical techniques and proven skill in regulatory and non-regulatory credit risk modeling. - Understanding and experience with regulatory risk model development/validation guidelines such as SR 11-7, Basel IRB, CCAR, CECL, IFRS9, etc. - End-to-end development or independent validation of credit risk and regulatory models (PD, LGD, EAD, Stress Testing, CECL, Credit Scorecards, AML, counter fraud models, etc.). - Expertise in developing statistical/mathematical and machine learning based models, working with large data sets using SQL, ETL, SAS, Python, R. - Master's degree in a quantitative discipline (Statistics/Economics/Finance/Data Science, etc.). - Strong client management, communication, presentation skills. - Self-driven, proactive, with a "can-do" attitude, able to work under ambiguity and minimal supervision. - Strong project management experience, ability to communicate and coordinate across multiple business units. - Lead projects, provide thought leadership, technical guidance, training, and oversight. Preferred Qualifications: - Strong networking, negotiation, influencing skills. - Knowledge of credit risk management for retail and wholesale lending products. - Hands-on experience in Machine Learning modeling techniques. - Prior Project Management and People Management expertise. Required Skills And Certifications: - Model Validation. - SAS. - Python. - Regulatory Model. - Model Development. - Credit Risk.,

You are an experienced Senior Quantitative Analyst specializing in credit risk modeling, especially focused on Internal Credit Risk Rating modeling. Your role involves leading the end-to-end development and validation of advanced credit risk models, with an emphasis on Expert judgement-based PD models for various sectors. You will work on data preparation and preprocessing using tools like SAS, Python, R, and SQL. Collaboration with cross-functional stakeholders is key to analyze and interpret complex model results and insights. Your responsibilities also include developing technical documentation for regulatory compliance, test plans, validation reports, and business requirements documents. Continuous model improvement is expected through optimization, implementing advanced modeling techniques, and enhancing predictive accuracy. Mentorship and technical guidance to junior team members are essential to foster knowledge sharing and professional development. Required qualifications include 5-10 years of hands-on experience in credit risk model development, expertise in modeling across retail and wholesale credit portfolios, proficiency in SAS, Python, R, SQL, deep understanding of IFRS9 and CECL regulatory frameworks, analytical skills, and excellent communication abilities. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning techniques, and knowledge of Basel regulatory guidance. Technical skills required for the role encompass Model Development (PD, LGD, EAD, Qualitative PD Models), Programming (SAS, Python, R, SQL), Regulatory Knowledge (IRB, IFRS9, CECL), Statistical Modeling, Data Preprocessing, and Machine Learning Techniques.,

You are an experienced Senior Quantitative Analyst (Model Developer/Validator) with a strong background in credit risk modeling, particularly focusing on Internal Credit Risk Rating modeling. Your expertise will be crucial in leading the development and validation of sophisticated credit risk models for retail and wholesale portfolios. Your responsibilities will include developing and validating credit risk models such as PD, EAD, LGD, with a special emphasis on Expert judgement-based PD models for Corporate, Specialised Lending, and Financial Institutions. You will also be responsible for data preparation and preprocessing using tools like SAS, Python, R, and SQL. Collaborating with various stakeholders to analyze and interpret complex model results and insights will be a key aspect of your role. In addition, you will develop technical documentation for regulatory compliance, test plans, validation reports, and business requirements documents. You will drive continuous model improvement by identifying optimization opportunities, implementing advanced modeling techniques, and enhancing model performance. Mentoring and providing technical guidance to junior team members will be part of your responsibilities to encourage a culture of knowledge sharing and professional development. To be successful in this role, you should have 5-10 years of hands-on experience in credit risk model development and validation, along with proven expertise in modeling across retail and wholesale credit portfolios. Advanced proficiency in SAS, Python, R, and SQL is essential, as well as a deep understanding of IFRS9 and CECL regulatory frameworks. Strong analytical and problem-solving skills, along with excellent written and verbal communication abilities, are also required. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or a related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning/advanced statistical modeling techniques, and knowledge of Basel regulatory guidance. Your technical skills should encompass model development (PD, LGD, EAD, Qualitative PD Models), programming (SAS, Python, R, SQL), regulatory knowledge (IRB, IFRS9, CECL), statistical modeling, data preprocessing, and machine learning techniques.,

Model Monitoring/Model Validation EXL (NASDAQ:EXLS) is a leading operations management and analytics company that helps businesses enhance growth and profitability in the face of relentless competition and continuous disruption. Using our proprietary, award-winning methodologies, that integrate advanced analytics, data management, digital, BPO, consulting, industry best practices and technology platforms, we look deeper to help companies improve global operations, enhance data-driven insights, increase customer satisfaction, and manage risk and compliance. EXL serves the insurance, healthcare, banking and financial services, utilities, travel, transportation and logistics industries. Headquartered in New York, New York, EXL has more than 30,000 professionals in locations throughout the United States, Europe, Asia (primarily India and Philippines), Latin America, Australia and South Africa. EXL Analytics provides data-driven, action-oriented solutions to business problems through statistical data mining, cutting edge analytics techniques and a consultative approach. Leveraging proprietary methodology and best-of-breed technology, EXL Analytics takes an industry-specific approach to transform our clients decision making and embed analytics more deeply into their business processes. Our global footprint of nearly 2,000 data scientists and analysts assist client organizations with complex risk minimization methods, advanced marketing, pricing and CRM strategies, internal cost analysis, and cost and resource optimization within the organization. EXL Analytics serves the insurance, healthcare, banking, capital markets, utilities, retail and e-commerce, travel, transportation and logistics industries. Please visit www.exlservice.com for more information about EXL Analytics. Home EXL Service is a global analytics and digital solutions company serving industries including insurance, healthcare, banking and financial services, media, retail, and others Role Details : We are seeking a strong credit risk model professional with experience in model monitoring, validation, implementation and maintenance of regulatory models. Responsibilities: Helping with various aspects of model validation Perform all required tests (e.g. model performance, sensitivity, back-testing, etc.) Interact with model governance team on model build and model monitoring Work closely with cross functional teams including business stakeholders, model validation and governance teams Deliver high quality client services, including model documentations, within expected timeframes Requirements : Minimum 2+ years of experience in executing end to end monitoring/validation/production/implementation of risk model validation/monitoring understanding with respect to marketing/general analytics problems Managing assigned projects in a timely manner, ensuring accuracy and that deliverables are met. Training, coaching and development of team members Qualifications: Previous experience (2+ years) in analytics, preferably in BFSI Good knowledge in General Analytics, Fraud Analytics Past experience in problem solving roles, strategic initiatives Good problem-solving skills

Roles and Responsibilities Develop and maintain credit risk models using SAS, SQL, and other relevant tools. Ensure compliance with regulatory guidelines such as Basel II/III, CCAR, CECL, LGD, PD, EAD.

Entity : - Accenture Strategy & Consulting Team : - Global Network – Data & AI Practice : - CFO & EV - Risk Analytics Title : - Ind & Func AI Decision Science Senior Manager/Manager About S&C - Global Network : - Accenture Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition. WHAT’S IN IT FOR YOU? Accenture CFO & EV team under Data & AI team has comprehensive suite of capabilities in Risk, Fraud, Financial crime, and Finance. Within risk realm, our focus revolves around the model development, model validation, and auditing of models. Additionally, our work extends to ongoing performance evaluation, vigilant monitoring, meticulous governance, and thorough documentation of models. Get to work with top financial clients globally Access resources enabling you to utilize cutting-edge technologies, fostering innovation with the world’s most recognizable companies. Accenture will continually invest in your learning and growth and will support you in expanding your knowledge. You’ll be part of a diverse and vibrant team collaborating with talented individuals from various backgrounds and disciplines continually pushing the boundaries of business capabilities, fostering an environment of innovation. What you would do in this role Engagement Execution: Work independently/with minimal supervision in client engagements that may involve model development, validation, governance, strategy, transformation, implementation and end-to-end delivery of risk solutions for Accenture’s clients. Ability to manage workstream of small projects with responsibilities of managing quality of deliverables for junior team members. Demonstrated ability of managing day to day interactions with the Client stakeholders o Practice Enablement o Guide junior team members. o Support development of the Practice by driving innovations, initiatives. o Develop thought capital and disseminate information around current and emerging trends in Risk. Who we are looking for? 2-11+ years of relevant Risk Analytics experience at one or more Financial Services/Banking firms, or Professional Services / Risk Advisory with significant exposure to one or more of the following areas: Development, validation, and audit of: Credit Risk- PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting and Revenue Forecasting Models, IFRS9/CECL Loss Forecasting Models across Retail and Commercial portfolios Credit Acquisition/Behavior/Collections/Recovery Modeling and Strategies, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios Regulatory Capital and Economic Capital Models Liquidity Risk – Liquidity models, stress testing models, Basel Liquidity reporting standards o Anti Money Laundering – AML scenarios/alerts, Network Analysis o Operational risk – AMA modeling, operational risk reporting Conceptual understanding of Basel/CCAR/DFAST/CECL/IFRS9 OR other risk and compliance regulations. Experience in conceptualizing and creating risk reporting and dashboarding solutions. Experience in modeling with statistical techniques such as – linear regression, logistic regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time series – ARMA/ARIMA, ML interpretability and bias algorithms etc. Programing Languages - SAS, R, Python, Spark, Scala etc., Tools such as Tableau, QlikView, PowerBI, SAS VA etc. Strong understanding of Risk function and ability to apply them in client discussions and project implementation. Academic Requirements: Master’s degree in a quantitative discipline mathematics, statistics, economics, financial engineering, operations research or related field or MBA from top-tier universities. Strong academic credentials and publications, if applicable. Industry certifications such as FRM, PRM, CFA preferred. Excellent communication and interpersonal skills. Accenture is an equal opportunities employer and welcomes applications from all sections of society and does not discriminate on grounds of race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, or any other basis as protected by applicable law.

Lead Quantitative Analytics Specialist ALM Modeling Balance sheet modeling IRRBB EVE FTP Deposit models Liquidity Risk models- Corporate Risk helps Wells Fargo businesses identify and manage risk. The team focuses on three key risk areas: credit risk, operational risk and market risk. As the company's second line of defense, Corporate Risk or Independent Risk Management provides independent oversight of risk-taking activities. Independent Risk Management establishes and maintains Wells Fargo's risk management program and provides oversight, including challenges to and independent assessment of the frontline's execution of its risk management responsibilities. Corporate Risk roles depend on a variety of skills, viz. data analysis and synthesis, root cause analysis, change management, process management & execution, risk governance, risk strategy, risk identification & assessment, risk prevention, controls & mitigation, risk monitoring, reporting & escalation, risk systems & technology. In this role, you will: Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly statistical theory Qualify monitor markets and forecast credit and operational risks Strategize short and long-term objectives, and provide analytical support for a wide array of business initiatives Utilize stochastic, structured securities, spread analysis, with the expertise in the theory and mathematics behind the analysis Review and assess models inclusive of technical, audit, and market perspectives Identify structure and scope of review Enable decision making for product and marketing with broad impact and act as key participant to develop and document analytical models Collaborate and consult with regulators and auditors Present results of analysis and strategies Required Qualifications: 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science Desired Qualifications: Risk Modeling Group (RMG) Forecasting: The team is responsible for development and delivery of models leveraged for Credit Risk, Compliance Risk, and Operational Risk. These include models for credit and pre-provision net revenue (PPNR) forecasting, and fair lending. Deposit & PPNR: This team within RMG (Risk Modeling Group) Forecasting is responsible for driving entire model life cycle (model development, monitoring & forecasting) of Wells Fargo deposit balance and yield. Deposit & PPNR team support Pre-Provision Net Revenue (PPNR) estimates including forecasting deposit balance & rate models to support ALM, FP&A, CCAR and Recovery and Resolution Planning. Team is responsible for the design, development, delivery, monitoring and forecasting of econometric forecasting models for Deposit (Interest Expense), Fees (Non-II) & Expense (Non-IE) components to support business planning and economically sensitive CCAR submission. Enhance Deposit modeling framework effectively ensuring consistency in modeling methodologies, Annual/Semi-Annual validations and Audit- tracking thereby ensuring controlled model risk Contribute to the banks balance sheet and income statement modeling methodologies in support of asset & liability management (ALM), FP&A and capital planning by capturing interest rate risk in the banking book (IRRBB) by EVE Responsible for steering stakeholder conversations of user review and model challenge sessions with Business, Finance, Treasury and Model Risk Management for signoffs on Champion & Challenger models Conduct econometric and statistical analysis of time series and panel data sets Knowledge on Python/R/SAS is must Knowledge on model life cycle (development, monitoring, implementation and forecasting) and its intricacies are good to have Should possess strong documentation capabilities which would effectively convey complex models and processes Communicate design and results of complex models to a variety of audiences, including senior management, bank supervisors, Model Governance, Internal Audit and LOB end users Coordinate with business partners, including forecasting teams, and end users to ensure accurate model usage and implementation Adhere to model validation governance to ensure models are following policy and are working as intended, address model validation and regulatory feedback issues Solving model development and model analytics/forecasting challenges in python with quick turn arounds Master's degree or higher in a quantitative field such as Statistics/Economics 5+ years of experience in Deposit & PPNR, Treasury Analytics , or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 5+ years of experience in Deposit balance sheet modeling and treasury/liquidity analytics in support of asset & liability management (ALM), FP&A and capital planning by capturing interest rate risk in the banking book (IRRBB) by EVE 5+ years of advanced programming expertise in SAS or Python or R Strong documentation and project management capabilities with ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment Excellent verbal, written, and interpersonal communication skills Strong ability to develop partnerships and collaborate with other business and functional areas Excellent verbal, written, and interpersonal communication skills Perform various complex activities related to deposit balance sheet modeling Provide analytical support for development, remediation, monitoring, and production of Deposit & PPNR models Support development, implementation, execution and monitoring of Regulatory models such as Basel, CECL, and CCAR models Develop dynamic dashboards; analyze key risk parameters to help understand changes in business and model performance Identify opportunities and deliver process improvements, standardization, rationalization and automations Enhance and standardize performance analysis, reporting packages and business loss forecast processes Maintain documentation for development, implementation and monitoring of processes across the team with focus on standardization of controls Ability to identify and manage complex issues and negotiate solutions within a geographically dispersed organization

We are seeking a highly skilled and motivated CCAR/CECL Modeler to join our team. In this role, you will develop and deploy regulatory models used for regulatory reporting and financial forecasting. The ideal candidate should have expertise in statistical modeling, data analysis, and financial risk assessment, with a strong emphasis on understanding CCAR and CECL requirements. Responsibilities: Conducting specific aspects of the model development life cycle, which involves data acquisition, assessing data integrity, model development, documentation, and implementation assistance. Obtain, clean, and verify data used in model development, ensuring data integrity and quality. Design, develop, test, and validate statistical models for forecasting credit losses and assessing portfolio risk Provide comprehensive documentation for models and present findings to stakeholders Qualifications: 3-5+ years of experience in analytics, preferably in Banking and Financial Services. Hands-on experience working on regulatory models. Proficient in various statistical techniques, including regression, time series analysis. Understanding of credit risk, portfolio risk, and regulatory frameworks (e.g., CCAR, CECL). Excellent problem-solving and analytical skills, with the ability to work on complex projects and deliver high-quality results. Proficiency in programming languages such as Python Strong communication skills, both written and verbal, with the ability to convey complex ideas to stakeholders.

We are looking for a highly skilled and experienced Field Risk Officer to join our team at Equitas Small Finance Bank Ltd. The ideal candidate will have 1-5 years of experience in the BFSI industry. Roles and Responsibility Conduct risk assessments and evaluations to identify potential threats to the organization. Develop and implement strategies to mitigate risks and ensure compliance with regulatory requirements. Collaborate with cross-functional teams to monitor and manage risk exposure. Analyze market trends and competitor activity to inform risk management decisions. Provide expert guidance on risk management best practices to stakeholders. Identify and report on key performance indicators (KPIs) related to risk management. Job Requirements Strong understanding of risk management principles and practices. Excellent analytical and problem-solving skills. Ability to work effectively in a fast-paced environment and prioritize multiple tasks. Strong communication and interpersonal skills. Experience working with financial institutions or similar organizations. Knowledge of relevant regulations and standards, such as Basel II or CCAR/CECL. Additional Info The company offers a competitive salary and benefits package.

Job Description: Understanding of Basel Framework, PD, EAD, LGD and Regulatory Capital. Proficiency in SAS and Python for Model Development Good Understanding of Regulations and has experience of IRB Model Development Good understanding of retail credit risk products and their key variables.

Location: PAN India Immediate joiner required Experienced in end to end capital or Impairment process management RWA calculation engine using Standardized approach (BASEL 1/2/3) for Credit Risk Asset classification for Retail and Wholesale Products, Collateral Adjustment, on balance/ off balance exposure calculation Migration RWA calculation from BASEL 3 to 3.1 using Standardized or AIRB approach Knowledge of Banking domain/ banking products like Retail, corporate, banks, SME, Sovereign Project management / stakeholder management Keywords : Standardized approach - BASEL 1/2/3 Capital Reporting (Standardized approach) RWA Calculation Credit Risk (RWA) capital management

Lead Quantitative Analytics Specialist ALM Modeling Balance sheet modeling IRRBB EVE FTP Deposit models Liquidity Risk models About this role: Wells Fargo is seeking a Lead Quantitative Analytics Specialist. Corporate Risk helps Wells Fargo businesses identify and manage risk. The team focuses on three key risk areas: credit risk, operational risk and market risk. As the company's second line of defense, Corporate Risk or Independent Risk Management provides independent oversight of risk-taking activities. Independent Risk Management establishes and maintains Wells Fargo's risk management program and provides oversight, including challenges to and independent assessment of the frontline's execution of its risk management responsibilities. Corporate Risk roles depend on a variety of skills, viz. data analysis and synthesis, root cause analysis, change management, process management & execution, risk governance, risk strategy, risk identification & assessment, risk prevention, controls & mitigation, risk monitoring, reporting & escalation, risk systems & technology. In this role, you will: Lead complex initiatives including creation, implementation, documentation, validation, articulation, and defense of highly statistical theory Qualify monitor markets and forecast credit and operational risks Strategize short and long-term objectives, and provide analytical support for a wide array of business initiatives Utilize stochastic, structured securities, spread analysis, with the expertise in the theory and mathematics behind the analysis Review and assess models inclusive of technical, audit, and market perspectives Identify structure and scope of review Enable decision making for product and marketing with broad impact and act as key participant to develop and document analytical models Collaborate and consult with regulators and auditors Present results of analysis and strategies Required Qualifications: 5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science Desired Qualifications: Risk Modeling Group (RMG) Forecasting: The team is responsible for development and delivery of models leveraged for Credit Risk, Compliance Risk, and Operational Risk. These include models for credit and pre-provision net revenue (PPNR) forecasting, and fair lending. Deposit & PPNR: This team within RMG (Risk Modeling Group) Forecasting is responsible for driving entire model life cycle (model development, monitoring & forecasting) of Wells Fargo deposit balance and yield. Deposit & PPNR team support Pre-Provision Net Revenue (PPNR) estimates including forecasting deposit balance & rate models to support ALM, FP&A, CCAR and Recovery and Resolution Planning. Team is responsible for the design, development, delivery, monitoring and forecasting of econometric forecasting models for Deposit (Interest Expense), Fees (Non-II) & Expense (Non-IE) components to support business planning and economically sensitive CCAR submission. Enhance Deposit modeling framework effectively ensuring consistency in modeling methodologies, Annual/Semi-Annual validations and Audit- tracking thereby ensuring controlled model risk Contribute to the banks balance sheet and income statement modeling methodologies in support of asset & liability management (ALM), FP&A and capital planning by capturing interest rate risk in the banking book (IRRBB) by EVE Responsible for steering stakeholder conversations of user review and model challenge sessions with Business, Finance, Treasury and Model Risk Management for signoffs on Champion & Challenger models Conduct econometric and statistical analysis of time series and panel data sets Knowledge on Python/R/SAS is must Knowledge on model life cycle (development, monitoring, implementation and forecasting) and its intricacies are good to have Should possess strong documentation capabilities which would effectively convey complex models and processes Communicate design and results of complex models to a variety of audiences, including senior management, bank supervisors, Model Governance, Internal Audit and LOB end users Coordinate with business partners, including forecasting teams, and end users to ensure accurate model usage and implementation Adhere to model validation governance to ensure models are following policy and are working as intended, address model validation and regulatory feedback issues Solving model development and model analytics/forecasting challenges in python with quick turn arounds Master's degree or higher in a quantitative field such as Statistics/Economics 5+ years of experience in Deposit & PPNR, Treasury Analytics , or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 5+ years of experience in Deposit balance sheet modeling and treasury/liquidity analytics in support of asset & liability management (ALM), FP&A and capital planning by capturing interest rate risk in the banking book (IRRBB) by EVE 5+ years of advanced programming expertise in SAS or Python or R Strong documentation and project management capabilities with ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment Excellent verbal, written, and interpersonal communication skills Strong ability to develop partnerships and collaborate with other business and functional areas Excellent verbal, written, and interpersonal communication skills Perform various complex activities related to deposit balance sheet modeling Provide analytical support for development, remediation, monitoring, and production of Deposit & PPNR models Support development, implementation, execution and monitoring of Regulatory models such as Basel, CECL, and CCAR models Develop dynamic dashboards; analyze key risk parameters to help understand changes in business and model performance Identify opportunities and deliver process improvements, standardization, rationalization and automations Enhance and standardize performance analysis, reporting packages and business loss forecast processes Maintain documentation for development, implementation and monitoring of processes across the team with focus on standardization of controls Ability to identify and manage complex issues and negotiate solutions within a geographically dispersed organization