14 Loss Forecasting Jobs

As the Supervisor of Finance, you will be responsible for managing the preparation, coordination, and documentation of financial reports and analytics, both reported and forward-looking. You will work closely with managers to oversee the budget process and ensure effective budgets are produced. Additionally, you will be involved in preparing financial forecasts and reports and providing strategic analytical expertise within your assigned areas. Identifying issues, suggesting courses of action, and making recommendations for improving operations will also be part of your responsibilities. You will supervise and assign work to direct staff, providing analytical and financial support to senior management. Leading the financial preparation of forecasts, annual budgets, and long-term strategic plans will be crucial. You will also be responsible for preparing schedules and analysis required for compliance activities, such as external audits, quarterly reviews, board of directors materials, and investor relations presentations. Ensuring accurate and timely monthly, quarterly, and yearly reporting is essential. Coordinating across the business and company to obtain information and input on key assumptions and variables will also be part of your role. Supporting the development of the Company's annual budget, as well as tracking and analyzing variances throughout the year, is a key responsibility. Monitoring sales and margins to ensure the appropriate billing margin is earned will also fall under your purview. Qualifications for this role include a Bachelor's degree in Accounting, Finance, or a related business field, with a Master's degree preferred. You should have at least 5 years of financial analysis experience, including discounted cash flow, and 3 years of data query extraction and analytics experience. Additionally, 2 years of prior experience as a Lead or Senior Financial Analyst is required, along with 1 year of profit and loss and balance sheet forecasting and management experience. Strong communication and presentation skills are necessary, with the ability to translate complex analytical data into an easily understandable format. Proficiency in Microsoft Office Suite, especially Excel, is crucial. Strong teamwork, collaboration, problem-solving skills, and the ability to manage and organize large amounts of data are essential. Experience in analyzing financial data, preparing financial reports, statements, and projections is required. Report writing skills utilizing Hyperion and Oracle are preferred. You should be self-directed, take responsibility for projects, and see them through to completion. Experience with short and long-term budgeting and forecasting, rolling budgets, and product-line profitability analysis is a plus. The ability to travel up to 25% may be required.,

Hiring for Multiple Roles 1. SAS, SQL, Marketing Analytics 2. SAS, SQL, Credit Risk Model 3. SAS, SQL Strategy Development 4. SAS, SQLCollection Strategy 5. SAS, SQL, MRM 6. SAS, SQL, Credit Risk Model

Roles and Responsibilities Develop credit risk models using SAS, SQL, and statistical modeling techniques to predict defaults, losses, and other credit-related metrics. Collaborate with cross-functional teams to design and implement effective credit risk strategies that meet business objectives. Conduct stress testing and scenario analysis to identify potential risks and opportunities for growth. Provide data insights and recommendations to stakeholders on loss forecasting, scorecards, and portfolio performance. Desired Candidate Profile 2+ years of experience in Credit Risk Modelling/Analytics or related field. Strong expertise in Basel II/III regulations, CECL/CCAR requirements under IFRS9 framework. Proficiency in programming languages such as Python/R/SAS; strong understanding of machine learning algorithms an added advantage.

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

Salary: 15 to 30 LPA Exp: 3 to 7 years Location: PAN India Notice: Immediate only..!! Key Skills: SQL, Power BI, Credit Risk, risk analytics, MIS, risk reporting Roles and Responsibilities Extract, manipulate, and analyze large datasets from various sources such as Hive, SQL databases, and ETL processes. Develop and maintain dashboards using Tableau to provide insights on banking performance, market trends, and customer behavior. Collaborate with cross-functional teams to identify key performance indicators (KPIs) and develop data visualizations to drive business decisions. Desired Candidate Profile 3-8 years of experience in Data Analytics or related field with expertise in Banking Analytics, Credit risk . Strong proficiency in tools like SQL, Advance SQL knowledge preferred. Experience working with big data technologies like Hadoop ecosystem (Hive), Spark; familiarity with Python programming language required.

Salary: 20 to 35 LPA Exp: 3 to 10 years Location: Bangalore/Gurgaon/Pune Notice : immediate to 30 days..!! Role and Responsibilities: Credit Risk /Fraud Risk Strategy: Role Details: The role is expected to use analytical tools to identify opportunities to grow overall assets as well as manage risk. It involves managing risk management framework across customer lifecycle acquisition, portfolio management and collections, across retail lending products. Responsibilities : - Design, analyze, monitor credit risk strategies for different loan products such as personal loans, auto loans, etc. - Identify the opportunity areas for portfolio growth and pro-actively communicate with stakeholders - Collaborate across other risk functions (example technology, product, etc.) to implement the analytical decisions - Understand existing underwriting rules, strategies and replicate them in business rules using SAS/SQL - Design and analyze income, employment, fraud verification strategies - Develop, maintain and improve risk policies, strategies, processes and procedures within the assigned function - Utilize application, bank and bureau information to derive business insights - KPI generation, tracking of risk and delinquency metrics for portfolios using SQL/Tableau

Salary: 15 to 30 LPA Exp: 3 to 7 years Location: PAN India Notice: Immediate only..!! Key Skills: SAS, Credit Risk, risk analytics, MIS, risk reporting Roles and Responsibilities Extract, manipulate, and analyze large datasets from various sources such as Hive, SQL databases, and ETL processes. Develop and maintain dashboards using Tableau to provide insights on banking performance, market trends, and customer behavior. Collaborate with cross-functional teams to identify key performance indicators (KPIs) and develop data visualizations to drive business decisions. Desired Candidate Profile 3-8 years of experience in Data Analytics or related field with expertise in Banking Analytics, Credit risk . Strong proficiency in tools like SAS, Advance SQL knowledge preferred. Experience working with big data technologies like Hadoop ecosystem (Hive), Spark; familiarity with Python programming language required.

Roles and Responsibilities Develop credit risk models using SAS, SQL, and statistical modeling techniques to predict defaults, losses, and other credit-related metrics. Collaborate with cross-functional teams to design and implement effective credit risk strategies that meet business objectives. Conduct stress testing and scenario analysis to identify potential risks and opportunities for growth. Provide data insights and recommendations to stakeholders on loss forecasting, scorecards, and portfolio performance. Desired Candidate Profile 2+ years of experience in Credit Risk Modelling/Analytics or related field. Strong expertise in Basel II/III regulations, CECL/CCAR requirements under IFRS9 framework. Proficiency in programming languages such as Python/R/SAS; strong understanding of machine learning algorithms an added advantage.

Ensuring that safety & loss prevention measures are effectively integrated into the project lifecycle from design to implementation & operation minimize risks to personnel, assets & the environment Expertise loss prevention Required Candidate profile 10 yrs Exp in Loss Prevention Engineering within the Oil & Gas industry, with a background in EPC / Vendor environments Professional certifications such as CSP, CFPS Fire suppression

Hiring for Multiple Roles 1. SAS, SQL, Marketing Analytics 2. SAS, SQL, Credit Risk Model 3. SAS, SQL Strategy Development 4. SAS, SQLCollection Strategy 5. SAS, SQL, MRM 6. SAS, SQL, Credit Risk Model

About this role: Wells Fargo is seeking a Risk Analytics Consultant In this role, you will: Participate in less complex analysis and modeling initiatives, and identify opportunity for process production, data reconciliation, and model documentation improvements within Risk Management Review and analyze programing models to extract data, and manipulate databases to provide statistical and financial modeling, and exercise independent judgment to guide new and existing projects with medium risk deliverables Coordinate and consolidate the production of monthly, quarterly, and annual performance reports for more experienced management Present recommendations for resolving data reconciliation, production, and database issues Exercise independent judgment while developing expertise in policy governance, risk projects, and regulatory requests Collaborate and consult with peers, managers, experienced managers, compliance, including various lines of business Required Qualifications: 2+ years of Risk Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Experience in Loss Forecasting , CCAR Reporting, Stress testing or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Expertise in few programming and statistical packages - SAS , SQL Advanced expertise in MS office tools including Excel and Powerpoint Strong analytical and problem-solving skills with keen attention to detail Model review and ability to analyze and challenge model parameters and assumptions Understand business objectives and provide challenge to requirements. Knowledge and understanding of credit risk, loss forecasting, and related governance policies. Verify sound analysis practices and data decisions were leveraged throughout planning and data sourcing phases. Conduct in-depth research within complex data environments to identify data integrity issues and propose solutions to improve accuracy. Ensure comprehensive documentation exists supporting the end-to-end data reporting and analysis approach and execution. Understanding of complex databases and ability to navigate and query data effectively. Apply critical evaluation to challenge assumptions, formulate a defendable hypothesis, and ensuring high quality results. Ensure adherence to data management/ model governance regulations and policies. Ensure adherence to compliance and legal regulations and policies on all projects managed Collaborate and consult with peers, colleagues, and more experienced managers to resolve issues and achieve goals. Understanding in Python, Tableau, PowerBI will be an added advantage.

Roles and Responsibilities Develop credit risk models using SAS, SQL, and statistical modeling techniques to predict defaults, losses, and other credit-related metrics. Collaborate with cross-functional teams to design and implement effective credit risk strategies that meet business objectives. Conduct stress testing and scenario analysis to identify potential risks and opportunities for growth. Provide data insights and recommendations to stakeholders on loss forecasting, scorecards, and portfolio performance. Desired Candidate Profile 2+ years of experience in Credit Risk Modelling/Analytics or related field. Strong expertise in Basel II/III regulations, CECL/CCAR requirements under IFRS9 framework. Proficiency in programming languages such as Python/R/SAS; strong understanding of machine learning algorithms an added advantage.

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

Roles and Responsibilities Develop credit risk or fraud risk models using Python, SQL, and statistical modeling techniques to predict defaults, losses, and other credit-related metrics. Collaborate with cross-functional teams to design and implement effective credit risk strategies that meet business objectives. Conduct stress testing and scenario analysis to identify potential risks and opportunities for growth. Provide data insights and recommendations to stakeholders on loss forecasting, scorecards, and portfolio performance. Desired Candidate Profile 5+ years of experience in Credit Risk Modelling/ Fraud Modeling or related field. Strong expertise in PD, LGD Model Development ,Basel II/III regulations, CECL/CCAR requirements under IFRS9 framework. Proficiency in programming languages such as Python/R/SAS/SQL; strong understanding of machine learning algorithms an added advantage.