196 Fraud Analytics Jobs - Page 8

Profile - AML/KYC Analyst Location - Noida Salary - upto 45k Inhand Qualification - Any Graduate Experience - 1-3 Year Skills - Excellent Communication skills Contact us - Rahul Aryan (HR) - 9315128616 (Whatsapp/Call)

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.

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.

Roles and Responsibilities Review and assess content quality, accuracy, and compliance with community guidelines. Identify potential fraudulent activities on the platform and report them to relevant teams. Provide feedback on process improvements for content review processes.

Job Title: Senior Fraud Risk Modeler (Credit Card) About Straive: Straive is a market leading Content and Data Technology company providing data services, subject matter expertise, & technology solutions to multiple domains. Data Analytics & Al Solutions, Data Al Powered Operations and Education & Learning form the core pillars of the companys long-term vision. The company is a specialized solutions provider to business information providers in finance, insurance, legal, real estate, life sciences and logistics. Straive continues to be the leading content services provider to research and education publishers. Data Analytics & Al Services: Our Data Solutions business has become critical to our client's success. We use technology and Al with human experts-in loop to create data assets that our clients use to power their data products and their end customers' workflows. As our clients expect us to become their future fit Analytics and Al partner, they look to us for help in building data analytics and Al enterprise capabilities for them. With a client-base scoping 30 countries worldwide, Straives multi-geographical resource pool is strategically located in eight countries - India, Philippines, USA, Nicaragua, Vietnam, United Kingdom, and the company headquarters in Singapore. Website: https://www.straive.com/ Job Summary: As a Senior Risk Modeler specializing in Fraud Risk, you will design, develop, and maintain models to detect and prevent fraud across various financial products and channels - primarily in the credit card domain. Youll analyze emerging fraud trends, assess fraud risk, and support fraud prevention strategies, while clearly communicating insights to stakeholders and collaborating with cross-functional teams to enhance fraud detection capabilities and reduce fraud losses. Model Development & Validation : Build, implement, and validate fraud detection and prevention models using advanced statistical and machine learning techniques for credit card products. Data Analysis & Interpretation : Analyze large-scale transactional and behavioral data to identify fraud patterns, assess model performance, and provide actionable insights. ¢ Risk Assessment & Monitoring : Evaluate existing fraud controls, monitor fraud trends, and quantify exposure to evolving threats across digital and traditional channels. ¢ Communication & Collaboration : Effectively present analytical findings and model performance to both technical and non-technical stakeholders, including fraud operations, compliance, and executive leadership. ¢ Documentation & Reporting : Maintain comprehensive documentation of model development processes, risk assumptions, fraud detection frameworks, and compliance requirements. ¢ Technical Skills : Strong proficiency in Python, SQL, and data science tools; familiarity with real-time decision engines and fraud detection platforms is a plus. (e.g., Actimize, Falcon, SAS). ¢ Domain Expertise : Deep understanding of fraud domain expertise for debit card product. ¢ Leadership & Teamwork : Ability to lead fraud analytics initiatives, mentor junior analysts or data scientists, and collaborate with risk, IT, and fraud operations teams. ¢ Problem Solving : Proactively identify vulnerabilities in fraud strategies, recommend enhancements, and respond to emerging threats in a fast-paced environment. ¢ Adaptability : Stay current with the latest fraud schemes, detection technologies, and regulatory developments impacting fraud risk management. Qualifications: Bachelors or Masters. in a quantitative discipline such as Statistics, Mathematics, Computer Science, Economics, Data Science, or a related field. 6 to 7 years of hands-on experience in a banking environment , specifically in developing, implementing, and maintaining fraud risk models across products and channels. Proven experience in fraud analytics and modelling , including transaction monitoring, real-time detection, and rules-based or machine learning-driven approaches. Strong programming skills in Python, SQL, R, or SAS for model development, data manipulation, and automation. Proficiency with machine learning and statistical techniques such as decision trees, gradient boosting, clustering, anomaly detection, and neural networks. Good understanding of how linear regression and XGBoost work, including their assumptions, strengths, and limitations. Solid understanding of fraud typologies and fraud prevention technologies. Demonstrated ability to work with large and complex datasets , conduct deep-dive analytics, and extract actionable insights. Excellent communication and stakeholder management skills , with the ability to clearly articulate model logic, assumptions, and outcomes to non-technical audiences. Experience performing fraud model validation, performance monitoring, and tuning processes to ensure effectiveness and compliance. Strong problem-solving skills to address emerging fraud risks, data quality challenges, and operational issues.

Fraud Analytics Roles and Responsibilities: • Utilize data analytics tools and methodologies to conduct in-depth assessments and generate reports on fraud trends (including first-party and third-party fraud). • Investigate suspicious activities and transactions, determine root causes and develop strategies and statistical models to prevent future occurrences. • Develop Fraud rules on workflow systems e.g. Actimize. • Develop fraud reports for ongoing monitoring of fraud events. • Generate reports and presentations outlining fraud risks, incidents, and mitigation strategies for management review. • Collaborate with cross-functional teams, including risk management, operations, and compliance, to enhance fraud prevention measures. • Monitor industry trends, regulatory changes, and best practices to continually enhance fraud prevention strategies. For Manager Level: • Experience in leading high performance data analytics teams to deliver impact. • Motivate team to deliver high quality output and quality check team output. • Synthesize and present findings to senior client management. • Good understanding of banking products and services, and regulations. Skills Required: • Bachelor's degree in engineering, technology, computer science or related field. Masters degree or certifications in fraud examination or risk management is a plus. • 3+ years of proven data analytics experience in fraud prevention, risk management, or a related field • Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance. • Excellent communication and presentation skills with the ability to convey complex information clearly and concisely. • Detail-oriented with a proactive mindset toward problem-solving and risk mitigation. • Ability to work collaboratively in a cross-functional team environment. For Manager Level • 7+ years of experience in data analytics in fraud, risk or related field. Experience in business development is a plus. • 3+ years of experience in leading teams

Fraud Analytics Expertise Ability to find fraud patterns in digital transactions and understand fraud modus operandi. Fraud Control Creation & Implementation – Skilled at designing, testing, and deploying fraud prevention controls. FRM Tool Experience – Hands-on with tools like Clari5 or Falcon . Advanced Data Skills – Strong in Excel (macros, data analysis) and preferably SAS/Python. RBI Guidelines Knowledge – Clear understanding of fraud risk regulatory requirements. Leadership & Team Management – Leading teams, creating SOPs, and ensuring governance. Cross-functional Collaboration – Working with IT, business teams, and senior management to implement strategies.

Job Title : Fraud Analytics Location State : Karnataka Location City : Bengaluru Experience Required : 3 to 10 Year(s) CTC Range : 15 to 30 LPA Shift: Rotational Work Mode: Onsite Position Type: Permanent Openings: 10 Company Name: VARITE INDIA PRIVATE LIMITED About The Client: Client is a leading global professional services company that helps the worlds leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services. About The Job: Fraud Data Analyst is responsible for designing unique analytic approaches to detect, assess, and mitigate identity and fraud risk. Analyze the effectiveness of our day-to-day fraud policy and rules in our fraud systems. Analyze large amounts of applications, account, and transaction data to build actionable insights to derive the methods to identify fraud risk, reduce friction and enhance experience on money movement. Data governance & management, data science, analytics (Artificial Intelligence, Machine Learning, Natural Language Processing/Generation, Network Analysis, etc.) and technology to predict, identify, detect, measure, and prevent internal and external fraud, bribery and corruption for an organization Essential Job Functions: Fraud Data Analyst is responsible for designing unique analytic approaches to detect, assess, and mitigate identity and fraud risk. Analyze the effectiveness of our day-to-day fraud policy and rules in our fraud systems. Analyze large amounts of applications, account, and transaction data to build actionable insights to derive the methods to identify fraud risk, reduce friction and enhance experience on money movement. Data governance & management, data science, analytics (Artificial Intelligence, Machine Learning, Natural Language Processing/Generation, Network Analysis, etc.) and technology to predict, identify, detect, measure, and prevent internal and external fraud, bribery and corruption for an organization Develop new data driven rules with data attributes and ML scores that optimize decisioning performance between member experience and fraud prevention Develop data insights to help understand customers’ banking behavior and preferences Develop personalized segmentations and micro-segmentation to identify customers based on their fraud risk, banking behavioral, and value Work with external fraud prevention vendors to optimize their performance and assist in maintaining, design and implementation of existing and new fraud detection tools Aggregate and analyze internal and external risk datasets to understand performance of fraud decisioning and granular performance of multiple decision methods Find insights from risk data sets to improve fraud strategies and rules Participate in regular root-cause analysis to form the correct hypothesis in preparing for fraud detection framework Able to lead fraud/risk investigations for both simple and complex cases to successful conclusions and mark false positives and false negative cases Qualifications: Skill required: Delivery - Fraud Data & Analytics Education:Any Graduation Years of Experience:3 to 10 years Strong knowledge of financial products and processes, including Account Application, ACH, RDC, debit cards, credit cards, P2P, lending products, and deposit accounts Knowledge of CIP and fraud related verification and authentication processes including DOCV, eCBSV, MFA, KBA, and more. An expert in SQL, Tableau, preferred to have Python based data analytics experience Experience with working with fraud solutions vendors and their data directly, such as Socure, Sentilink, iOvation, LexisNexus, Falcon, Visa, Zelle, and more Fraud analytics: 5+ years Data and ML analytics: 3+ years Reporting analytics, e.g. tableau: 5 + years How to Apply: Interested candidates are invited to submit their resume using the apply online button on this job post. Equal Opportunity Employer: VARITE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, veteran status, or disability status. Unlock Rewards: Refer Candidates and Earn. If you're not available or interested in this opportunity, please pass this along to anyone in your network who might be a good fit and interested in our open positions. VARITE offers a Candidate Referral program, where you'll receive a one-time referral bonus based on the following scale if the referred candidate completes a three-month assignment with VARITE. Exp Req - Referral Bonus 0 - 2 Yrs. - INR 5,000 2 - 6 Yrs. - INR 7,500 6 + Yrs. - INR 10,000 About VARITE: VARITE is a global staffing and IT consulting company providing technical consulting and team augmentation services to Fortune 500 Companies in USA, UK, CANADA and INDIA. VARITE is currently a primary and direct vendor to the leading corporations in the verticals of Networking, Cloud Infrastructure, Hardware and Software, Digital Marketing and Media Solutions, Clinical Diagnostics, Utilities, Gaming and Entertainment, and Financial Services.

Job Title: Fraud Analytics Specialist - Bengaluru Job Overview: We are looking for a highly analytical and detail-oriented Fraud Analytics Specialist to join our team. This role is critical in safeguarding our organization against fraudulent activities by leveraging advanced analytics, strategic thinking, and cutting-edge fraud detection tools. Key Responsibilities: Fraud Detection & Prevention Monitor transactional data to identify suspicious patterns and potential fraud Develop and implement fraud detection models and rule-based systems Proactively identify emerging fraud trends and recommend mitigation strategies Collaborate with internal teams to enhance fraud controls and reduce risk exposure Fraud Investigation & Strategy Conduct thorough investigations into suspected fraudulent activities Perform root cause analysis and document findings for internal reporting Design and refine fraud prevention strategies based on data insights Liaise with legal, compliance, and law enforcement teams when necessary Analytics & Reporting Extract, analyze, and interpret large datasets using SQL and Python Build interactive dashboards and visualizations in Tableau to track fraud metrics Generate regular reports on fraud incidents, trends, and KPIs for senior management Evaluate the effectiveness of fraud detection tools and recommend improvements Cross-Functional Collaboration Work closely with product, engineering, risk, and customer support teams Provide training and guidance to internal teams on fraud awareness and best practices Support audits and compliance reviews related to fraud risk management Skills & Attributes Deep understanding of fraud detection, investigation, and prevention techniques Experience designing and executing fraud strategies across digital platforms Familiarity with financial crime patterns, identity theft, and transaction fraud SQL: Advanced querying for data extraction, manipulation, and analysis Tableau: Building dashboards and visualizations for fraud monitoring Python (Preferred): Data analytics, automation, and model development Sentilink Identity verification iOvation Device intelligence LexisNexis Risk solutions Falcon Card fraud detection Visa Payment fraud analytics Zelle Peer-to-peer fraud monitoring

Hiring AML with Transaction Monitoring requires excellent English with a minimum of 1 year of experience in the AML process. Rotation shift, 2 Rotation week off, Both ways cabs available. Non-voice process immediate joining Chennai Candidates * Required Candidate profile Should have AML with Transaction Monitoring Process experience Call us to line up your interview Khushi-9811121475 Sukriti -8176976655 Palak-8115955507 Riya-8176074455 Arjuna-9810615875 *

Hiring KYC Profile, required excellent English with a minimum exp of 1 Year in the International KYC process. Rotation shift, 2 Rotation week off, Both ways cabs available. Non-voice process immediate joining Online interview only * Required Candidate profile Should have International KYC Process experience / FATCA Graduation is Must Salary up to 5.5 LPA call Khushi-9811121475 Sukriti -8176976655 Palak-8115955507 Riya-8176074455 Arjuna-9810615875 *

Fraud Analytics 1. Develop Fraud Detection Models: Design and deploy predictive analytics models and machine learning algorithms to identify suspicious activities and patterns. 2. Enhance Systems: Continuously optimize fraud monitoring systems to improve detection accuracy and reduce false positives. 3. Data-Driven Insights: Analyse internal and external data sources to identify vulnerabilities and recommend proactive measures. 4. Performance Metrics: Define and track key performance indicators (KPIs) to measure the effectiveness of fraud detection strategies. Market Intelligence 1. Industry Monitoring: Stay updated on emerging fraud tactics, industry benchmarks, and regulatory changes. 2. Competitor Analysis: Analyze competitors risk management strategies to identify opportunities for improvement. 3. Market Trends: Provide actionable insights from market intelligence to inform strategic decision-making. Team Leadership 1. Build and Lead: Recruit, develop, and mentor a high-performing team of data analysts, data scientists, and market intelligence specialists. 2. Stakeholder Collaboration: Work closely with risk management, compliance, IT, and other departments to ensure alignment and effective communication. . Qualifications Education Masters degree in Data Science, Statistics, Economics, Business Administration, or a related field. Experience 10+ years of experience in fraud analytics, risk management, or data analytics Proven track record of developing and implementing fraud detection systems. Experience with market intelligence tools and competitive analysis. Technical Skills Expertise in data analytics tools (e.g., Python, R, SQL, SAS). Familiarity with machine learning platforms and fraud detection software. Knowledge of industry-specific regulations and compliance standards. Key Competencies Strong analytical and problem-solving skills. Excellent leadership and team-building abilities. Strategic thinker with strong business acumen. Effective communicator with the ability to convey complex data insights to non-technical stakeholders

About this role: Wells Fargo is seeking a Lead Analytics Consultant In this role, you will: Advise line of business and companywide functions on business strategies based on research of performance metrics, trends in population distributions, and other complex data analysis to maximize profits and asset growth, and minimize operating losses within risk and other operating standards Provide influence and leadership in the identification of new tools and methods to analyze data Ensure adherence to compliance and legal regulations and policies on all projects managed Provide updates on project logs, monthly budget forecasts, monthly newsletters, and operations reviews Assist managers in building quarterly and annual plans and forecast future market research needs for business partners supported Strategically collaborate and consult with peers, colleagues, and mid-level to senior managers to resolve issues and achieve goals Lead projects, teams, or serve as a peer mentor to staff, interns and external contractors Be responsible for performing various complex activities related to fraud, claims and scam risk prevention and detection efforts for fraud analytics including Deposits (Check, MRDC, ACH), credit card, debit card, wires, and online money movement products including optimization of existing strategies, creating new detection or prevention strategies/rules to increase overall detection rates, and managing controls for a given set of money movement products. Team member must be able to work and align with operations and the broader fraud and scam mitigation strategy. The position will communicate regularly with team members and management both internally and the broader Wells Fargo enterprise fraud community to share trends or analysis, facilitate strategy development, or drive mitigation work streams. Required Qualifications: 5+ years of Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education 5+ years of experience in one or a combination of the following: strategy development and evaluation, analytics, reporting. Experience with partnering and collaborating across lines of business and with operations to deploy prevention and detection strategies. BS/BTech degree or higher in a quantitative field such as applied math, statistics, engineering, physics Strong analytical skills with high attention to detail and accuracy Fraud Strategy Fraud domain understanding experience 4+ years of SAS (e.g. Enterprise Guide or Enterprise Miner or Base SAS) and/or Python or R experience Demonstrated experience with Strategy development and evaluation. Ability to create documentation of process flows, business analysis and metadata, and conduct root cause analysis. Experience in Financial services or knowledge of consumer/retail financial products Demonstrated critical thinking and problem-solving skills. Desired Qualifications Collaborate across Lines of business including operations on fraud and scam mitigation efforts. Provide analytical support for different types of fraud identification and prevention/detection strategies. Perform ad-hoc analysis to understand portfolio trends and develop actionable solutions. Support analysis and development of strategies, methods, and other fraud- related projects Establish mechanisms to manage and mitigate fraud risks for all portfolios. Leads project and mentors junior Team Members Serve as a valuable resource to the other members of the team while promoting knowledge sharing and team collaboration. Knowledge and understanding of fraud detection process in banking. Predictive modeling AI-ML basics Strong analytical skills with high attention to detail and accuracy Dedicated, enthusiastic, self-driven and performance-oriented and capable of handling multiple projects simultaneously. Possesses a strong work ethic and thrives in a collaborative team environment. Excellent verbal, written, and interpersonal communication skills and demonstratable strong presentation skills; ability to tell the story to an executive audience. Engage with cross culture team members and stakeholders, and other lines of business with competing priorities. Understanding of retail branch, phone, and digital customer experience Experience working on BI Tools like QlikView or Tableau Experience with MS Office Suite (PowerPoint, Excel, Word) intermediate at a minimum

E Role & responsibilities Hiring for Fraud Investigation Profile & Transaction Monitoring / Work from Office / Salary Max-7.5lpa Minimum 2 year exp and above in fraud investigator or Transaction Monitoring 5 days work 2 week offUS Rotational shift & off1 way transportBangalore location onlyImmediate Joiners only Key Responsibilities: (Transaction Monitoring) Conduct transaction monitoring to identify unusual patterns and potential fraudulent activities. Perform KYB checks to verify business client authenticity and mitigate risk. Analyze and review alerts generated by transaction monitoring systems. Conduct investigations on suspicious activities and escalate cases as necessary. Ensure compliance with regulatory requirements and internal policies. Prepare and submit periodic reports on monitoring activities. Collaborate with the compliance team to enhance existing processes and controls. Roles & Responsibilities: (Fraud Investigation) Identifying, investigating, and preventing fraudulent activities Tracking down individuals involved in illegal or suspicious activities and interviewing them. The case documentation should be carefully examined to understand the history of the suspects violations and to retain the information necessary for future references. Examining various documents like victim testimonies and financial records to find out whether the fraud occurred Prepare reports that clearly state the investigations and evidence Identifying any possible threats to the company and taking appropriate actions to avoid them promptly. Doing background checks, employee investigations, and asset searches on suspected individuals. Graduates OnlyRequired docs:Aadhar card, Pan card, Educational Documents, Previous organization offer letter/ Relieving letter or resignation acceptance mail if quit recently & payslips For more details Call HR Gayathri 9538878905 (WHATSAPP OR CALL) Email - gayathri@thejobfactory.co.in Preferred candidate profile

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.

We are urgently hiring for "AML" analyst - Minimum 1 yr of relevant experience (AML,KYC,Sanctions,PEP). - Salary upto 32 k - Shifts 24*7 (Work from office) - 5 days working, 2 weekoffs - UG and Graduate both can apply HR Arti 9522754537 Required Candidate profile Excellent communication is required 1 year experience is mandate in Aml undergraduate and graduate both can apply

Job Description: We are seeking a detail-oriented and analytical Fraud Detection and Investigation Specialist to join our Risk & Compliance team. The ideal candidate will be responsible for identifying, investigating, and mitigating fraud across various business functions. You will play a key role in safeguarding company assets, ensuring regulatory compliance, and maintaining stakeholder trust. To apply, Call/WhatsApp Miss Susanah at 9910069479 Key Responsibilities: Monitor transactions and activities to detect potential fraud patterns. Conduct in-depth investigations into suspected fraudulent activities. Work closely with internal teams and external stakeholders to gather evidence and document findings. Develop and enhance fraud detection tools, models, and protocols. Prepare detailed reports and present findings to management and legal teams. Support compliance with local and international regulatory requirements. Qualifications: Bachelors degree in Finance, Accounting, Forensics, Criminology, or related field. 1+ years of experience in fraud detection, investigation, or risk management. Strong analytical and investigative skills with proficiency in data analysis tools. Knowledge of fraud prevention technologies and regulatory frameworks. To apply, Call/WhatsApp Miss Susanah at 9910069479

About the team: This team involves in making a difference. A lot of contingency and new challenges are encouraged within the team to do stuff that is meaningful for those we serve. We are successful, and our successes are rooted in our people's collective energy and unwavering focus on the employees, and that's how it will always be change management in Social Media. About the Role: As a Manager in Fraud Analytics, you will play a key role in monitoring, analyzing, and preventing fraudulent activities across our payment platforms. Reporting to the Senior Manager Fraud Analytics, you will be responsible for building and maintaining fraud detection models, configuring rules, and supporting control-related projects. You will also collaborate with other teams such as Risk ops, Product, and Engineering to ensure that the organizations risk controls are both effective and scalable. Key Responsibilities: Develop and refine fraud detection models, leveraging both rule-based and data-driven approaches to prevent and mitigate fraud risks. Monitor real-time transaction data for suspicious activity, escalating concerns and providing recommendations for corrective action. Assist in the configuration of fraud detection rules within the transaction monitoring system, ensuring accuracy and minimal false positives. Analyze fraud trends and transaction patterns to proactively address potential vulnerabilities and emerging fraud schemes. Collaborate with cross-functional teams, including Risk, Compliance, and Product, to ensure fraud risk mitigation strategies are aligned with business objectives. Support fraud-related control projects, from planning through to execution, ensuring compliance with RBI regulations and internal risk frameworks. Assist in preparing fraud risk reports for senior management, outlining key insights, emerging trends, and actionable recommendations. Work closely with the Senior Manager to ensure regulatory requirements are met, including adherence to RBI and other regulatory standards. Continuously improve fraud monitoring tools and techniques, suggesting enhancements to improve fraud detection accuracy and efficiency. Participate in regulatory audits and assist in responding to fraud-related queries from authorities. Qualifications: A bachelors degree in Data Analytics, Statistics, Risk Management, or a related field is preferred. 4-8 years of experience in fraud analytics, risk management, or a related role within the fintech or payments industry. Strong understanding of fraud detection techniques, including rule-based systems and data-driven models. Experience with fraud detection tools, transaction monitoring systems, and data analytics platforms. Familiarity with RBI guidelines and other regulatory frameworks governing payment companies in India. Strong analytical and problem-solving skills, with the ability to identify trends and make data-driven decisions. Excellent communication skills, with the ability to present insights and findings clearly to both technical and non-technical audiences. Experience working in a high-volume transaction environment, such as a payments gateway, mobile wallet, or UPI system. Preferred Skills: Knowledge of machine learning models for fraud detection. Experience working with fraud detection systems in the fintech space, especially in a licensed TPAP setup. Familiarity with compliance and audit requirements in a regulated financial environment.

We are looking for a highly skilled and experienced Fraud Risk Analyst to join our team at Equitas Small Finance Bank. The ideal candidate will have 2 to 7 years of experience in the BFSI industry, with expertise in fraud risk analysis and mitigation strategies. Roles and Responsibility Conduct thorough analysis of customer data to identify potential fraud risks. Develop and implement effective fraud prevention measures to minimize losses. Collaborate with cross-functional teams to investigate and resolve fraudulent activities. Identify trends and patterns in fraud data to inform future prevention strategies. Provide expert guidance on fraud-related matters to internal stakeholders. Stay up-to-date with industry developments and best practices in fraud prevention. Job Requirements Strong understanding of fraud analytics tools and techniques. Excellent analytical and problem-solving skills with attention to detail. Ability to interpret complex data sets and communicate findings effectively. Experience working in a fast-paced environment with multiple priorities. Strong collaboration and communication skills with internal stakeholders. Familiarity with regulatory requirements related to fraud prevention.

Graduate with 6 months banking exp on paper (fraud,dispute exp or knowledge) Salary - 28*950 inhand + incentives 5 days working with any 2 week off Rotational shift HR apoorva Required Candidate profile banking experience is mandatory

Forensic-Ftech KPMG has a dedicated Forensic Technology lab which enables the recovery and use of critical digital evidence to support investigations and litigation. Using various tools (proprietary, open source, vendor tools), we can extract, transform and visualize information from any source in any format, including laptops, mobile phones and other electronic devices. The tools can help establish whether evidence has been erased or modified; analyze electronic content and patterns of Internet and e-Mail usage; recover deleted data; and assess and explain metadata within recovered files, even if certain persons sought to destroy it. 2-5 Years of experience. Preferably from Big 4 Hands on experience in data crunching through SQL Technical knowledge of methods of anomaly detection Experience in fraud investigations, fraud analytics Good in report writing (MS Office) Proficiency in Microsoft Office and Windows based applications Good communication, presentation, and organizational skills Demonstrated ability to communicate complex technical problems in simple plain stories. Ability to present information professionally & concisely with supporting data. Ability to work effectively & independently in a dynamic environment with tight deadlines. Ability to engage with cross-functional teams for driving the project .