Risk Analytics

Shobit Kumar Singhal | Assistant Manager | Barclays

What is Risk Analytics?

A Career in Risk Analytics is very intriguing. Almost everyone seems to be talking about How to start a Career in Risk Analytics, while one should first develop an understanding of What is a Career in Risk Analytics. While anyone can have an opinion on what Risk Analytics entails; only a real professional can really explain it.

Assistant Manager Shobit Kumar Singhal has worked in Risk Analytics for 2 years. Here is how Assistant Manager Shobit Kumar Singhal detailed Risk Analytics:

Risk analysis is the process of identifying and analyzing potential issues that could negatively impact key business initiatives or critical projects in order to help organizations avoid or mitigate those risks.

How Assistant Manager Shobit Kumar Singhal got into Risk Analytics?

After completing my education, I joined Barclays as senior analyst and I am working as an Assistant Manager at Barclays.

Assistant Manager Shobit Kumar Singhal's Talk on Risk Analytics

The Journey of Risk Analytics What Is Risk Analytics Risk Analytics Risk Analytics is the systematic process of identifying, assessing, and prioritizing risks using data analysis, statistical models, and technology. It enables organizations to make informed decisions by quantifying potential threats and opportunities, ultimately helping to minimize losses and maximize gains in an increasingly complex business environment. Risk Analytics plays a crucial role in modern organizations by providing actionable insights that drive strategic decision-making. For professionals in this field, it offers the ability to anticipate potential issues before they arise, ensuring better resource allocation and improved operational efficiency. One major benefit is enhanced decision-making, as data-driven insights reduce uncertainty. Another significant advantage is regulatory compliance, as analytics help organizations meet industry standards and avoid penalties. Additionally, Risk Analytics supports competitive advantage by identifying emerging risks and opportunities faster than competitors, allowing businesses to adapt proactively in a dynamic marketplace. A financial institution employs Risk Analytics professionals to monitor and manage credit risk within its loan portfolio. By analyzing historical loan data, market trends, and customer behavior, these experts build predictive models that estimate the likelihood of default for each borrower. This enables the bank to adjust lending policies, set appropriate interest rates, and allocate capital more efficiently. When early warning signs of increased risk appear, such as changes in economic indicators or shifts in customer payment patterns, the analytics team can recommend timely interventions. As a result, the institution reduces its exposure to bad debt, improves profitability, and maintains regulatory compliance, all while delivering better value to its customers. Education Economics Economics is the study of how individuals, organizations, and societies allocate scarce resources to satisfy unlimited wants and needs. It examines decision-making processes, market dynamics, and the impact of policies on economic outcomes. For Risk Analytics, economics provides essential frameworks for understanding market behavior, risk factors, and the broader financial environment. A solid grasp of economics is indispensable for anyone pursuing a career in Risk Analytics. Economics equips professionals with the ability to interpret market signals, anticipate shifts in supply and demand, and understand the ripple effects of macroeconomic events on financial systems. This foundational knowledge enables risk analysts to assess potential threats and opportunities with greater accuracy, supporting more informed decision-making. Over the long term, expertise in economics enhances a professional’s ability to communicate complex risk scenarios to stakeholders, adapt to evolving market conditions, and contribute to strategic planning. As economic landscapes shift, those with a strong economic background remain agile, ensuring their analyses remain relevant and impactful in a rapidly changing world. Consider a risk analyst working at a financial institution who is tasked with evaluating the potential impact of an interest rate hike by the central bank. Drawing on their understanding of economics, the analyst assesses how higher borrowing costs might reduce consumer spending and corporate investment, potentially slowing economic growth. They also evaluate how these changes could affect the institution’s loan portfolio, default rates, and overall profitability. By integrating economic theory with real-time data, the analyst is able to forecast potential risks, recommend adjustments to lending strategies, and communicate these insights to senior management. This application of economics ensures the institution remains resilient in the face of shifting economic conditions. Advanced Statistics Advanced Statistics refers to the study and application of complex statistical methods, including multivariate analysis, time series modeling, hypothesis testing, and predictive analytics. In Risk Analytics, it forms a critical part of the academic and professional toolkit, enabling practitioners to interpret data, quantify uncertainty, and make informed, data-driven decisions in complex environments. A strong grasp of advanced statistical techniques is essential for anyone aspiring to excel in Risk Analytics. This field relies on the ability to analyze large and often messy datasets, identify patterns, and assess probabilities of adverse events. Mastery of advanced statistics empowers professionals to build robust risk models, validate assumptions, and communicate findings with clarity and confidence. Over time, this expertise not only enhances analytical accuracy but also supports career advancement by demonstrating a capacity for rigorous problem-solving and strategic thinking. As organizations increasingly depend on data-driven insights to manage uncertainty, professionals with advanced statistical skills become indispensable assets, capable of translating complex data into actionable risk mitigation strategies. Consider a risk analyst working for a financial institution tasked with assessing the likelihood of loan defaults. By applying advanced statistical methods such as logistic regression and survival analysis, the analyst can model the probability of default based on borrower characteristics and economic indicators. This theoretical knowledge allows the analyst to identify significant predictors, quantify the impact of various risk factors, and simulate different economic scenarios. The results inform the institution’s lending policies, helping to minimize losses while maintaining profitability. In daily operations, the analyst’s expertise in advanced statistics ensures that risk assessments are not only accurate but also adaptable to changing market conditions, ultimately supporting sound decision-making and regulatory compliance. Data Intrerpretation Data interpretation is the process of analyzing data sets to extract meaningful insights, identify patterns, and draw logical conclusions. In Risk Analytics, it bridges raw data and actionable intelligence, enabling professionals to assess uncertainties, predict outcomes, and make informed decisions. Mastery of this skill is essential for academic and professional success. Understanding data interpretation is crucial for anyone aspiring to excel in Risk Analytics because it underpins every aspect of risk assessment and management. Professionals must not only collect and process data but also critically evaluate its significance, accuracy, and implications. This skill allows them to transform complex data into clear, actionable recommendations that drive strategic decision-making. Over time, proficiency in data interpretation enhances an individual’s ability to anticipate potential risks, communicate findings effectively to stakeholders, and adapt to evolving analytical tools and methodologies. As organizations increasingly rely on data-driven insights to navigate uncertainty, those with strong data interpretation capabilities are better positioned for career advancement and long-term success in the field. Consider a risk analyst working for a financial institution who receives a large dataset detailing customer credit histories, transaction patterns, and market trends. By applying their knowledge of data interpretation, the analyst identifies subtle correlations between certain spending behaviors and loan default rates. They recognize that a recent uptick in specific transaction types coincides with increased risk exposure. Drawing on this insight, the analyst communicates their findings to management, recommending adjustments to the institution’s lending criteria. This real-world application of data interpretation not only helps the organization mitigate potential losses but also demonstrates the analyst’s ability to convert theoretical knowledge into practical, value-driven solutions. Programming Languages Programming languages are formal systems of communication used to instruct computers to perform specific tasks. They enable the creation, manipulation, and analysis of data through structured commands and logic. In Risk Analytics, programming languages are essential tools for automating processes, building models, and extracting actionable insights from complex datasets. Understanding programming languages is crucial for anyone pursuing a career in Risk Analytics because it empowers professionals to efficiently process and analyze large volumes of data. Mastery of languages such as Python, R, or SQL allows analysts to automate repetitive tasks, develop custom risk models, and implement advanced statistical techniques. This technical proficiency not only enhances productivity but also enables deeper exploration of data, leading to more accurate risk assessments and informed decision-making. Over the long term, strong programming skills provide a competitive edge, opening doors to advanced roles and enabling professionals to adapt to evolving technologies and methodologies within the risk analytics field. Consider a risk analyst working at a financial institution who is tasked with assessing the credit risk of loan applicants. By leveraging their knowledge of programming languages, the analyst can write scripts to automatically clean and preprocess large datasets, apply statistical models to predict default probabilities, and visualize the results for stakeholders. This approach streamlines the entire workflow, reduces the potential for human error, and allows the analyst to quickly adjust models in response to new data or regulatory requirements. Ultimately, the ability to program transforms theoretical knowledge into practical solutions, directly impacting the quality and efficiency of risk assessments. Skills Reading & Research Reading & Research refers to the continuous process of gathering, analyzing, and synthesizing information from diverse sources to stay updated, solve problems, and make informed decisions. In Risk Analytics, this skill enables professionals to understand emerging risks, regulatory changes, and industry trends, forming the foundation for accurate analysis and strategic recommendations. Mastering Reading & Research directly enhances a risk analyst’s ability to identify potential threats, interpret complex data, and recommend effective mitigation strategies. Employers and clients value this skill because it ensures that analyses are grounded in the latest evidence and best practices, reducing the likelihood of oversight or outdated conclusions. Cultivating this skill involves regularly engaging with academic journals, industry reports, and regulatory updates, as well as developing critical thinking to assess the credibility and relevance of sources. Over time, consistent practice sharpens the ability to quickly extract key insights and apply them to real-world scenarios, making the professional indispensable in dynamic and high-stakes environments. Imagine a risk analyst working for a financial institution during a period of economic uncertainty. Faced with ambiguous market signals and evolving regulations, the analyst embarks on thorough reading and research, reviewing recent economic studies, government policy updates, and global market reports. By synthesizing this information, the analyst identifies early indicators of a potential credit risk surge. Armed with these insights, they advise the institution to adjust its lending criteria and enhance monitoring protocols, ultimately safeguarding the organization from significant financial losses. This scenario highlights how adept reading and research can directly influence strategic decisions and protect a company’s interests in volatile conditions. Communication Skills Communication skills refer to the ability to clearly and effectively convey information, ideas, and insights through verbal, written, and visual means, while also actively listening and adapting messages to different audiences. In Risk Analytics, these skills are vital for translating complex data findings into actionable recommendations that stakeholders can understand and trust. Strong communication skills directly enhance a Risk Analytics professional’s performance by ensuring that technical analyses are not only accurate but also accessible to non-technical audiences. Clients and employers highly value this skill because it bridges the gap between data-driven insights and strategic decision-making, enabling organizations to act confidently on risk assessments. To cultivate communication skills, professionals should seek opportunities to present findings, write clear reports, and engage in active listening during meetings. Over time, consistent practice, feedback from colleagues, and adapting communication styles to suit different stakeholders help refine this essential skill, making the professional a more effective and trusted advisor in risk-related matters. Imagine a Risk Analytics professional tasked with presenting the results of a complex risk model to a company’s executive team during a crisis. The executives are not familiar with statistical jargon or technical details. By leveraging strong communication skills, the analyst distills the findings into clear, concise language, uses relatable analogies, and highlights the practical implications of the data. This approach not only reassures the executives but also enables them to make informed decisions quickly, mitigating potential losses. The analyst’s ability to bridge the technical and business worlds through effective communication proves critical to the organization’s successful navigation of the crisis. Attention to Detail Attention to detail is the ability to thoroughly and accurately process information, identifying even the smallest discrepancies or errors while maintaining a comprehensive understanding of the bigger picture. In Risk Analytics, this skill ensures that data is interpreted correctly, models are built accurately, and potential risks are identified before they escalate. Attention to detail directly enhances performance in Risk Analytics by minimizing errors in data analysis, model development, and reporting. Clients and employers highly value this skill because even minor mistakes can lead to significant financial losses or regulatory issues. A professional who consistently demonstrates meticulousness builds trust and credibility, ensuring that risk assessments are reliable and actionable. Cultivating attention to detail involves practicing careful review of work, seeking feedback, and developing habits such as double-checking calculations and validating data sources. Over time, these practices become second nature, enabling professionals to deliver consistently high-quality results and adapt to the evolving demands of the field. Imagine a Risk Analytics professional tasked with assessing the credit risk of a portfolio containing thousands of loans. While reviewing the data, they notice a subtle inconsistency in the way loan maturities are recorded. By investigating further, they uncover a data entry error that, if left uncorrected, would have significantly skewed the risk model’s predictions. Their attention to detail not only prevents a flawed analysis but also safeguards the organization from making poor lending decisions based on inaccurate information. This vigilance ensures that the final risk assessment is both accurate and trustworthy, demonstrating the critical role of attention to detail in achieving successful outcomes in Risk Analytics. Logical & Analytical Skills Logical and analytical skills refer to the ability to systematically break down complex problems, identify patterns, evaluate evidence, and draw sound conclusions based on data and reasoning. In risk analytics, these skills enable professionals to assess uncertainties, interpret data accurately, and make informed decisions that minimize potential losses and maximize opportunities. Logical and analytical skills are fundamental to excelling in risk analytics because they empower professionals to dissect intricate datasets, recognize emerging trends, and anticipate potential threats or opportunities. Clients and employers highly value these abilities, as they ensure that risk assessments are thorough, objective, and actionable. By applying logical reasoning, analysts can justify their recommendations and build trust with stakeholders. Cultivating these skills involves continuous practice in critical thinking, engaging with complex case studies, and seeking feedback on analytical approaches. Over time, exposure to diverse scenarios and a commitment to learning from both successes and failures help professionals refine their logical and analytical capabilities, making them indispensable assets in the risk analytics field. Imagine a risk analytics professional working for a financial institution who notices unusual fluctuations in transaction data. Using logical and analytical skills, they systematically investigate the anomalies, cross-referencing internal records with external market data. By identifying subtle correlations and ruling out false positives, the analyst uncovers a previously undetected pattern of fraudulent activity. Their ability to logically connect disparate data points and analytically assess the situation enables the institution to respond swiftly, preventing significant financial losses and strengthening internal controls. This scenario highlights how logical and analytical skills are not only crucial for problem-solving but also for safeguarding organizational interests and ensuring long-term success in risk analytics. Positives Moneatry Benefits Moneatry Benefits refer to the direct financial rewards and compensation packages that professionals receive for their expertise, skills, and contributions in their roles. This includes salary, bonuses, incentives, and other financial perks. In Risk Analytics, these benefits recognize the value and impact of managing uncertainty and safeguarding organizational assets. The promise of substantial moneatry benefits makes a career in Risk Analytics especially attractive. Competitive salaries and performance-based bonuses not only reflect the high demand for analytical talent but also serve as a powerful motivator for professionals to excel in their roles. These financial rewards contribute to greater job satisfaction, as individuals feel their specialized skills are truly valued. The assurance of strong compensation also encourages continuous learning and professional growth, as employees are motivated to stay ahead in a rapidly evolving field. Every day, risk analysts experience the tangible impact of their work through recognition and financial stability, which in turn fosters loyalty and long-term commitment to their organizations. Imagine a risk analyst working for a major financial institution who successfully identifies emerging threats and implements strategies that save the company millions of dollars. As a result, the analyst receives a significant year-end bonus and a salary increase, directly reflecting the value of their expertise. This financial recognition not only boosts their confidence but also provides a sense of accomplishment and security. The analyst is able to invest in personal goals, such as purchasing a home or furthering their education, all thanks to the moneatry benefits earned through their dedication and skill. This real-world scenario highlights how rewarding financial compensation can transform both professional and personal lives in the field of Risk Analytics. Job Security Job security is the assurance that an individual’s employment is stable, with minimal risk of sudden job loss or unemployment, often due to the ongoing demand for their skills and expertise. In risk analytics, job security provides professionals with confidence and peace of mind, allowing them to focus on delivering meaningful insights and solutions. This stability is rooted in the essential role risk analysts play in helping organizations navigate uncertainty, comply with regulations, and make informed decisions. As businesses increasingly rely on data-driven strategies to manage risks, the demand for skilled risk analysts continues to grow, making job security a defining and attractive feature of this career path. The strong job security found in risk analytics significantly enhances job satisfaction and professional growth. Knowing that their expertise is consistently valued and sought after, risk analysts can invest in long-term career development without the constant worry of job instability. This sense of stability fosters a positive work environment, where professionals are motivated to innovate and collaborate, knowing their contributions are crucial to the organization’s success. Daily, risk analysts experience the benefit of job security through ongoing projects, continuous learning opportunities, and the trust placed in them by leadership. This reliability not only encourages personal and professional growth but also allows individuals to plan for the future with confidence. Imagine a risk analyst working at a major financial institution during a period of economic uncertainty. While other departments face restructuring and layoffs, the risk analytics team remains essential, guiding the company through turbulent times with data-driven insights. The analyst feels secure in their role, knowing their expertise is indispensable for identifying potential threats and safeguarding the organization’s assets. This stability allows them to focus on developing innovative risk models and collaborating with colleagues, rather than worrying about job loss. The assurance of job security empowers the analyst to pursue advanced training and certifications, further enhancing their skills and career prospects, while contributing meaningfully to the company’s resilience and success. Work Life Balance Work Life Balance is the harmonious integration of professional responsibilities and personal pursuits, allowing individuals to meet career goals while nurturing their well-being, relationships, and interests outside of work. In risk analytics, this balance fosters sustained productivity, reduces burnout, and enhances creativity, making the profession both sustainable and deeply rewarding. The emphasis on work life balance in risk analytics is a significant advantage because it empowers professionals to excel in their roles without sacrificing personal fulfillment. Flexible work arrangements, clear project timelines, and a results-oriented culture enable analysts to manage their workload efficiently. This positive aspect leads to higher job satisfaction, as individuals feel valued and supported by their organizations. It also encourages continuous learning and professional growth, since a balanced lifestyle leaves room for skill development and innovation. On a daily basis, risk analytics professionals experience reduced stress, greater motivation, and the ability to bring their best selves to both work and life, creating a virtuous cycle of well-being and achievement. Imagine a risk analytics specialist working for a financial institution who is able to adjust their schedule to accommodate family commitments and personal interests. After completing a major project ahead of deadline, they take a mid-week afternoon off to attend their child’s school event, knowing their team supports flexible hours. Later, they return to work refreshed and energized, contributing new insights to a complex risk model. This ability to seamlessly transition between professional and personal spheres not only enhances their job satisfaction but also strengthens their commitment to the organization. The fulfillment they experience from maintaining this balance becomes a driving force behind their continued growth and success in the field. Challenges Different Time Zones In Risk Analytics, “Different Time Zones” refers to the challenge of collaborating with colleagues, clients, or stakeholders located in various parts of the world. This creates difficulties in scheduling meetings, aligning project timelines, and ensuring real-time communication, making it demanding to maintain seamless workflow and timely decision-making. Working across different time zones can disrupt daily routines, delay responses, and complicate project coordination. Professionals often face early morning or late-night meetings, which can lead to fatigue and reduced productivity. This challenge demands resilience, adaptability, and strong organizational skills. Successful risk analysts overcome these constraints by proactively planning their schedules, setting clear expectations with international teams, and leveraging asynchronous communication tools. They prioritize tasks based on urgency and availability, ensuring that critical decisions are not delayed. By fostering a culture of flexibility and mutual respect, they maintain effective collaboration despite the geographical and temporal gaps. Over time, these strategies help professionals build trust and maintain high performance, even when working with globally dispersed teams. Consider a risk analyst based in London who collaborates daily with colleagues in New York and Singapore. To manage the time zone differences, the analyst establishes a rotating meeting schedule, ensuring that no single team consistently bears the burden of inconvenient hours. They use shared digital platforms to document discussions and decisions, allowing team members in different regions to stay informed and contribute asynchronously. By setting clear deadlines and maintaining open lines of communication, the analyst ensures that risk assessments and reports are delivered on time, regardless of location. This approach not only minimizes delays but also fosters a sense of inclusion and teamwork, demonstrating how professionals in Risk Analytics can successfully navigate the complexities of working across multiple time zones. Continuous Research & Updation Continuous Research & Updation in Risk Analytics refers to the ongoing need for professionals to stay current with evolving regulations, emerging risks, new analytical techniques, and technological advancements. This constant learning is demanding because the risk landscape shifts rapidly, requiring practitioners to adapt their knowledge and methodologies to remain effective and compliant. The necessity for continuous research and updation significantly shapes the daily routines of risk analytics professionals. They must allocate time to monitor regulatory changes, study new risk models, and evaluate the impact of technological innovations, all while managing their core responsibilities. This ongoing pressure can lead to information overload and fatigue, making resilience an essential trait. Successful professionals address this challenge by cultivating a habit of structured learning, integrating research into their workflow, and leveraging professional networks for knowledge sharing. They prioritize critical updates, use reliable information sources, and remain adaptable, ensuring their skills and insights remain relevant in a dynamic environment. Consider a risk analyst working in the financial sector who faces frequent changes in anti-money laundering regulations and the introduction of advanced machine learning models. To manage this, the analyst dedicates a portion of each week to reviewing regulatory bulletins and attending webinars on new analytical tools. By actively participating in industry forums and collaborating with colleagues, the analyst quickly identifies which updates are most pertinent to their organization’s risk profile. This proactive approach allows the analyst to implement necessary changes efficiently, ensuring compliance and maintaining the effectiveness of risk assessment processes despite the constant influx of new information and requirements. No Margin for Error In Risk Analytics, "No Margin for Error" refers to the critical necessity for absolute precision in data analysis, modeling, and reporting, as even minor mistakes can lead to significant financial losses, regulatory penalties, or reputational harm. This demand for perfection makes the role exceptionally high-stakes and mentally taxing. The pressure of having no margin for error permeates every aspect of a risk analyst’s daily responsibilities. Each decision, calculation, and recommendation must be meticulously validated, as inaccuracies can have far-reaching consequences for the organization. This environment requires unwavering attention to detail, robust quality control processes, and a deep understanding of both technical and business contexts. The constant vigilance can be mentally exhausting, demanding resilience and adaptability from professionals. Successful risk analysts manage this constraint by fostering a culture of peer review, leveraging advanced validation tools, and maintaining open communication with stakeholders. They also prioritize continuous learning to stay ahead of emerging risks and regulatory changes, ensuring their analyses remain both accurate and relevant. Consider a risk analyst at a major financial institution tasked with assessing the credit risk of a large corporate client. The analyst knows that a single error in the risk model’s input data or assumptions could result in the bank extending too much credit, exposing it to potential multi-million-dollar losses. To manage this, the analyst rigorously cross-checks data sources, collaborates with colleagues for independent model validation, and documents every step for transparency. When a discrepancy is found during a peer review, the analyst quickly investigates and corrects the issue before the report is finalized. Through diligence, collaboration, and a commitment to accuracy, the analyst ensures the institution’s risk exposure remains within acceptable limits, exemplifying how to thrive despite having no margin for error. A Day Of Risk Analytics In the world of Risk Analytics, every day unfolds like a high-stakes puzzle, where the pieces are ever-shifting data streams, regulatory updates, and the unpredictable tides of global markets. The pace is brisk but thoughtful, driven by a constant need to anticipate threats and uncover hidden vulnerabilities before they become costly realities. The environment buzzes with a quiet intensity, blending the analytical rigor of data science with the strategic foresight of risk management. Here, professionals move seamlessly between deep dives into complex models and rapid-fire discussions with stakeholders, always balancing precision with agility. It’s a role where curiosity meets caution, and where each decision can ripple far beyond the confines of the desk. As the sun rises, a Risk Analytics professional begins the day by reviewing overnight market movements, scanning for anomalies or emerging trends that could impact the organization’s risk profile. This early hour is dedicated to digesting fresh data feeds, checking automated alerts, and revisiting dashboards to ensure all systems are functioning smoothly. With a cup of coffee in hand, the practitioner prioritizes tasks, flags urgent issues, and prepares a mental roadmap for the day ahead, setting the tone for focused, proactive analysis. By mid-morning, the real analytical work takes center stage. This is the most intellectually demanding part of the day, where the practitioner refines risk models, runs scenario analyses, and interprets complex datasets to identify potential exposures. The work often involves collaborating with data engineers to validate inputs, troubleshooting model discrepancies, and synthesizing findings into actionable insights. During this period, the professional may also prepare reports or visualizations for senior management, translating technical results into clear, strategic recommendations. The afternoon brings a shift toward teamwork and execution. Meetings with colleagues from compliance, finance, and business units fill the calendar, as the Risk Analytics professional presents findings, discusses mitigation strategies, and aligns on next steps. These sessions are dynamic, requiring both technical fluency and strong communication skills to bridge the gap between quantitative analysis and business decision-making. The practitioner may also respond to ad hoc requests, support ongoing audits, or participate in workshops aimed at enhancing the organization’s risk culture. As the day winds down, attention turns to consolidating the day’s work and preparing for tomorrow’s challenges. The practitioner reviews progress against key deliverables, documents insights, and updates risk registers or project trackers. This is also a time for professional development—catching up on industry news, exploring new analytical tools, or brainstorming improvements to existing processes. With a final check of emails and a glance at the next day’s agenda, the Risk Analytics professional ensures that no loose ends remain, closing out the day with a sense of accomplishment and readiness for whatever comes next.

Install the LifePage App to:

(for Free) Watch Assistant Manager Shobit Kumar Singhal’s full Risk Analytics Career Talk

₹ Do a Self Assessment on Risk Analytics to calculate your Dream Index, which is defined as:

According to Shobit Kumar Singhal your chances of success in Risk Analytics is __%

Access your personalized Dream Index Report which will have all your Dream Indices sorted in descending order.

How to get into

Risk Analytics?

If you are want to get into Risk Analytics, start by investing in a Career Plan.

The 14 hour process, guided by a LifePage Career Advisor, will help you introspect and check whether your interest in Risk Analytics is merely an infatuation or is it truly something you wish to do for the rest of your life.

Next, your Career Advisor will help you document how you can get into Risk Analytics, what education and skills you need to succeed in Risk Analytics, and what positives and challenges you will face in Risk Analytics.

Finally, you will get a Career Plan stating which Courses, Certifications, Trainings and other Items you need to do in the next 7 years to become world’s best in Risk Analytics.

LifePage Career Plan

14 hour personalized guidance program

Your LifePage Career Advisor facilitates your guided introspection so that you systematically explore various Career options to arrive at a well thought out Career choice.

Next: your Advisor helps you figure out how you will get into your chosen Career and how will you develop the skills needed for success in your Chosen Career.

LifePage Plan will not stop at saying "to become an Architect study Architecture". It will guide you on which Certifications, Trainings and Other items you need to do along with your Architecture education to become the world's best Architect.

Links for this Talk

Assistant Manager Shobit Kumar Singhal's LifePage:

[LifePage]
https://www.lifepage.in/page/shobitkumarsinghal

LifePage Career Talk on Risk Analytics

[Career]
https://www.lifepage.in/careers/risk-analytics-1

[Full Talk]
https://lifepage.app.link/20190812-0001

[Trailer]
https://www.youtube.com/watch?v=0gwuF8k_rVA

(Risk Analytics, Shobit Singhal, Barclays, Assistant Manager, Analysis, Risk Analysis, Banker, Analytics)

Similar Talks

Decision Management

Kapil Rawat
Business Analyst | G E Corp, Bangalore

[ 3 years & 2 months Experience ]

Use of computers allows organizations to collect enormous amount of data. Decision Management is tasked with analyzing this data to help take smarter business decisions. These decisions can comprise of anything and everything, like which advertisement to show to a particular user on Facebook or which credit card defaulters to call and when.

"After M A in Economics from JNU, I started my career as a Business Analyst with G E Corp in Bangalore. In my almost two years there I was responsible for making data based collections strategies for two large US retailers with several million defaulting buyers."

Actuarial Profession

Romik Rai
Risk Officer | Ageas SA/NV

[ 9 years Experience ]

An Actuary is a business professional who deals with the measurement and management of risk and uncertainty. These risks can affect both sides of the balance sheet, and require asset management, liability management, and valuation skills. Actuaries use mathematics, statistics, and financial theory to study uncertain future events, especially those of concern to insurance and pension programs.

"After completing my Masters in Actuarial Studies from University of New South Wales, Australia, I started working as a consultant with Watson Wyatt Worldwide. I have worked with over 20 financial institutions across Europe and Asia. Currently, I am the Founder and CEO of Greenassets.in which I started in 2015 in India. Greenassets.in is a startup where we promote investments which have a positive environmental and social impact."

Data Analysis

Sunaina Kuhn
Senior Associate | Evaldesign

[ 3 years & 4 months Experience ]

Data analysis, also known as analysis of data or data analytics, is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.

"After completing my Schooling from Woodstock, I did BA in Political Science from Purdue University. I taught Business English for a year in Budapest. After that I joined Teach for India. I also worked as a Research Associate in IIM, Ahmedabad. I have been working as a Senior Associate at Evaldesign since 2015."

Planning & Statistics

Dr Manoj Pant
Chief Coordination Officer | Department Of Planning

[ 25 years Experience ]

Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data. Statistics in indispensable into planning in the modern age which is termed as the age of planning. Almost all over the world the govt. are re-storing to planning for economic development.

"I completed my MSC in Statistics from Lucknow University. I did my PG Diploma in Computer Application. I joined Department of Planning as Chief Coordination Officer."

Data Science

Rajan Gupta
Analytics Consultant | Various Assignments

[ 7 years & 4 months Experience ]

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining.

"I am a Research & Data Analytics professional, learning new ways to deal with various business and research problems through technological and analytical tools. With the help of past experiences and academic exposure, following are the highlights of current capabilities. I have a substantial experience of working on research & analytics projects in the area of Information Systems, E-Governance and Public Schemes Assessment. I have working knowledge of application of various data science concepts through statistical techniques, operation research & optimization, data mining and machine learning across multiple industries (healthcare, retail, education, etc.) and domains. I have hands-on experience of using various analytical & development tools like SPSS, R, Tableau/MS Power BI and MATLAB and exposure of training and teaching in specialized areas of IT & Analytics. I am UGC NET-JRF Qualified and also possess management consulting certification from Government of India. I am one of the few Analytics professional in India to have CAP (INFORMS) and GStat (ASA) certification & accreditation, respectively and also serving as the Brand Ambassador of CAP in Asia Region for INFORMS. I am Efficient in Report preparation and Article writing. I can prepare Research proposals, Research Frameworks, Data Source identification, Data Collection Framework and Data Preparations. I have experience of handling teams up to 50 people for project execution."

Risk Analytics

Malika Davar
Senior Consultant | BFSI Analytics

[ 5 years & 10 months Experience ]

Risk analytics (or risk analysis) is the study of the underlying uncertainty of a given course of action. It often works in tandem with forecasting professionals to minimize future negative unforseen effects.

"I pursued a Bachelors degree in Economics from St Stephen's College and a Masters degree in Economics from Delhi School of Economics. Soon after, I joined BFSI Risk Analytics where I have been working for more than 4 years. Currently, I am working there as a Senior Consultant."

Data Analytics

Pratap Shankar Gharge
Executive President & CIO | Bajaj Electricals

[ 34 years & 2 months Experience ]

Data analytics or analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making

"After completing my graduation from Shivaji University, Diploma in Computer Management from Mumbai University and an MBA (Operations Research) from IGNOU, I started my career with Simplex Textile Mills as a Programmer (1984-85) and post that I was associated with Bajaj Electricals for 33 Years and retired as an Executive President & Chief Information Officer."

Data Sciences

Dr T P Singh
Professor | UPES

[ 22 years & 4 months Experience ]

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining.

"After completing my education, I started my career with TCS as a DBA. After that, I joined Sharda University as an Associate Professor and worked there for almost 17 years. I am a Professor at UPES since 2017."

Data Science & Statistics

Raman Nautiyal
Scientist E | Indian Council of Forestry Research & Education (ICFRE)

[ 20 years & 10 months Experience ]

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining. Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.

"I did Bachelors in Statistics, Maths & Economics from DAV College, Dehradun. I then did Masters in Statistics from the same college. I am pursuing my Ph D in Statistics from Kumaon University. I am a Scientist E at Indian Council of Forestry Research & Education (ICFRE)."

Data Science

Aayushi Verma
Data Scientist | EdGE Networks Pvt Ltd

[ 5 years Experience ]

Data science is a multidisciplinary blend of data inference, algorithmm development, and technology in order to solve analytically complex problems. At the core is data. Troves of raw information keep streaming in and stored in enterprise data warehouses as there is much to learn by mining it.

"After completing my M Tech in Data Analytics, I joined a start-up in Delhi as a Data Scientist. After that I have worked for few companies as a Data Scientist, in 2018, I joined EdGE Networks Pvt Ltd as Data Scientist. I have also published few Research Papers in Journals like IEEE & Springer."

Economics & Finance Consulting

Manmeet
Consultant | Planning Commission of India

[ 7 years Experience ]

Economic consulting is the practice of providing organizations in the public and private sector with information to improve their performance and policies, primarily through the use of applied economics, mathematical economics, economic impact analysis, and forecasting across a broad spectrum of issues.

"After graduating in commerce, I went on to do masters in Economics. I also attended winter school in Delhi School of Economics. I have done a course in management from London School of Economics. I did my internship at Planning Commission of India. I have worked at RMS as Business Risk Analyst and as Risk Management Consultant at Inductis. I am Strategy & Operations Head at Nuts for Cuts."

Research in Data Science

Aayushi Verma
Data Scientist | EdGE Networks Pvt Ltd

[ 5 years Experience ]

Research in Data Science, which is a profession, the goal of Data Science research is to build systems and algorithms to extract knowledge, find patterns, generate insights and predictions from diverse data for various applications and visualization.

"After completing my M Tech in Data Analytics, I joined a start-up in Delhi as a Data Scientist. After that I have worked for few companies as a Data Scientist, in 2018, I joined EdGE Networks Pvt Ltd as Data Scientist. I have also published few Research Papers in Journals like IEEE & Springer."