Mind over matter Do you often get angry about small things? Feel depressed or start crying without really any big reasons? I often found myself stuck in past moments, but I turned it around. When I started to write this article, I wasn’t sure what to share but thought it best to start with my own experience. Most of us often suffer from trauma, depression, anxiety, low self-esteem, poor concentration, etc. We are always busy thinking about the past and the future but forget to think of our present. To cope with this, I decided to practice meditation and recently completed a 10-day meditation camp. Now after reading this, I’m sure a lot of you will have questions so here are some of the important details about meditation. How to practice meditation? It’s quite simple. All you have to do is sit still in a place of your comfort; keep your back and neck straight, close your eyes, and start observing your breath and the sensations around your upper lip. Why should you observe your breath and sensations? How does it help to be in the present? Breath and sensations are the two things that we can observe only in the present. We can’t observe breath and sensations of the past or future, and this helps us to be in the present. However, when we observe our breath, it helps us improve our past and future because activities we do in our past are the things we are currently doing (the present), and what we are doing now will be the future. We all know that our minds wander every now and then. But if you can control your mind, then you can win over the whole world. Simply changing your body will not make a difference, but consciously observing the changes brought about by the physical adjustments will change all things. Why is it important to meditate? We all have inner and outer worlds, but we usually only think about the outer world. We focus on external happiness and depend only on external things to make us happy. When we lose this thing, we get sad and often depressed. Meditation helps us to be happy in our inner world. If we are happy from the inside, we will be happy externally, and we will not depend on external things for satisfaction. It helps us to balance our life. It explains to us that we should not be over-excited in good times, and we should not get depressed at our bad times. What difference did it make for me? After practicing meditation, I got mental peace, was relaxed, and it made me calmer. I can control my anger, keep depression at bay, and be happier than I ever was. What are the perks of meditating? It helps us to be present, control our anger, increase concentration, improve self-esteem, and maintain mental peace.
Ways to optimize customer experience in retail industry What is customer experience? Customer experience, commonly known as CX, refers to all interactions a customer has with a brand or retailer. This includes various activities like searching products online, in-store shopping, contacting customer service, or getting products serviced. CX applies to both in-store and online interactions. Therefore, every single consumer touchpoint is a part of customer experience. Customer experience means “the internal and subjective response that customers have to any direct or indirect contact with a company.” Thus, it is evident customer experience is a psychological construct which is comprehensive, subjective reaction to customer’s interaction with any retailer and may involve varying degrees of customer involvement. Sales, e-commerce, and omnichannel are a small part of an experience-led consumer journey. Why should businesses improve their customer experience? Customer experience is undergoing continuous transformation from transactional process solely focused on shopping and purchasing to a model built on deep, enriching relationships at every step of the customer journey. Retailers and brands are integrating seamlessly into consumers’ lives. They must develop an understanding of the way the consumers live, eat, shop, work, and play and use this knowledge to deliver value at the right placeat the right time. An experience-led consumer journey is not simple task. It requires a digital ecosystem fuelled by real-time consumer data and a consumer-centred view of the entire organisation, from the operating model and supply chain to content and marketing. Today, consumers are surrounded by numerous options across many channels. Brands and retailers work to build connections between data, process, technology, and human interaction to uncover insights which create seamless experiences to boost conversion and foster loyalty. Such an ecosystem aids in harmonizing experiential marketing, agile supply chains, and personalized interactions, making it easier to turn touch points into trust points and create value which endures. As the retail industry is advancing into omnichannel solutions, there are proven strategies which need little tweaking to enrich customer-retail experience. Also read: What are the 7P’s of marketing Strategies that help in enhancing customer experience How do retail brands ensure that their customers must experience best shopping environment? Here are few tips: Offer customers what they want and need: Thorough research and sales data analysis help to decide which products are best to keep in stock. Companies can use point-of-sale system to send inventory notifications when items run low on stock. While doing research, ensure to identify trends early. For instance, when launching an e-commerce site, it’s important to stay up-to-date and ahead of trends to market them before they reach peak consumer popularity. By doing this, retail businesses can significantly outperform their online and offline competitors. To stimulate buyer interest and motivate them to purchase more, retailers can arrange store shelves with popular items and place it close to related categories. A seasonal planogram is often created by store owners to increase sales during certain holidays. Buyer choices may be influenced by product placement and space management. A planogram is useful for organizing products keeping the consumer psychology in consideration. A well-organized store will encourage customers to shop comfortably, spend long hours, and return visits. To give a wow factor, retailers can plan eye-catching displays for products. Personalize customer experience: Personalize customers’ shopping experiences by creating such unique service that allows them to shop on their own time and terms. It is crucial that each customer feels valued. Offering the individualized service is a key component of developing retail business with customer-centric approach. Staff must be trained and skilled to facilitate each customer by full attention. Thus, personalized tactic adds an edge to customer experience as interaction with sales associates and tangibility attached to brick-and-mortar stores yields retail success. Build and sustain customer loyalty: Making shopping convenient for customers contributes to building customer loyalty, as repeat customers are often repeat purchasers. Discover more about target customers. send them mails about new merchandise, coupons, promotions, and personalized birthday email with a voucher often works. Additionally, retailers can engage their customers on social media by proliferating about new deals and freebies. If a customer comments on posts or story, promptly reply, and thank them. Customers who feel appreciated for shopping at store are more likely to return. Facilitate customers an efficient checkout experience: Retailers can provide customers with fast and efficient checkout experience by accepting multiple payment methods, including all major credit and debit cards and mobile payments, whereby customers can pay via store terminal, mobile device, or online. Start a cash discount program to entice customers who prefer to pay with cash. Customers will spend more time if it is easier for them to buy in store. Prioritize customer’s comfort above all: Customers often don’t remember every detail of their visits, but they always remember how being in store made them feel. Creating an excellent customer experience is simple to attain. Paying attention to and prioritizing consumers will go a long way toward customer retention, positive word of mouth, business growth, and long-term success. Excellent customer service: Providing best customer service helps in retaining the existing customers and bringing in more new customers. To provide customers with seamless shopping experience, businesses need such workforce who can assist them with any issues. So, what retailers can do to provide customers with the finest possible experience? Providing personalized shopping experience, making consumers feel like a priority and showing appreciation for loyal customers are few tricks which business can practice enriching customer experience. Check out: Why marketing could be your dream career How does an MBA in marketing help in understanding and improving customer experience? An MBA in marketing course helps in understanding consumer behaviour and develop strategies for improving their experience. It helps marketers gain insights into the factors that influence purchasing decisions. Through comprehensive courses and case studies, MBA students learn about psychological, sociological, and economic aspects that shape consumer choices. This knowledge equips marketers with a deeper understanding of customer needs, motivations, and preferences. Armed with this understanding, marketing professionals can develop effective strategies, tailor messages, and create compelling brand experiences that resonate with their target audience. Manipal University Jaipur offers an UGC-entitled online MBA degree with 13 popular and new-age electives including marketing. The online MBA allows students as well as working professionals to learn at their own pace and schedule. MUJ’s online MBA is treated equal to on-campus MBA and is a great way to upskill oneself. Whether you’re looking to get a PG degree in management to elevate your career prospects or want to switch to a different domain, you can do so by choosing the right MBA elective. Check out: MBA marketing course guide Conclusion The number of retail options for customers is increasing continuously. The businesses must find their own ways to prove why customers should choose their company and brand. Retailers must be proactive in listening and responding to customers’ feedback. They shouldn’t be afraid to try and test different strategies and find what works best for business.
Why BFSI professionals must possess analytics skills Over the past decade, data analytics has emerged as a major buzzword. The BFSI industry is experiencing a spike in data generation in today’s unpredictable business landscape. Thus, making it necessary for individuals in this sector to be adept at strong analytical skills. This sector has witnessed an upsurge in the adoption of analytics, which can be attributed to assisting businesses in deriving insightful conclusions from enormous quantities of data. Professionals can analyze client behavior patterns, evaluate risks, spot market trends, and optimize corporate processes thanks to analytics. Personnel in the BFSI sector who hold expertise in analytics can efficiently evaluate large data sets, implement data-driven initiatives, improve consumer experiences, mitigate risks, and grab novel opportunities. Read more: Decoding the impact of big data analytics in the banking sector Advantages of possessing analytics skills for BFSI professionals Professionals in the BFSI sector can benefit from having analytics skills in several ways. A few of the advantages of possessing analytics skills for BFSI professionals are explained below. Analyzing large volumes of data: BFSI personnel with analytics skills can quickly analyze and decipher massive amounts of data. Professionals can learn significant details regarding risk profiles, market dynamics, and client behavior by skillfully analyzing this data. This analysis aids in pinpointing trends, patterns, and oddities that can impact business strategy and decision-making. Data-driven decisions: Professionals in the BFSI sector can leverage data analytics tools to guide their decision-making processes. Experts can identify potential threats, streamline operational processes, and create effective strategies by using statistical frameworks, predictive analysis, and machine learning techniques. This data-driven methodology improves decision accuracy and lowers the probability of making expensive mistakes. Product development: Professionals can pinpoint unmet needs, preferred options, and new business prospects by analyzing consumer data and industry trends. They can then employ these insights to generate fresh offerings that are tailored to specific customer categories. Additionally, analytics aids in the optimization of product attributes, pricing, and distribution plans based on data-driven conclusions. It can lead to improved client satisfaction and business expansion. Staying competitive in the industry: Organizations in the BFSI sector that successfully apply analytics to derive valuable insights from data acquire a competitive advantage. Professionals are better able to provide personalized services, improve client experiences, and proactively handle risks if they have a better understanding of customer behavior, market conditions, and risk profiles than their opponents. This exalts the organization to the forefront of its domain and enhances its potential to adapt to shifting market dynamics. Read more: Thriving in the BFSI Industry: Essential skills for today’s professionals Application of analytics in banking and finance The use of analytics in banking and finance has risen. From detecting fraudulent activities, risk management, business optimization to credit risk analysis, analytics is used in the BFSI industry for multiple reasons. Fraud detection and risk management: Analytics assists financial institutions in spotting and intervening in fraudulent actions by analyzing massive volumes of data and identifying trends or discrepancies. Machine learning algorithms can continuously monitor transactions, detect suspect patterns, and generate alerts for further inquiry. Analytics can help banks proactively manage risks, safeguard client funds, and uphold the reliability of financial systems. Credit risk analysis: Analytics assist banks and lenders in managing credit risk by evaluating creditworthiness. Banks can assess the risk of default and establish reasonable loan limits by examining historical data, financial documents, credit scores, along with other pertinent indicators. Advanced analytics models can additionally incorporate other data sources, like macroeconomic indicators or market trends, to raise the precision of credit risk assessments. This allows banks to manage an intact loan portfolio while making wise lending choices. Customer insights and personalized services: Banks can uncover valuable insights about the behavior, preferences, and demands of their customers thanks to analytics. Banks can segment their clientele to develop individualized services by analyzing transaction data, demographic data, and client interactions. Cross-selling opportunities, custom product or service recommendations, and personalized marketing campaigns can all be accomplished with analytics. AI-powered virtual assistants: AI and analytics collaborate to facilitate the development of chatbots or virtual assistants that can assist consumers with their banking inquiries and activities. These AI-powered advisors leverage ML algorithms and NLP (Natural language processing) to comprehend consumer requests, respond precisely, and carry out tasks. Virtual assistants can keep learning from client conversations, increase their accuracy, and offer more tailored and effective services via analytics. Business performance optimization: Banks can pinpoint inefficient regions, restructure procedures, and cut expenses by analyzing internal data, market dynamics, and industry standards. The efficacy of risk management, channel success, product profitability, and client acquisition and retention can all be gleaned from analytics. Banks can improve resource allocation, increase operational effectiveness, and provide better financial results by using this data-driven decision-making strategy. Read more: How will digital transformation reshape the future of banking in India? Top analytics job roles in banking and finance Discussed below are some of the top analytics job roles available in banking and finance, along with their highest estimated salaries:: Credit risk analyst The assessment and management of credit risks related to lending and investing activities are under the purview of a credit risk analyst. They examine financial information, assess creditworthiness, and offer suggestions to lessen prospective losses. They also create risk models and keep track of portfolio performance. The highest estimated salary of a credit risk analyst is ₹ 20.0 Lakhs. Compliance manager A compliance manager makes certain that a financial institution abides by all applicable laws, rules, and internal procedures. They create compliance programs, carry out audits, and offer direction on compliance-related issues. They also keep a gaze on modifications to regulatory standards while making the necessary adjustments. The highest estimated salary of a compliance manager is ₹ 25.0 Lakhs. Big data analyst Big data analysts leverage data analytics approaches to extract information from huge databases. They gather, filter, and analyze financial data to uncover patterns, indications, and correlations. Additionally, they create predictive analytics models, design data models, and offer data-driven suggestions to enhance company decision-making. The highest estimated salary of a big data analyst is ₹ 17.0 Lakhs . Fraud prevention analyst Fraud prevention analyst focuses on recognizing and terminating fraudulent activity within a financial organization. They perform an analysis of transactional data, seek out patterns and abnormalities, and put fraud control mechanisms in place. In addition, they investigate shady operations in conjunction with police enforcement. The highest estimated salary of a fraud prevention analyst is ₹ 8.0 Lakhs. Pursue an online MBA in BKFS from TAPMI Professionals have the opportunity to keep up with the rapidly evolving developments in the BFSI industry with the MBA in Banking and Financial Services (BKFS) program offered by T.A. Pai Management Institute through Online Manipal. Analytics for Banking and Finance is a noteworthy elective in this program that imparts participants with the expertise and skills needed to make data-driven conclusions. The most recent pedagogy used by TAPMI emphasizes combining theoretical understanding with real-world applications to create a well-rounded educational experience. Read more: How analytics in banking and finance opens doors to lucrative job roles in banks Professionals obtain an in-depth knowledge of analytics techniques and their relevance in the banking and finance business via immersive online sessions, case studies, and industry collaborations. This program ensures that learners become well-equipped to deal with the BFSI industry’s complexity while utilizing the latest analytical resources and techniques.
How much you can earn across roles in new-age banking and finance The business landscape in India fosters all the positives for the expansion of the BFSI sector at a commendable pace. The BFSI sector has witnessed substantial growth lately owing to a multitude of interlinked factors. Modern banking practices have been revolutionized by technological breakthroughs, which have additionally introduced forth innovative solutions. With the rise of mobile banking, e-payments, and automated financial guidance services, consumers now have more accessibility and convenience. The proliferation of fintech companies, which leverage technology like blockchain and artificial intelligence to provide individualized, secure, and effective financial services, has also been spurred by shifting customer needs. This rising phenomenon in financial services and banking within the BFSI sector heralds a disruptive era driven by new prospects, better operational effectiveness, and a customer-centric mindset. Pursuing a master’s degree like an MBA in banking and finance will help you explore lucrative career opportunities in the BFSI sector. Top jobs in banking and finance In the BFSI industry, job postings soared by about 53% between 2022 and 2023, as per a survey by Indeed. Investment banking, risk management, and portfolio management positions earned the most in the BFSI industry. The positions of financial manager, wealth manager, and credit manager were next. Here is a brief description of roles and responsibilities along with the earning potential of different roles in the banking and finance sector. Chief financial officer (CFO) A CFO manages all financial operations and is essential in the development and execution of financial strategies, financial risk administration, and the maintenance of the organization’s overall financial stability. Budgeting, dealing with investors, treasury management, financial evaluation and strategy, financial reporting, and shareholder interactions typically fall under the CFO’s purview. The highest estimated salary of a chief financial officer can go up to ₹ 101 Lakhs. Key skills required: Financial management Strategic planning Leadership Risk management Compliance officer The compliance officer is in authority to ensure that the bank or other financial institution abides by all relevant laws, rules, and internal procedures. They establish and enforce compliance initiatives, carry out routine audits, and keep an eye on internal procedures to reduce legal and regulatory risks. They collaborate closely with regulatory organizations and external auditors to ensure compliance and address any prospective compliance concerns. The highest estimated salary of a compliance officer can go up to ₹ 15 Lakhs. Key skills required: Knowledge of regulatory frameworks Risk assessment Attention to detail Strong ethics Financial advisor These professionals offer specialized financial counsel to clients, who can be individuals, firms, or institutional investors. They evaluate their clients’ risk tolerance and monetary objectives before creating extensive financial strategies to assist them in achieving their goals. Financial advisors offer advice on wealth administration, retirement strategy, tax reduction, and investment approaches. The highest estimated salary of a financial advisor can go up to ₹ 8 Lakhs. Key skills required: Financial planning Investment knowledge Client relationship management Investment banker An investment banker is a major player in facilitating diverse financial transactions and serves in the investment banking section of a financial institution. They provide their clients with capital raising via IPOs (Initial public offerings), equity or debt issuances, and acquisitions and mergers. Financial analysis, assessments, and due diligence are performed by investment bankers to gauge investment prospects and offer customers strategic counsel. The highest estimated salary of an investment banker can go up to ₹ 40 Lakhs. Key skills required: Strong analytical skills Financial modeling, Negotiation Market knowledge Chief risk officer (CRO) The CRO is accountable for identifying, evaluating, and mitigating the risks confronted by banks or other financial organizations. They develop and place into practice risk management frameworks and strategies to ensure that the firm proceeds within acceptable risk constraints. The CRO is in charge of managing several risk-related tasks, including credit risk, market risk, operations risk, and liquidity risk. They collaborate closely with top management to determine risk tolerance, track risk exposures, along with implementing risk-reduction strategies in place. The highest estimated salary of a chief risk officer can go up to ₹ 101 Lakhs. Key skills required: Risk management Financial analysis Regulatory compliance Strategic thinking Credit analyst A credit analyst assesses an individual, enterprise, or institution’s credibility to figure out whether they are financially able to pay back loans or other financial obligations. They examine financial records, credit scores, and other pertinent data to assess the risk involved with disbursing funds or granting credit. Credit analysts also consider market conditions, industry trends, and collateral to make wise credit choices. The highest estimated salary of a credit analyst can go up to ₹ 15 Lakhs. Key skills required: Credit analysis Financial statement analysis Risk assessment Attention to detail Fund manager A fund manager is in the role of regulating and tracking the performance of investment funds including hedge funds or mutual funds. They conduct the necessary investigations, analysis, and research to figure out potential investment opportunities and develop investment strategies compatible with the fund’s targets. These experts are liable for making buy/sell decisions, evaluating portfolio performance, and adhering to regulations. They also oversee the fund’s assets to generate favorable returns, interact with clients, and deliver regular updates. The highest estimated salary of a fund manager can go up to ₹ 93 Lakhs. Key skills required: Investment management Portfolio analysis Market research Decision-making Portfolio manager A portfolio manager is obligated for managing all kinds of assets, such as bonds, equities, or additional financial instruments, on behalf of individuals or institutional customers. Investment strategies that are tailored to the client’s goals, degree of risk aversion and period are devised and executed into action by these professionals. Portfolio managers perform research, keep watch on market trends, and arrive at investment choices to maximize portfolio performance. The highest estimated salary of a portfolio manager can go up to ₹ 30.5 Lakhs. Key skills required: Portfolio management Asset allocation Risk assessment Financial forecasting Factors influencing salaries in banking and finance roles Multiple factors affect compensation in the financial services industry for various roles. These aspects influence the salary packages offered to practitioners in this industry. Here are the key factors influencing salaries in new-age banking and finance. Relevant master’s degree/Certificate course The salary range in new-age banking and finance can be substantially raised by pursuing a pertinent master’s degree or earning a professional certificate program. For instance, a Master’s in Finance, MBA with a finance focus, or the Certified Financial Analyst (CFA) accreditation can improve your credentials and demonstrate to prospective employers your level of expertise. Industry-specific knowledge Professionals aiming to boost their earning potential must have extensive knowledge of the banking and financial sector. This entails comprehending intricate financial tools, guidelines, risk-management strategies, and market dynamics. You can earn better compensation by staying current with market trends, modifications in financial laws, and advances in technology via ongoing learning and professional credentials. New-age skills Professionals with new-age skills are highly desirable as the banking and financial sector continues to evolve. Skills in data analysis, FinTech (Financial technology), AI, ML, blockchain, and digital advertising can have a significant impact on earnings. With the use of these capabilities, professionals can leverage technology to spur innovation, promote operational effectiveness, and arrive at data-driven choices. Professional connections Establishing links with influential practitioners, industry experts, and mentors can lead to valuable counsel, job prospects, and access to better-paying choices. A strong network could assist you in gaining access to insider details regarding job openings, raise your profile among employers, and possibly even influence salary negotiations in your favor. While these elements are crucial, it’s also vital to take into account other elements that can have an impact on income levels, such as prior experience, work performance, the company’s financial situation, and geographic variations in pay. Also read: How TAPMI online MBA-BKFS electives help professionals tailor their career paths Emerging technologies in banking and finance The banking and financial industry has seen a tremendous transformation recently, driven by novel technologies. These developments have transformed how financial institutions function, engage with clients, and oversee their procedures. The following are some of the acknowledged emerging technologies currently reinventing the banking and financial sector: Artificial intelligence (AI) and machine learning (ML): AI and ML are redefining banking and finance by automating procedures, optimizing fraud detection, enhancing the client experience, and offering tailored financial proposals. They analyze massive quantities of data to uncover patterns, forecast market developments, and deliver customized fixes. Blockchain: Decentralized, open, and reliable transactions are made feasible by blockchain technology. It promotes data security, facilitates effective cross-border payments, and slashes transaction expenses. The blockchain’s smart contracts eliminate the need for middlemen by streamlining processes like loan approvals. Robotic process automation (RPA): RPA raises operational efficiency and lowers error rates by automating repetitive operations like data entry and report production. Banks and financial organizations can streamline their operations since it opens up staff members for more demanding and value-added services. Internet of things (IoT): Real-time data gathering from multiple sources, including wearables and connected gadgets, is made possible by IoT devices. Banks and financial institutions can use this data to deliver customized services, risk analysis, and insurance underwriting. IoT also facilitates seamless transactions and improves fraud detection. Biometrics: Customer identification employing biometric technologies, such as voice authentication, facial recognition, and fingerprint scanning, is reliable and practical. These innovations improve the safety of financial transactions, prevent fraud, and optimize authentication procedures. Cloud computing: Banks and other financial institutions can store and manage massive amounts of data safely, thanks to cloud computing. It improves cost effectiveness, scalability, and flexibility. A faster decision-making process and enhanced customer service are made feasible by cloud-based solutions that provide real-time collaboration, remote management, and data analytics. Open banking: Open Banking leverages Application APIs (Application Programming Interfaces) to promote safe financial data exchange between different organizations. It fosters innovation by enabling third-party developers to come up with novel financial apps and services, boosting competition while improving the user experience. Big data analytics: Data proliferation in banking and finance necessitates advanced analytics skills. Large datasets can be analyzed using big data analytics to gain insightful data that assists with handling risks, identifying fraud, segmenting consumers, and customized marketing. It aids financial firms in making data-driven decisions while improving overall performance. Read more: Top emerging technologies in financial services and how to upskill in them Become job-ready with tapmi’s online MBA BKFS The online MBA in BKFS (Banking and Financial Services) offered by TAPMI will help you gain the knowledge and skills you need to succeed in the financial industry. This extensive program is meticulously developed to prepare you for the job market with the acumen and expertise demanded by the sector. You will be involved in an interactive and dynamic learning experience via cutting-edge virtual platforms under the tutelage of renowned educators and industry experts. An online MBA in banking and finance will help you master the nuances of investment banking, risk management, economic analysis, and more while refining your management and decision-making skills. You will graduate from TAPMI’s online MBA in BKFS as a honed finance expert equipped for a successful career in the corporate world. Read more: MBA in finance vs MBA in banking and finance
Data scientist job role and description Who is a data scientist? A data scientist is a professional who analyzes and interprets complex data sets to uncover insights, patterns, and trends that can inform business decisions and strategies. They use a combination of statistical analysis, machine learning techniques, and programming skills to extract meaningful information from large and diverse data sets. Data scientists’ role is also to help companies make decisions based on the analysis of data. Data scientist roles and responsibilities The roles and responsibilities of a data scientist can vary depending on the organization and specific job requirements. However, here are some of the common responsibilities that data scientists are in charge of. Data analysis Data scientists are responsible for collecting, cleaning, and organizing data from various sources. They perform exploratory data analysis to understand the data, identify patterns, and determine the appropriate analytical approaches. Data scientists perform Exploratory Data Analysis to gain a deep understanding of the data. They use descriptive statistics, visualizations, and data profiling techniques to identify patterns, trends, and relationships within the data. EDA helps them uncover insights and formulate hypotheses for further analysis. Machine learning model development Data scientists apply various machine learning algorithms and techniques to develop predictive or descriptive models. They select appropriate algorithms based on the problem type (classification, regression, clustering, etc.) and the available data. They train the models using historical data, optimize the model parameters, and evaluate their performance using suitable metrics. Using statistical methods Statistical analysis techniques play a crucial role in data science work, enabling data scientists to examine datasets, uncover hidden patterns, and gain insights. These techniques are an integral part of the data scientist’s toolkit, facilitating exploration and interpretation of data to identify trends and patterns. Data storytelling Employers often require data scientists to possess excellent communication skills and the ability to convey data insights to business executives, managers, and employees using data storytelling techniques. In addition, data scientists are expected to demonstrate leadership skills and business acumen to effectively guide decision-making processes that rely on data analysis. Key skills required for data scientists A data scientist is a professional who leverages their knowledge of various fields, including computer science, mathematics, and business, to interpret complex data and drive valuable insights. Here are some of the key skills a data scientist should possess Programming Skills Data scientists need to be proficient in at least one programming language, typically Python or R, which are widely used for data analysis. Possessing programming skills in a data science job allows them to manipulate data, conduct analysis, and implement machine learning algorithms. Machine Learning Knowledge of machine learning is vital for many data science roles. This includes understanding different types of learning (supervised, unsupervised, reinforcement, etc.), the theory behind various algorithms (linear regression, decision trees, neural networks, etc.), and how to use these tools to solve real-world problems. Data Wrangling This involves cleaning and transforming raw data into a more suitable form for analysis. Data often comes from various sources in different formats, and it’s the data scientist’s job to ensure this data is cleaned, validated, and correctly formatted. Data Visualization The ability to present complex results in a visually intuitive form is crucial. Tools like Matplotlib, Seaborn, ggplot, or Tableau are often used for this purpose. Good data visualization helps to communicate findings effectively to both technical and non-technical audiences. Big Data Platforms Familiarity with big data platforms like Hadoop, Spark, or Hive is beneficial, as data scientists often work with large datasets that cannot be processed using conventional methods. Read more: Tools covered in MSc Data Science Top companies hiring data scientists Here is a list of some of the top companies hiring data scientists in India Fractal Analytics Deloitte Tiger Analytics Accenture Analytics IBM MuSigma LinkedIn Wipro Splunk Numerator How to start a data science career You need the right knowledge and skillset to start a career in data science. Here’s how you too can become a data scientist. Earn a relevant degree or certification To become a successful data scientist, you require analytical and mathematical skills to work with complex data sets. Additionally, you should have programming knowledge. For all this, you will ideally need a data science degree or a certification course. Nowadays, there are plenty of online courses available on data science, which you can pursue from the comfort of your homes. If you want to gain in-depth technical knowledge, then an online MSc in data science can be the perfect pick for you. This program will help you master in-demand tools like Hadoop, TensorFlow, Python, R, etc, and help you gain in-demand skills by learning subjects like linear regression models, deep learning & text mining, Bayesian statistical modeling, programming with R & Python, and stochastic processes. If you want to get a blend of data science and business knowledge, then pursuing an online MBA in data science can be the right choice. This program will help you acquire the latest skills and find lucrative jobs in top organizations. You can also choose to pursue an online professional certification in data science, if you are looking to upskill in the domain and explore better career opportunities. Gain key skills Apart from mastering various programming languages, it’s essential for a Data Scientist to be proficient in several tools used for data visualization, machine learning, and big data. Knowing how to manage, cleanse, arrange, and interpret sizable datasets is a vital skill when dealing with substantial amounts of data. Internships Internships are a great way to kickstart your career in data science. If you are just entering the domain, then internships can give you the right push to explore the right career opportunities. As an intern, you can work on various roles that will help you understand your strengths and weaknesses. Get an entry-level job You can kickstart your career with entry-level roles like data scientists, data engineer, or data analyst to gain the necessary skills and knowledge required to explore better roles through your career path. Frequently asked questions about data science jobs Can anyone do a data science course? Data science is an emerging domain in today’s digital world, and with the help of a degree or certification, anybody can do a data science course. The eligibility for a master’s degree in data science is 10 + 2 + 3-year bachelor’s degree from a recognized university/institution. However, some universities may require students with a minimum of two years of learning Mathematics or Statistics. Does data science require coding? Coding is very necessary for a data science job. Coding is essential to data science as it possesses a learning bend. Coding skills allow data scientists to manipulate and clean data, create models, and automate processes, all of which are critical to the data science process. Is it good to pursue a 2-year data science program? Pursuing a 2-year program like an MSc in data science allows you to gain in-depth knowledge about data science concepts and tools, which will help you gain key skills. What are the key concepts taught in a data science program? You will learn how to work effectively in groups, generate strategic and tactical recommendations, and use a perfect blend of machine learning, big data analytics, and statistics. You will learn key data science concepts like linear regression models, deep learning & text mining, Bayesian statistical modeling, programming with R & Python, and stochastic processes, and tools like Hadoop, TensorFlow, Python, R, SPSS, SAS, Matplotlib, NumPy, OpenCV, Pandas, Apache Spark, Apache Hive, SQL, Google Colab, KNIME, and WEKA. What are the programming languages a data scientist should know? Data scientists must have knowledge in programming languages like Python, R, SQL, C++, MATLAB, Scala, Go, SAS, and Java. What are the jobs you get after MBA in data science? Pursuing an MBA in data science helps you explore high paying job roles like data science managers, product analysts, data architects, market research analysts and more. What are the jobs you get after MSc in data science? After pursuing an MSc in data science, you can explore job roles like data scientist, machine learning engineer, data analyst, statistical analyst, research scientist and more.
Know the difference between B.Com and B.Com Honors Choosing the right academic path can be an exhilarating yet perplexing decision, especially when it comes to higher education. For those aspiring to embark on a journey in the realm of commerce and business, the Bachelor of Commerce (B.Com) and Bachelor of Commerce (Honors) degrees emerge as two prominent options. While both programs offer a solid foundation in business and finance, there are subtle yet significant differences that set them apart. In this blog, we will dive deep into the realm of B.Com and B.Com (Honors), shedding light on their respective characteristics, curriculum, career prospects, and other vital aspects. Whether you’re a prospective student eager to make an informed choice or someone seeking to enhance their understanding of these programs, this comprehensive exploration will help you navigate the nuances and make an informed decision. What is B.Com? Bachelor of Commerce is an undergraduate degree in commerce and other related subjects. A B.Com degree provides students with a wide range of managerial skills and understanding in streams like finance, accounting, taxation, and management. While undergoing this course, students also get to learn about the economic aspect of the business world, trading aspects, functions and policies of commerce, etc. Read more: Benefits of pursuing an online B.Com degree What is B.Com Honors? B.Com honors is a more specialized version of the BCom degree. Typically a year longer than the general BCom program, it allows students to specialize more deeply in a particular area of interest within commerce, like finance, accounting, marketing, etc. In this course, students generally study more advanced topics in greater detail. The curriculum is usually research-oriented and project-based, enabling students to gain in-depth knowledge in their area of interest. Eligibility: B.Com vs B.Com honors Eligibility for B.Com Candidates must have completed 10+2 from a recognized national or state board institution or 10+3 diploma from a recognized national or state institute. Candidates must have at least 45% aggregate in 10+2 / diploma (40% for reserved categories). Candidates must have studied Commerce as their stream in Class 11 and 12. Candidates should have studied compulsory subjects like Accountancy, Business Studies, and Mathematics/Economics in their 10+2 education. Eligibility for B.Com Honors Candidates must have completed 10+2 from a recognized national or state board institution with at least 50% aggregate. Candidates must have studied accounting, business & math in 11th and 12th Most reputed universities administer entrance exams to admit candidates to B.Com Honors degree courses. Note: Eligibility criteria may vary with university Course curriculum: B.Com vs B.Com honors B.Com course curriculum Semester 1Semester 2Semester 3Semester 4Semester 5Semester 6General EnglishComputer Awareness and InternetBusiness CommunicationIndirect TaxesManagement AccountingEntrepreneurship DevelopmentEconomic TheoryMarketing ManagementFinancial ManagementFinancial ServicesInvestment Options & Mutual FundsPrinciples & Practice of AuditingFundamentals of Accounting IFundamentals of Accounting IICost AccountingCorporate AccountingMoney and BankingBusiness EnvironmentBusiness OrganizationBusiness LawBusiness StatisticsEnvironmental ScienceE-CommerceDirect TaxesPrinciples of Business ManagementFundamentals of Entrepreneurship and InnovationFinancial Statement InterpretationHuman Resource ManagementInternational Trade and FinanceDissertationEconomic Environment in India B.Com Honors course curriculum Semester 1Core papers-Financial Accounting -Business Laws Generic elective (Any one)-Basics of Accounting -Business Organization and Management Semester 2Core papers-Corporate Accounting-Corporate LawsGeneric elective (Any one)-Entrepreneurship-Finance for Non-finance Executives Semester 3Core papers-Human Resource Management-Income- Tax Law & Practice-Management Principles & ApplicationsGeneric elective(Any one)-Investing in Stock Markets-Human Resource Management-Fundamentals of MarketingSkill Enhancement Course (Any one)-E-commerce-Training & Development-Digital Marketing-Personal Tax Planning-Communication & Documentation Business-Personal Finance & Planning Semester 4Core papers-Cost Accounting -Business Mathematics-Computer Applications in BusinessGeneric elective(Any one)-Insurance & Risk Management-Project Management & TechniquesSkill Enhancement Course (Any one)-Computerized Accounting System-Business Research Methods & Analytics-Leadership and Team Development-Collective Bargaining & Negotiation Skills-E-Filing of Returns-Cyber Crimes and Laws Semester 5Core papers-Principles of Marketing-Financial ManagementGeneric elective(Any one)-Management Accounting-Organizational Behavior-Macro- Economics-Entrepreneurship DevelopmentDiscipline-specific Elective-Corporate Tax Planning-Financial Markets, Institutions and Services -Advertising and Personal Selling-Business Statistics Semester 6Core Papers-Auditing & Corporate Governance-Goods & Service Tax (GST)Discipline-specific Elective (Any one)-Fundamentals of Investment-Compensation Management-Business Tax Procedures and Management-Consumer Affairs and Customer Care Discipline-specific Elective (Any one)-Financial Reporting & Analysis -Banking and Insurance -Project Management & Techniques -International Business-Industrial Relations and Labor Laws Note: This course curriculum is of Delhi University & is only indicative. Curriculum may vary with university. Also read: B.Com project ideas Career opportunities: B.Com vs B.Com Honors Truth to be told, there are no major differences between the kind of career opportunities you will find after completing either a B.Com or B.Com honors. However, B.Com honors is a more specialized degree, that focuses on the electives and subjects that you choose to specialize in. We’ve tried to jot down the most common careers that you can explore after pursuing these degrees. Jobs after B.Com Here are some the top jobs after B.Com Accountant The primary role of an accountant is to prepare and examine financial records. They ensure that financial records are accurate, that taxes are paid correctly and on time, and assess financial operations to help organizations run efficiently. Tax Consultant A tax consultant advises businesses and individuals with issues related to their taxes. They help clients navigate complex tax regulations, ensure compliance with tax laws, and seek deductions and credits. Auditor Auditors examine and prepare financial records while checking for their accuracy, then explaining their findings to key stakeholders. Internal auditors check for mismanagement of an organization’s funds and identify ways to improve processes for eliminating waste and fraud. Banking Jobs With a B.Com degree, you can get entry-level positions in private and public sector banks. Jobs can range from bank teller to bank manager. Read more: How to get a banking job after B.Com Human Resources (HR) Manager Although it may not directly relate to commerce, many B.Com graduates find successful careers in HR. HR Managers are responsible for coordinating an organization’s administrative functions and ensuring smooth communication between employees and management. Jobs after B.Com Honors Chartered Accountant (CA) This is one of the most sought-after professions for commerce students. Chartered Accountants work in all fields of business and finance, including audit, taxation, financial and general management. Financial Analyst Financial Analysts assess the performance of stocks, bonds, and other types of investments. They guide businesses and individuals in making investment decisions. Company Secretary (CS) Company Secretaries deal with the legal activities of any business. The role of a CS is to keep the company’s records, advice on governance and statutory compliance, and implement corporate strategies. Investment Banker Investment Bankers help companies, governments, and other groups plan and manage large projects, saving their client time and money by identifying risks associated with the project before the client moves forward. Tax Auditor/Consultant They help their clients with their financial and income tax statements. This can be at the federal, state, and local level. Their goal is to help clients minimize their tax liabilities. B.Com vs B.Com Honors: What’s best for you? If you want an overview of all commerce-related subjects, then you must take up a B.Com degree. If you are looking to study in-depth and gain extensive knowledge in commerce, then you can choose to pursue B.Com (Hons). If you’re looking for a more general education that still offers a wide range of career options, a regular B.Com degree will suffice. If you’re certain about building a career in the field of commerce – for example, becoming a Chartered Accountant, Company Secretary, you might benefit from B.Com (Hons). The admission process and eligibility criteria for B.Com (Hons) can be more stringent than for the regular B.Com program. You typically need a higher percentage in your Class 12 exams to qualify for B.Com (Hons). If you’re planning to pursue higher studies, consider which program will better equip you. Conclusion If you are looking to pursue a B.Com degree online, look no further than Online Manipal. The online B.Com degree offered by Manipal University Jaipur is flexible, affordable, and accessible from anywhere. You can get to interact with peers from world over, faculty, industry leaders and experts.
Webinar: Emerging Careers in Data Science and Analytics Why Data Science has the hottest Jobs today? In an age defined by data-driven decision-making and technological advancements, there are but a handful of domains that have captured the spotlight as emphatically as Data Science. With every digital interaction, a trail of data is left behind, and within that data lies a treasure trove of insights waiting to be unearthed. It’s no wonder that Data Science has taken the centre stage of the job market, offering some of the most sought-after and compelling opportunities of our time. As organizations across industries recognize the immense potential of data to drive innovation, efficiency, and strategic growth, the demand for skilled Data Scientists has surged, making it one of the hottest job prospects today. Here are a few captivating facts as to why Data Science commands respect for hosting the hottest jobs in today’s times. The data science market size is expected to grow from USD 95.39 billion in 2021 to USD 322.9 billion by 2026. Artificial Intelligence is increasingly becoming popular in business, and companies of all sizes and from all locations feel they need data scientists to develop Al models. According to the US Bureau of Labor Statistics, the number of jobs requiring data skills is expected to grow by 27.9 percent by 2026. About 80 percent of the firms across the globe are investing a large part of their earnings into creating a skilful data analytics division, thus hiring the smartest of people in the industry domain. According to IBM, we are generating data at the rate of 2.7 Quintillion bytes per day and 90% of the world’s data (that’s 90% of all the data ever created) had been created in the previous two years. According to the data perspective, about 90% of the data that has been created, have been created from the last couple of years. From the skill perspective, the amount of data created is so humongous, that companies are now sitting on explosive amounts of data and are not sure what to do with the same. Therefore, they are investing actively to find ways to leverage this data goldmine. What Is Business Analytics? Let’s assume I am a company operating from several years looking forward to take an important meaningful decision that involves a huge risk or a large sum of money. Then you know this decision will not be taken randomly. I will collect all the data available to me, I will analyse all the data I am exposed to, and only after understanding the situation, I will be making that important decision. This whole process of making decisions, after investigating data and making the necessary predications is called Business Analytics. In-depth: What Is Business Analytics? The business analytics process includes data collection, data mining, descriptive analytics, predictive analytics, and visualization and reporting. Business analytics builds on the foundation of business intelligence and attempts to make educated predictions about what might happen in the future using next generation technology. Business analytics uses cloud analytics tools, such as machine learning, data visualization, and natural language query, to process, sort, and present data from various sources. Business analytics Process Like other emerging technologies, business analytics also use several tools and technologies. There are several steps involved in the process of analysing a data. There are mainly five steps involved in this process and the same will be explained below: Data collection – We live in 2023, which means data is generated by each and every device like the cameras, your refrigerator or your cell phone etc. From a business point of view, it can be something as simple as a social media copy posted by an organization, or a ThinkPad sensor in a factory, etc. Therefore, there are different types of data that are available in different formats for data collection. This step helps us understand the different kinds of data that can be collected in a process and how the same can be converted to a reliable database which are usually cloud-based. This is very important as data can be in any form, like it would be text based or image based, which needs to be processed into a single database. Data Mining – Once the data is collected, the next step is to process it. The collected data needs to be sorted, so valuable insights can be gained from the same. This step usually uses machine learning to identify meaningful insights and patters that can be extracted from the data. Using of these technologies, enables a data scientist to identify reliable patters and monetizable trends in a shorter period compared to when the same is done manually. Descriptive analysis – Is all about making sense of the data. This step is basically to understand the story behind the data. The conditions and parameters in which this data was generated. This has a great influence in shaping the direction of our decision. Predictive analysis – Business analytics tools will then start to build predictive ML/DL models based on trends and historical context derived from the above steps. These models can thus be used to inform future decisions regarding business and organizational choices. Visualization & reporting– Understanding a data model is not easy. If you are a data scientist, then you would have without a doubt constructed a reliable model that would give invaluable insights about the business. However, when communicating the same to other teams or business heads, everyone might not always understand the technicality of your decisions. This is where visualization comes into picture. Being able to present the insights obtained for further course of action in an understandable manner becomes very important when multiple teams are in the game. This is done by converting all technical information to easily comprehensible graphs and charts. What is the major Difference between Business Analytics and Data Analysis? Data analytics is an extremely general nomenclature for the process. For instance, if you are solving a problem that uses data, then it’s a normal data analysis process. However, if the analysis and subsequent output is obtained to solve a business problem, then it’s called a business analytics process. Also read: Difference between business analytics and data science Uses of analytics in the industry! Marketing: Analytics to identify success and impact Analytics in marketing is used for multiple activities. Which customers are more likely to respond to an email campaign? What was the last campaign’s ROI? More and more marketing departments are trying to better understand how their programs affect the business at large. With Al and machine learning powering analysis, it’s possible to use data to drive strategic marketing decisions. Human Resources: Analytics to find and share talent insights The need for the use of analytics here is to understand and fulfil the employment needs of an organization as well and employees. It’s to understand pointers like What drives employee decisions regarding their career? More and more HR leaders are trying to better understand how their programs affect the business at large. With the right analytical capabilities, HR leaders can quantify and predict outcomes, understand recruitment channels, and review employee decisions. Sales: Analytics to optimize your sales What is the critical moment that converts a lead to a sale? In-depth analytics can break down the sales cycle, taking in all the different variables that lead to a purchase. It helps you to breakdown the mind of the consumer at every stage. Price, availability, geography, season, and other factors can be the turning point on the customer journey—and analytics offer the tool to decipher that key moment. Finance: Analytics to power predictive organizational budgets How can you increase your profit margins? Finance works with every department, be it HR or sales. That means that innovation is always key, especially as finance departments face larger volumes of data. With analytics, it’s possible to bring finance into the future for predictive modelling, detailed analysis, and insights from machine learning. Career Options in Business Analytics: Overview and key differences in skillsets We all have belonged to a phase where we feel – I do not have experience into this field and I want to go into this field? I am new will I be able to make my career etc. Understanding how your career can span out in the field of data, we must consider it in a top-down approach and identify the different job roles associated with each stage. Data Collection – If you want to deal with the backend data then becoming a data engineer might be a great choice. As we know data can be in any form – it can be an image data, text or it can be purely numbers. Activities like how to store the data, how do you make it available how do you make queries run really fast, are all a part of data collection and mastering the same opens your opportunity to become a Data engineer. Data Mining – This is usually done by data analyst or a data scientist. These two roles are usually interchangeable. Both the roles have spill over responsibilities and must be equipped in sorting the data or building the relevant ML model. Descriptive analysis – this step in the process is usually associated with business analysts. Here it’s all about understanding the history of the data to address a business problem Predictive analysis – This is ideally the major job description of Data Scientists. Identifying patters and trends and predicting future demands is the basic role of a Data Scientist. Visualization & Reporting – This can be considered the face/front end aspect of the data business. Don’t forget: Career options with an M.Sc. in Business Analytics Top opportunities with M.Sc. in Data Science in India Key skill set for a career is data! Being a wide domain, data has opportunities to offer access industries. There are only few prominent ones lifted below. However, with niche skill set and affinity towards data, one can carve out successful careers in cross functional teams like – technical predict manager, technical program manager etc. Data Scientist – Deals with ML modelling – Data exploration using EDA Business Analyst – Deals with Data Visualization – SQL scripting and EDA Data Engineer – Backend storage of Data – Big Data Technologies ML Engineer – Building platforms and features for Data Scientist – More geared towards software development Check this out: How to get into the business analytics industry? Some common misconceptions about Data! Everyone has a lot of confusion about this domain as it is relatively new. Here are a few most common misconceptions about the data science domain and the answers for the same. Data Science is just another name for computer science. Most people often believe that they need to have a computer science background to excel in data science. This is completely untrue. Data science is integrated everywhere. It’s used by lawyers, doctors etc who too have no computer science background. Most data scientists today have picked up this skill by either venturing into the stream and taking a chance, or by pursuing a course which will help them in understanding the basics. Data science is dominated by mathematicians. This is a very common misconception because of which many people tend to not take up the opportunity. Advanced mathematics might be needed in some niche part of the job roles, but that is not true for 90% of the job requirements. Most aspect of the data science job requires you to have a keen understanding of basic mathematics of upto 10th – 12th standard which most of us would have already delt with in our academic years. To succeed in the field of Data Science, you must be a hardcore coder. If this is true one might as well become a software developer, why become a data scientist, correct? To become a successful data scientist, you need to have some basic programming skills. You will not be required to solve complex dynamic problems. Business/Domain knowledge is not so important. The requirement is quiet opposite to the misconception. It very important to have the necessary domain knowledge to solve a problem. Although you need not be a maser in the domain you are working on, but having a basic idea is very important. This will in fact help you get a clear picture of the problem being addressed and give you all the necessary insights to build the perfect solution model. Learning a tool is most important in Data Science. Well, the idea is to use these tools to make your job easier, not the other way around. There is no one correct tools for all problems. As a skilled professional you must be able to solve a give problem using any tool available. Therefore, there is no point in only becoming a python or a R champion. Develop your skills and be ready to think critically to obtain a solution irrespective of the tools at hand. Data Science is all about building models. These very steps and processes od data science will prove it to you its not all about building ML models. Building reliable models is only one of the important aspects of data science, which gives birth to different types and roles for aspirants. How to kickstart a career in Data Science? Choose the right role. There are many roles within Business Analytics Domain like for example – Data Scientist, Business Analyst, Data Engineer etc. Pick a role based on your area of interest. You can do quick research to figure this out before pursuing the same full-fledged. Take up a Course and Complete it. This is good for aspirants across all experience level. Take up a specialization course and complete the same with dedication to understand the latest ongoings of the domain. Also, pursuing a course will help you get a brief insight into all aspects of data management. Then based on your interest you can pick one of the niches and master the same. Choose a Tool / Language and stick to it with complete dedication. This might sound contrary to what we have said before, but here we are talking about quality instead of quantity. The depth of your knowledge is more important than the width, imagine you know 5+ tools with very basic or no knowledge, instead of just one tool/language perfectly, then you will most definitely not land a job. Therefore, it is important to master a particular tool/language to establish a successful data science career. Note: This blog is based on insights from Syed Mohammed Ali, Data and Applied Scientist, Microsoft .
Evolving role of finance leaders in the digital world Multiple global megatrends have had a knock-on effect on financial operations in the corporate world, with shifting business demands, digital momentum, and technological advances. As a result, the role of finance heads has undergone tremendous transformation. They are now expected to take the lead as strategic partners and serve as the business’s principal advisors, assisting stakeholders in making decisions, mitigating risks, and propelling the new-age narrative using digital advances. Finance heads have to revamp their operational models to keep pace with the expanding business challenges and digital transformation in finance leadership. Overall, the role of finance professionals is undergoing shifts in the digital era, mandating switching from a conventional financial perspective to a strategic approach. By adopting strategic management, finance executives can capitalize on the groundbreaking capabilities of digital technology. Read more: Emerging trends in corporate finance Responsibilities of finance leaders Today’s finance executives are responsible for a wide range of obligations that are vital to the performance of their businesses. They must adapt to numerous advances as the company environment changes, notably in the area of digitization. The following are some changing responsibilities of financial leaders: Adapting to innovations: Finance heads must keep abreast of technological developments and comprehend strategies to leverage digitization to improve financial operations and decision-making processes. They ought to actively seek for approaches to streamline financial procedures, automate repetitive tasks, and discover digital solutions that could enhance precision and effectiveness. Developing digital skills: Finance leaders must enhance their digital skills if they intend to thoroughly embrace digitization. They must be well-versed in all financial-related digital technologies and tools, including the cloud, data analytics, and ERP (Enterprise resource planning) platforms. Leveraging digital analytics: Finance leaders need to utilize digital analytics to acquire insightful information and drive strategic financial choices in light of the growing availability of data. They should be able to collect, analyze, and interpret financial information to discern trends, patterns, and business prospects. Finance professionals can deliver precise projections, improve business performance, and foster data-driven choices by harnessing the potential of digital analytics. Risk management: Financial risk management and mitigation within organizations are crucial roles of finance leaders. They must be fully versed in financial guidelines, compliance specifications, and industry-standard practices. These can help safeguard the business’s financial resources, uncover possible risks, and devise efficient mitigation plans by implementing comprehensive risk management strategies. Skills required for finance leaders Finance heads require a broad spectrum of skills to expertly navigate the intricate and constantly shifting financial landscape. The vital skills for financial executives are listed below: Data analytics: Finance leaders must understand data analytics to fully capitalize on the potential of financial data. This competence entails having the ability to accumulate, organize, and interpret enormous amounts of financial data. They ought to be knowledgeable in statistical analytic methods, data visualization software, and financial modeling. Finance leaders must be capable of finding important insights, predicting trends, spotting anomalies, and arriving at informed decisions by adopting data analytics. Digital proficiency: Finance heads need to be adept users of technology and digital tools in today’s digital world. Such abilities include expertise in accounting software, ERP platforms, and financial analytics solutions. They should also be conversant with cutting-edge technologies such as blockchain, AI, and RPA (Robotic process automation). Digitally proficient finance leaders can automate repetitive procedures, expedite financial processes, and boost accuracy and productivity. Data storytelling: Effective communication of intricate financial information to multiple stakeholders is a skill that finance leaders should have. Presenting financial data in an appealing and relatable way is an art termed data storytelling. They must be able to condense complicated financial ideas into compelling tales that resonate with their target demographic. Finance professionals may effectively communicate the significance of financial findings, improve decision-making, and motivate actions by using data storytelling strategies. Business intelligence: Strong business acumen and an extensive understanding of marketplace and industry dynamics are essential for finance leaders. Maintaining current knowledge of market trends, competitive analysis, and economic variables that may affect an organization’s financial performance is required for this competency. Finance leaders may contribute to overall corporate strategy, offer strategic insights, uncover growth opportunities, and manage risks by fusing financial data with market expertise. Read more: Effective strategies for financial product selling Digital transformation in finance leadership The financial sector has undergone a digital revolution, and its effects on financial leaders cannot be understated. Financial leaders are going through a paradigm shift in their duties and responsibilities as a result of the enactment of cloud-based tools, the emergence of cutting-edge technologies like blockchain, and a greater emphasis on security and compliance. Great use of blockchain: The financial environment has been reshaped by blockchain technology, allowing for greater openness, security, and performance. Blockchain is being embraced by prominent financial firms to speed up procedures, including transaction settlement, managing supply chains, and identity verification. Blockchain gives real-time visibility into financial interactions and offers a decentralized ledger, avoiding the need for intermediaries and diminishing the likelihood of fraud and blunders. This provides finance leaders with precise and auditable data, which facilitates them to make educated choices, increase operational effectiveness, and foster stakeholder trust. Security and compliance: Financial leaders face the crucial task of protecting sensitive financial information in an era when cyber threats are pervasive. As businesses now have to abide by strict standards and safeguard client data, there is a greater emphasis on security and compliance. Financial leaders are adopting cutting-edge cybersecurity solutions like multi-factor authentication, encryption, and intrusion detection devices to strengthen their digital infrastructure. They are additionally putting into effect rigorous risk management structures, carrying out routine audits, and investing funds in employee training to ensure adherence to shifting regulatory standards. Financial leaders may reduce risks, safeguard their company’s brand, and cultivate trust among investors and customers by adopting digital security practices. Cloud-based tools: The way that financial leaders organize and safeguard data, collaborate with teams, and access essential apps has undergone a complete transformation, thanks to cloud computing. Financial leaders are given the choice to optimize resource allocation and optimize operations by using cloud-based technologies owing to their scalability, flexibility, and cost-effectiveness. They may utilize cloud-based financial management and accounting solutions to automate procedures, increase accuracy, and deliver real-time insights. Furthermore, cloud-based collaboration solutions offer remote work and seamless communication, enabling financial executives to communicate with stakeholders and teams at any time and from any location. Financial leaders may improve agility, stimulate innovation, and quickly adjust to shifting market dynamics by leveraging cloud-based solutions. Read more: Top emerging technologies in financial services and how to upskill in them Pursue an online MBA in BKFS from TAPMI TAPMI’s online MBA in BKFS curriculum allows you to stay abreast of the trends in new-age banking and finance. You will learn Fintech & role of emerging technologies in finance, Analytics & AI in finance, risk analytics in finance, and more, that will help you become competitive finance leaders in the digital age. Conclusion Everywhere in the world, finance is geared up to take on more complex and demanding roles for decision-making across multiple business domains. The leaders require to provide extra motivation internally and make broad and deliberate use of current technologies. Next-gen finance heads must promote innovation, regulate employee expectations, and incorporate technology to be able to handle the possibilities and challenges of the business climate of today and tomorrow to maximize corporate growth. Read more: Emerging trends in the BFSI sector
Why today’s banking professionals must master the applications of AI The digital revolution is transforming the functionality of every other industry operating today. The time to embrace AI’s potential is now, making it essential for banking professionals in the modern banking sector to be skilled in leveraging artificial intelligence (AI). Banking professionals can deploy the powers of AI to derive valuable insight from enormous quantities of data. It can empower them to make data-driven decisions, mitigate risks, and foster business expansion. Benefits of AI in banking The global marketplace has fully embraced artificial intelligence, and banks have already begun incorporating this technology into their offerings. An online MBA in banking and finance consists of AI in its curriculum, allowing professionals to gain broader knowledge in advancing technologies. Let’s delve into the AI applications in the banking industry. Risk management: Large volumes of data can be quickly and correctly analyzed by AI-powered systems, facilitating banks to strengthen their risk management competencies. Machine learning techniques are leveraged by AI systems to quickly identify patterns, abnormalities, and potential risks. As a result, banks have become more equipped to spot fraudulent activity, gauge creditworthiness, and oversee compliance. Chatbots: AI-driven chatbots have redefined customer interactions in the banking sector. These virtual assistants provide 24/7 support, responding to consumer inquiries and offering tailored assistance. Chatbots use NLP (Natural language processing) abilities to interpret and respond to consumer inquiries rapidly and precisely, accelerating client satisfaction and driving up service response timelines. Improved customer experience: AI enables banks to provide their consumers with tailored and catered solutions. AI algorithms get valuable insights into the interests, behaviors, and demands of customers by examining customer data. As a result, banks can provide specialized merchandise suggestions, discounts, and advertising initiatives. Additionally, AI streamlines customer onboarding and alleviates paperwork by automating procedures like funding approvals, opening accounts, and KYC (Know Your Customer) processes. Cybersecurity: AI systems rapidly determine prospective security breaches and indicate dubious activities by skillfully detecting anomalies in real-time. Banks are now better equipped to create robust safety precautions and proactively fend off fresh breaches, thanks to machine learning algorithms that continually evolve from patterns and data. Large volumes of transactions are analyzed by AI-powered fraud detection systems, which spot trends that point to fraudulent activity and aid in reducing monetary losses. Predictive analytics: Banks can forecast client behavior, anticipate market shifts, and streamline operations by utilizing previous data and machine learning algorithms. Risk evaluation, scoring credit, and making investment choices are all facilitated by predictive analytics. Additionally, it allows banks to provide customers with proactive financial counseling and guidance following their expenditure patterns and financial objectives. Read more: How analytics in banking opens doors to lucrative careers Why banking professionals should master AI Professionals must become proficient in AI to stay relevant in the evolving banking sector. The benefits of mastering AI for banking professionals are listed below. To meet job demands: Banking professionals should be adept in AI owing to the industry’s growing need for individuals versed in artificial intelligence technology. Industries are on the lookout for workers with the skills to deploy AI tools and strategies as AI keeps reshaping a broad spectrum of industries, including banking and finance. Banking employees can enhance their future opportunities and stay on par in a volatile work setting by becoming experts in AI. To track market trends: Banking personnel can more effectively and precisely track market developments with the use of AI. AI algorithms have the potential to evaluate and uncover correlations, trends, and oddities in real-time using the immense quantity of data generated by the financial sector. Banking professionals can gain substantial insights into marketplace dynamics, client behavior, and industry advances by leveraging AI capabilities. Everything is digital: In recent years, the banking sector’s digital shift has been revving up, and AI is crucial to this paradigm transition. Banking professionals need to become experts in AI to effectively maneuver the digital world and comprehend how AI-powered innovations are transforming conventional banking processes. They can use these technologies to improve operational efficiency, optimize operations, and provide consumers with cutting-edge solutions. Data collection and analysis: Banking professionals who have mastered AI can efficiently collect, process, and interpret massive amounts of data in real-time, allowing them to reach data-driven choices, pinpoint risks, identify fraud, and come up with tailored offerings. Professionals can use AI-powered data analytics to improve risk management procedures, discover prospective opportunities, and streamline operational processes. To work on improving customer experience: Banking professionals can make use of tools like predictive analytics, machine learning, and natural language processing to create customized solutions, automate repetitive operations, and offer preemptive assistance to clients. AI-enabled virtual assistants, chatbots, and recommendation engines can make targeted proposals, expedite client interactions, and ensure a smooth and efficient banking experience. Higher salary packages: AI proficiency might result in higher earnings for banking personnel. Employees with AI expertise have been in high demand as AI strives to spur innovation and tweak the finance sector. Banks and other financial organizations are willing to shell out resources on top personnel who can capitalize on AI’s potential to enhance business processes. Banking professionals who master AI can be eligible for leadership positions, specialized obligations, and roles that command higher salaries. Read more: How digital transformations are reshaping the future of banking The future of AI banking AI in banks is poised to overhaul the field on multiple fronts in the coming years. Virtual assistants and chatbots driven by AI will reinvent customer service by offering round-the-clock, instantaneous support. Banks will be able to gain deeper insight into the needs and preferences of their clientele thanks to sentiment analysis and natural language processing. Improved data analytics and machine learning techniques will strengthen identifying and avoiding fraud and thus simplify risk administration. AI will additionally transform the credit evaluation and lending processes by utilizing predictive analytics to analyze creditworthiness and speed up loan approvals. The amalgamation of AI with blockchain innovation will further enhance safety, accelerate transactions, and facilitate precise and transparent record-keeping. The financial ecosystem will reap the rewards greatly from improved productivity, personalized experiences, and outstanding risk oversight in the foreseeable future of AI banking. Read more: Neo banks: A revolution in banking The need for skilled professionals The burgeoning discipline of AI has driven up the need for qualified personnel who have the know-how to cope with the sector’s evolving requirements. There is a pressing need for professionals with an in-depth knowledge of AI algorithms, machine learning, and data analysis as businesses implement AI technology. Skilled professionals are needed to develop and execute AI-driven solutions that optimize decision-making, streamline corporate processes, and incite invention. Additionally, the proficiency in security, privacy, and AI ethics ensures ethical and legal AI deployments. The dire need for an adept AI workforce to cater to market demands is further underscored by the realization that professionals with AI expertise are sought after by businesses across sectors. Taking up a banking course can help you excel in this sector. Become future-ready with TAPMI’s online MBA BKFS The MBA in Banking and Financial Services (BKFS) offered by T.A. Pai Management Institute through Online Manipal equips participants with the profound educational experience required to thrive in the ever-evolving banking industry of today and the future. This extensive program aims to deepen participants’ comprehension of the complex dynamics of financial sectors, legal frameworks, managing risks, and novel technologies. Students obtain in-depth knowledge of topics like business finance, investment banking, monetary analysis, and fintech through the online MBA in banking and finance curriculum. Graduates will be well-furnished to confront the complexities and challenges encountered by the banking industry, owing to the program’s emphasis on real-world applications, case studies, and hands-on learning, developing into highly capable employees who can foster innovation and navigate the shifting terrain of contemporary banking. Read more: How you can switch to managerial roles with TAPMI’s online MBA in BKFS
Top FinTech careers to explore in the digital age FinTech has evolved over time, delivering individuals with a straightforward, quicker, less expensive, and more practical means of procuring financial offerings while fostering digital inclusion. This industry is perpetually growing around the world, and India has also witnessed an uptick in expansion. Emerging technologies, changing consumer behavior, and growing investor interest have all fueled the meteoric rise of the FinTech industry. According to estimates, the future Indian FinTech business is estimated to bring in $200 billion by 2030. As the industry evolves, additional expertise is required, which demands a workforce with the right training to bolster the sector’s advancement. It is anticipated that this growth orbit will continue, producing a favorable environment for professionals looking for job opportunities in this sector. Additionally, job opportunities in the digital age for FinTech professionals come with alluring compensation packages. FinTech offers a dynamic environment enabling individuals to flourish and shape the trajectory of finance. Read more: Mapping the surge in fintech startups in India Top FinTech jobs to pursue Growth potential in FinTech careers is substantial that allures individuals towards various positions in this domain. Promising careers in FinTech include the following. Blockchain developer: The task of developing, generating, and implementing blockchain solutions falls under the purview of a blockchain developer. They work on developing smart contracts and decentralized applications and boosting the effectiveness and security of current blockchain systems. Programming, bug fixing, and collaborating with cross-functional teams are some of their duties as they strive to integrate blockchain technology into different financial procedures. The highest estimated salary of a blockchain developer is ₹ 19.0 Lakhs. Quantitative analyst: A quantitative analyst, commonly referred to as quant, uses statistical and mathematical techniques on financial data to create models and trading and investment strategies. They perform risk analysis, design algorithms, analyze big databases, and offer insights to help investors make the best possible investment choices. They frequently collaborate closely with traders and portfolio managers. The highest estimated salary of a quantitative analyst is ₹ 34.8 Lakhs. Cybersecurity expert: In the FinTech sector, a cybersecurity expert is in charge of shielding infrastructure, data, and financial systems against online attacks. They develop and execute safety protocols, keep an eye out for system flaws, carry out risk analyses, and manage security occurrences. These experts collaborate directly with IT teams, regulatory officials, and upper management to ensure data safety and uphold regulatory compliance. The highest estimated salary of a cybersecurity expert is ₹ 24.0 Lakhs. Financial analyst: A financial analyst is essential for analyzing financial data, performing research, and offering analysis to promote investment choices. They examine financial statements, evaluate market trends, create financial models, and offer suggestions for improving financial performance. Investment bankers, portfolio managers, and other stakeholders are frequently close associates of financial analysts. The highest estimated salary of a financial analyst is ₹ 12.3 Lakhs. Data analyst: A data analyst is tasked with gathering, compiling, and analyzing massive datasets to derive actionable insights. They employ statistical tools, data visualization methods, and machine learning algorithms to find trends, correlations, and patterns in financial data. Additionally, this personnel enables the development of data-driven models and strategic decision-making. The highest estimated salary of a data analyst is ₹ 12.0 Lakhs. Compliance manager: A compliance manager ensures that a FinTech company complies with legal obligations and professional norms. They create and administer compliance programs, carry out risk analyses, keep surveillance for suspicious activity in transactions, and give advice on compliance-related issues. Compliance managers collaborate closely with legal departments, higher-ups, and regulators to preserve a lawful and morally upright workplace. The highest estimated salary of a compliance manager is ₹ 25.0 Lakhs. Read more: Emerging trends in corporate finance How to start your FinTech career There are a few essential steps you may take to start a successful FinTech career. Here is an easy-to-follow outline on how to enter the FinTech industry: Pursue a master’s degree or certification: Consider earning a master’s degree with a FinTech specialization in a relevant discipline, including finance, business management, or computer science. Alternatives include choosing industry-specific credentials like CBP (Certified Blockchain Professional) or CFTP (Certified FinTech Professional). These credentials show that you’re dedicated to exploring everything you need to know about the FinTech industry. Stay abreast of FinTech trends: The FinTech scene is continually changing with changes in regulations and technological breakthroughs. Utilize credible industry journals, academic papers, relevant conferences, and webinars to stay up-to-date on the most recent trends, developments, and market dynamics. This will demonstrate your zeal for the field and commitment to keeping up with FinTech’s rapid-fire evolution. Acquire key FinTech skills: Develop a broad repertoire of skills that integrates technological and financial expertise. The ability to program in languages like Python and R, analyze and visualize data, and comprehend blockchain technology, machine learning, AI, cybersecurity, and financial modeling are just a few instances of vital talents. Your marketability and productivity as a FinTech practitioner will rise with ongoing learning and executing these abilities. Build your professional network: Every field, including FinTech, depends extensively on networking. Attend industry events, join FinTech-related associations, and engage on professional networking sites like LinkedIn to forge contacts with experts in the field, mentors, and peers. Developing a solid professional network may unlock avenues to favorable possibilities, collaborations, and valuable insights into the FinTech industry. In-demand FinTech skills to have Certain skills have become extremely valuable and in demand for individuals looking to succeed in the FinTech sector. These are the top five skills required for FinTech careers, along with a description of each: Data analysis: The ability to collect, analyze, and draw conclusions from huge data sets is an important aspect of data analysis skills. For the sake of comprehending patterns, trends, and consumer behavior, competence in statistical analysis, data visualization, and data modeling approaches is a must. Data analysis assists well-informed decision-making, risk evaluation, and the formulation of data-driven corporate growth strategies. AI & ML: The FinTech industry is undergoing a paradigm shift thanks to AI and ML technologies, which automate procedures, enhance client experiences, and improve risk management. Mastering algorithms, data preprocessing, choosing models, and evaluation strategies are prerequisites for AI and ML proficiency. These skills make it possible to create and deploy personalized suggestions, chatbots, fraud detection systems, and predictive models, among other things. Cybersecurity: Robust cybersecurity solutions are imperative as the FinTech sector manages private financial data. Expertise in encryption, secure coding techniques, network safety, and risk management are all part of the discipline of cybersecurity. Cybersecurity experts can maintain regulatory compliance, safeguard financial data and systems from cyber attacks, and mitigate any risks related to data breaches or unauthorized access. Blockchain expertise: In the FinTech sector, blockchain technology has become extremely prevalent owing to the potential of encrypted and transparent transactions. Learning the technology of distributed ledgers, smart contracts, and cryptographic principles inside and out is crucial for adeptness in the blockchain. Blockchain expertise makes it possible to create decentralized financial applications, online identity authentication, supply chain monitoring, and effective cross-border payments. DevOps: The incorporation of DevOps techniques enables more efficient collaboration and quicker deployment of financial apps and systems by bridging the gap between software creation and operations. CI/CD (Continuous integration/continuous deployment) procedures, infrastructure automation, containerization, and cloud computing platforms are all necessary for DevOps proficiency. In the FinTech sector, DevOps expertise improves agility, scalability, and reliability. Read more: Why BFSI professionals should stay abreast of trends in banking Top FinTech companies in India Discussed below are some of the top FinTech companies in India that offer various lucrative opportunities for professionals. Razorpay: Razorpay provides online payment solutions and subscription billing services for businesses. Cred: Cred is a credit card management platform that offers rewards for timely bill payments and expense tracking. BharatPe: BharatPe provides simplified digital payments for small merchants with UPI QR code-based payments, credit services, and POS machines. PhonePe: PhonePe is a digital payments platform that enables users to make payments, transfer funds, and recharge mobiles. Groww: Groww is an investment and wealth management platform that allows retail investors to invest in mutual funds, stocks, and gold. ClearTax: ClearTax offers technology-driven tax filing and compliance solutions, simplifying income tax and GST processes. Mintify: Mintify provides a mobile app for personal finance management, helping users track expenses, set budgets, and gain insights. Insurance Dekho: Insurance Dekho is an online platform that enables individuals and businesses to compare and purchase insurance policies. KreditBee: KreditBee offers digital lending solutions, providing instant personal loans and education loans to young professionals. Pine Labs: Pine Labs specializes in payment and merchant commerce solutions, offering POS systems, payment acceptance, and loyalty programs. Read more: How TAPMI’s online MBA-BKFS helps pursue managerial careers in corporate finance
