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Day: January 17, 2019

How To Get Certified in Blockchain Technology?

Posted on by Imarticus Learning

Last Updated on 2 years ago by Imarticus Learning

How To Get Certified in Blockchain Technology?

Emerging tech blockchain is the star today in many industries. Due to the high demand for professionals who know blockchain, it is a good idea to get trained and certified in blockchain. A few years ago, jobs in the financial market were limited to the traditional set-ups of the organisation. You could be a banker but not a technologist. Today, the digital revolution has created an abundance of jobs of different kinds across various industries.

Programmers who are trained in artificial intelligence, machine learning and blockchain technology are in high demand. This is strictly not restricted only to tech companies. Many organisations are investing to have their employees trained in fintech as they can prepare their workforce for the future.
Blockchain has applications across industries apart from banking and fintech. Healthcare industry uses blockchain to manage patient records, similarly retail uses blockchain for supply chain management. It has revolutionized many industries and is a game changer.
So, what is blockchain? The blockchain is simply a block of transactions that are assembled in a chain. Usually, every block is a transaction, and it is validated with a time-stamp. It is near impossible to tamper with this digital ledger. It also reduces human error and leaves the data immutable.
Here are a few things you should know if you are planning to get certified in blockchain technology.
Only engineers can certify
 Emerging tech is easy to learn, and you do not need to have a qualification in engineering to pursue a course in the same. While it takes focus and discipline to do a fintech certification course, it is not impossible if you do not have a traditional engineering background. Many learning institutions offer professional certification online for blockchain, AI and machine learning without any pre-requisites.
Jobs are restricted
 Due to digitisation, every organisation irrespective of the industry has adopted blockchain. As the application of the framework is simple, it has wide benefits across administrative, logistical spaces. The blockchain is a digital ledger that keeps track of all transactions and payments. Therefore, the traditional role of a ledger and bookkeeper has now moved to those who maintain this in a bank. Job opportunities are plenty and lucrative for those who are trained in blockchain.
Blockchain is illegal
Blockchain is neither free nor illegal. Technology is the backbone of digital transactions, and thereby there is a fear that it is not secure and illegal. However, most banks today are using blockchain to maintain a decentralized database of the ledger and for applications in customer management and database management. Getting certified in one of the biggest technology trends in the world is a good idea from an employability perspective.
Today many companies are quickly adopting emerging tech such as blockchain. This creates a vast amount of opportunity for those who are skilled in managing the technology to derive insights which help businesses make strategic decisions. An ascending career trajectory is guaranteed for those who are certified professionals.

How investment banks operate in DCM markets?

Posted on by Imarticus Learning

Last Updated on 4 years ago by Imarticus Learning

How investment banks operate in DCM markets?

DCM or Debt Capital Markets is the link that connects the corporate issuers and bankers. DCM groups provide advisory services to corporate issuers for debt-raising required for acquisitions, restructuring of debts existing-debt refinancing, and old-debt refinancing. The investment banker is the vital link in the entire process and acts as a broker between the intermediaries. Such investment banking teams need to be agile, flexible and abreast a fluctuating market.

One will need proficiency in markets with fixed income, treasuries, bonds, instruments in the money market, and much more. The investment banker receives a fee from the contracting parties for his mediation and making of financial arrangements, advice on financial issues like mergers, acquisitions, and services in trading of bonds, shares etc.

Let us understand the Debt Capital Market operations to explore the role of the investment banker in DCM operations.

DCM Teams and ECM Teams
DCM teams focus on operating the fast-paced short-term side of financial investments. ECM-Equity Capital Markets teams focus on the long-term investments which move slower. The risk factors keep these two teams in different environs. Obviously, the ECM teams bear more risk with longer termed investments. DCM teams work with debt securities and ECM teams with equity securities. The differences between the teams are due to the risk capabilities and types of investments they focus on.

Debt Capital Markets explained.
DCM or Debt capital markets are capital markets that generate fixed-income and have low-risk. The investors receive debt securities for money lent to the company invested in. The DCM is popular with companies who look for finance through debt. Investors also prefer them as it ensures their capital remains intact while they earn profits and a fixed-income.

Investors are comfortable with low-risk income providing instruments in the DCM like bonds, debt securities, and others. This helps them preserve the capital amount while earning profits when trading in the securities. The investment bankers advice customers for a fee on the risks involved in investing in such money investments.

Debt Securities:
Companies that raise funds make debt securities to the lenders in the form of money market instruments, bonds, treasuries and such. The creditworthiness of the debtor is assessed and sets the interest rate. Higher the creditworthiness lower will be the interest rates.

Debt securities can be obtained from both the primary and secondary markets. The primary market is one where companies issue their bonds. The secondary market is one where persons holding bonds sell them at market prices which may be higher or lower.

Bonds:
 Bonds are securities dealt in by the DCM teams. They have different values, characteristics and return profiles. The most often mentioned bonds are: 

  1. Investment bonds
  2. Bonds with high-yield
  3. Bonds from the government
  4. Emerging markets based bonds
  5. Bonds by the municipality

    Learn all about the DCM team, investment banking roles, and job opportunities, payouts expected and more by doing investment banking courses in India. These courses offer a good grasp of fundamentals, concepts, theoretical knowledge, practical skills and certifications that could help enhance your resume and career. They also offer boot camps, short term workshops, and basic knowledge of technical skills in Java, Python etc.

    For investment bankers. While certification definitely helps, you need to be an excellent communicator and work diligently to acquire the best analytical, technical and business skills crucial to your job role. Another advantage in such courses is of mentoring by certified and experienced industry aces that helps garner the latest best practices, techniques, skills, and practice on the latest trending technologies in the field of investment banking, financial courses and more.

How do investment banks operate?

Posted on by Imarticus Learning

Last Updated on 3 years ago by Imarticus Learning

 

Let us understand a little about investment banks and their operations.

Definition of an Investment Bank.
Investment banks offer funding and advice to clients, corporates and other investors, trade, buy, finance, and sell services, commodities, and financial products to earn money for themselves and their customers. Retail banks offer loans and accept deposits from customers while keeping their money safe.

Modern days have seen banks called universal banks that include both retail and simple investment banking. Example: Barclay’s, Citi and so on. Boutique advisory services, pure investments only banks, and mid-market dealing banks are some other kinds of investment banks.

Who owns them?
 Leading US and European investment banks form public companies whose shares are traded on exchanges. The owners of shares own the bank. Some of the major investors are financial institutions, family holdings, bank directors, HNW individuals, government institutions, both private and public banks and investments banks.

Smaller financed investment banks may be partnership firms or privately owned companies.
Who are an investment bank’s main clients?

The main clients of investment banks are:

• Companies: From varied sectors fintech, energy, construction, retail, technology, healthcare, media, food, drinks, chemicals, organisations including financial services and such
• Funds: Are investment tools which pool assets of investors following an investment pattern and include pension funds, equity funds, and hedge funds
• Government: Semi-governmental institutions, export and credit agencies, wealth funds, and governmental funds
• Individuals with high assets: These are investors with surplus assets over1 million $
• Banks: Most banks protect themselves by investment activities, bank trading, and such to earn brokerage and profits for the bank

The main activities of an investment bank are:

 • Advisory: Clients are advised regarding selling, buying and IPOs of companies, raising money, the maintaining of financial affairs, trading of financial products and economic risk management
• Management of investments: Both individuals and corporations are advised on investment managing
• Providing loans and financing
• Trading: Trading of shares, derivatives, debt products, commodities etc. to earn brokerage
• Monitoring and research: Industry trends, economic developments, investment patterns etc. for clients and itself

How do they make money?
 Investment banks make money by offering these financial services to clients to earn income like

Fees: Advisory charges, finance, and short term funds, for providing loans, keeping money safe for clients, trading services, financing and arranging funds for its clients, research and reports, and investment services generate fees.
Dividends: Shares provide returns on investments.
Interest: Loans generate interest as income.
Investments: Brokerage and profits from making of investments.
Trading: Profits and brokerage made from selling and buying of securities.

What regulates such activity?
Besides government monitoring through regulators and monitoring agencies, the activities are regulated in these areas.
• Adequacy of capital: Banks have to maintain a cash-credit ratio, reserve funds and such.
• Activities undertaken: The operations of particular activities, regulations on operations, differentiation into various divisions, and such regulations prevent problems from spreading to healthy sectors.
• Trading for themselves is also regulated.
• Insider dealing: Prevents banks making unfair profits from client information
• Money laundering: Monitoring to ensure illegal parking of funds, launder money etc
• Transparency: Audits on banks and regulations to disclose their funds status, finances, and activities
• Payments to staff: Regulators scrutinize these to prevent excessive risk to the bank

Why does the economy need them?
 Investment banks are integral to the financial global ecosystem. They are crucial for the system and offer stability through their services like
• Providing businesses finance
• Advisory services
• Managing risks
• Providing research, strategy, and information
If you wish to learn more about investment, you can learn investment banking course. 

Also Read: What are the Best Investment Banks to Work For

How do Data Scientists Use Programming?

Posted on by Imarticus Learning

Last Updated on 3 years ago by Imarticus Learning

 

There are few fields in the world which have grown in stature as data science has in recent years. As a discipline, the growth of data science has been unparalleled – machine learning and AI are now implemented in a host of large organizations around the world. 

With every passing second, new data is created by millions of users around the world. Companies try to leverage this data by analyzing it, and data science is used to get business value from the findings. This means that using data science as both a business tool and a product, a number of companies have made business decisions which have made them grow quicker than ever. 

With the rise of data science, the demand for capable data scientists has also improved. It is now one of the most lucrative career options and one which is extremely accessible too. However, how do you become a data scientist, and is programming truly required for being successful in the discipline?

The Importance of Programming for a Data Scientist

Programming remains to be one of the main technical skills which any data scientist requires to succeed. In the initial stages of learning, one does not need to know much programming. This is because the focus is one using the tools at hand to implement algorithms, in order to analyse the data at hand. 

However, when you grow in your career, you will find that you need to modify algorithms or even create new ones for analysis. This means that you will have to modify the codes behind them, or even write a new algorithm from scratch. This requires you to have a command over at least one programming language – be it Python, R or Java. 

Knowledge in programming and statistics can go a long way in helping you implement your own algorithms and analyse the data in a more efficient manner. It will help you manipulate the data set, and bring any unconventional ideas you have to life. If programming is something you can’t do, you will be forced to use the tools at hand without the option of trying to change those tools themselves. While you may be able to manage with this, it will have an impact on your career in the long run. 

Can Data Scientists Be Good Without Programming?

Of course, if you do not know how to program, the obvious thing would be to start learning it since it can improve your career over the long term. However, there are some other ways in which you can excel at your job too. You should try and master a GUI tool, like Tableau so that you are able to visualize your data in a much more efficient manner. You should become a storyteller, and must be able to convey the story the data tells you in a concise manner to the client. Excelling at sales would also help, since you may have to interact with the client a lot. 

If you find yourself interested in machine learning and data science, you should definitely check out the data science course at Imarticus Learning. It is one of the best data science training in Banglore. 

Do Data Scientist Use Statistics?

Posted on by Imarticus Learning

Last Updated on 3 years ago by Imarticus Learning

Do Data Scientists Use Statistics?

Data science has been the buzzword of the tech industry for the past few years. Everyone is aware of the endless opportunities and large pay scale awaiting the data scientists. But when the question becomes “what do they do?” or “how do they do it? ” Only a few people know it. This article discusses whether data scientists use statistics in their operations. Read on to find out.

Statistics in Data Science
Statistics can be a very powerful tool in data science. It is simply the use of mathematics to analyse the data technically. The following are the few important instances where data scientists use statistics.

  1. Design Experiments to Inform Product Decisions.
    Data scientists use Frequentist Statistics and experimental design to determine whether or not the difference in the performance of two types of products are significant to take action. This application help data scientists to understand the experimental results especially when there are multiple metrics being measured.
  2. Models to Predict the Signal
    Using Regression, Classification, Time series analysis and casual analysis, data scientists can tell the reason behind a change of rate of sales. They use these techniques to predict the sales of upcoming months and point out the relevant trends to be careful of.
  3. Turning Big Data Into Big Picture
    Consider a large group of customers buying products. The data about each person’s shopping list is worthless if it stays like that. Data scientists can label each customer and put similar ones into a group and understand the buying pattern. It helps to identify how each group of people affect the business development. Statistic techniques such as clustering, latent variable analysis and dimensionality reduction are used to achieve this.
  4. Understand User Engagement, Retention, Conversion and Leads
    It is known that many customers would be lost from the signing-in stage to the actual regular use stage. Data science use techniques such as regression, latent variable analysis, casual effect analysis and survey design to find out the reason behind this loss. It also identifies the successful leads the company is using to engage more customers.
  5. Predicting the Customer Needs
    Statistical techniques such as latent variable analysis, predictive modelling, clustering and dimensionality reduction help data scientists to predict the items a customer might need next. A matrix of users and their interactions with the company product is all that is needed to obtain this.
  6. Telling the story with Data
    It is the end product of all operations of data scientists. He acts as the ambassador between the company and data. All the findings from data should be properly communicated with the rest of the company without losing any fidelity. Rather than summarizing the numbers, a data scientist has to explain why each number are significant. To do that properly, data visualisation techniques from statistics are used. Clearly, data scientists use statistics to solve various problems in their day to day life. If data science seems the right career choice for you, don’t wait for long. Imarticus  Learning is now providing course on data science prodegree. This Genpact data science course will equip you with all the necessary skills for a successful data science career.
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