How can actuarial science skills be applied in investment banking?
To understand how skills in actuarial science can be applied to investment banking we need to understand what actuarial science deals with.
So what is actuarial science?
Actuarial science can be defined as the application of mathematical skills to social science to solve important issues. Most of the time the actuaries use statistics to solve the issues by reducing risks in the insurance industry, government, business and in academic research. Actuaries use statistics and mathematical models to predict uncertain events like income from an insurance policy, payout from pension scheme and performance of stock markets.
Actuarial science deals with the technical understanding of the following areas:
Though most qualified actuaries choose to work in the insurance industry their skills are highly valued in the investment banking sector. Investment banking sector tends to be highly volatile and unpredictable. Investment banking deals with a lot of risks. Risk while investing in stock market and during mergers and acquisitions. Basically, actuarial science can be applied to any field that has an element of risk associated with it.
An investment banker who has actuarial skills will be well equipped to assess how much risk is attached to each merger, acquisition or investment in stocks and hedge funds.
An actuary has expert skills at projecting future cash flow. This skill can prove to be immensely invaluable in mergers and acquisitions for business owners. Typically companies rely heavily on the financial reports and assessment of an investment banker of companies during mergers and acquisitions. The ability to predict future cash flows with scientifically backed statistical models can bring a lot of clarity during decision making.
Skills in actuarial science equip an investment banker with the mathematical skills, modeling skills, ability to understand financial statements with ease.
The statistical tools used by an actuary to score the worthiness of a client for health and automobile insurance can be applied in assessing the ability of a client to pay back the loan successfully or predicting the ability to default on the loan. This comes in handy especially when financing businesses and their ability to pay back huge loans. Similar models come in handy for home loans and personal loan predictability too
Actuarial science deals with risk management and investment banking involves huge risks so actuarial science skills make an investment bankers job easier.
Investment analysis actuary falls a major type of actuary called the banking actuary. The people equipped with these skills are usually hired by merchant banks and equity research companies for analyzing investments.
Another major type of actuary is investment actuary. The investment actuary has the necessary skills to determine the liability risk involved in any investment strategy design and products, tools and models to minimize and manage such risks.
An investment banking will have to pore over a lot of data when reading the financial reports and performance reports of a company. Having actuarial skills can help in creating mathematical models of the reports for quick reference. These models can be referenced quickly instead of trying to find and make sense of huge amounts of data while assessing the profitability of a company or a deal.
Becoming an actuary is a long and arduous road one which requires lots of studying and having to clear multiple actuarial exams. People who have actually pursued a degree in actuarial science rarely tend to work as investment bankers. They usually go on to be employed as actuaries mostly working in the insurance sectors. Even If you have a degree in actuarial science you will need additional skills to excel as investment bankers. An investment banker needs to be adept at the art of selling and acting as a bridge between two companies. Actuarians are mostly technically skilled in mathematical, statistical and financial knowledge to create models to analyze and minimize risk. An actually will usually have higher pay, better work-life balance, less stress and their nature of work will be purely mathematical in nature. While the role of an investment banker requires them to work longer hours, travel more, play the role of an intermediary a la sales agent between two companies while major financial moves like meager and acquisition or find clients for huge investments in stocks and funds. This leaves little time for the investment banker to have a social life. An investment banker can acquire some of the relevant skills of an actuary to make his/her work life easier. The valuable skills which an investment banker should aim to learn from the actuarial science skill set are:
Analyse trends to predict outcome: The ability to analyze complex data and predict the outcome by identifying the trends and patterns of the input and evaluate the various factors that can influence the outcome. Examine the factors that can lead to an undesirable outcome and ways to avoid the undesirable outcome and predict the financial cost to the company should the undesirable outcome be realized.
Quick mathematical skills: Ability to quickly and correctly do arithmetic computations. A sound knowledge of probability and statistics is a must to predict the probability of an event’s occurrence, the risk it carries and various statistical models to be used in day to day investment banking
Sound understanding of financial and business concepts: They are required to evaluate pension plans, insurance plans, the stock market. They need to access the financial risk of a possible outcome and advise their clients like the business, government, banks and other financial institutions on how to avoid exposing themselves to financial risks. They are required to also provide their clients with expert advice to maximize their profits from a variety of investment options.
Computer skills: Knowing basic computer skills along with Microsoft Office is absolutely essential and ability to program in a statistical programming knowledge is a basic necessity as they have to frequently deal with huge data in tabular format and create meaningful statistical models.
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