Banking, Finance, Services & Insurance Sector Know How to Achieve The Most Lucrative Salary Package

By Learnbay Category Hot Topics Reading time 20-25 mins Published on Apr 7, 2022

Find out how useful the BFSI Sector is for you.

Introduction to Banking Financial Services and Insurance

The BFSI industry is witnessing a significant transformation in the Indian economy, fueled by new FinTech competition, shifting business models, compliance demands, customer experience enhancement, and innovative technologies.

However, in 2020, this scenario changed due to an unprecedented event that shook the entire world; the BFSI sector was heavily hit like any other industry resulting in layoffs and halting employment.

An illustration shows four bankers standing, lifting their hands, and carrying coins, calculators, rupees, and an insight symbol.

Nevertheless, as the lockdown has been lifted and the world learned to live with this normalcy, the hiring trends in the BFSI sector are beginning to shine again.

A report by the National skill development corporation (NSDC) reveals that banking and financial services need 1.6 million skilled workforces in India by 2022.

Therefore, this can be the right time for you to get back on track and secure your career.

But what can be the best option for you?

Data Science.

In today's world, Data science plays a significant role in the BFSI sector. They help in analyzing data to improve the overall customer experience.

Data science and AI can be the finest option to land a high-paying job in the BFSI sector.

Throughout this blog, you'll get an idea of how data science influences the financial industry and how it can help secure your career. Let us discuss Data Science in BFSI (banking, finance, services, and insurance).


Financial Services are under high competition now. Even entrepreneurs are targeting this industry. According to the Goldman Sachs insight, more than 4.7 trillion dollars in revenue might be directed to startups from traditional financial MNCs (Source: Global Hitachi). The massive changes in regulatory compliance (such as the Dodd-Frank Act and ALLL of the US ) make it harder for the banking business to maintain profit. However, this is not the end. The applications of Robo-advisory and algorithmic trading are making the competition harder day by day.


Indian Banks are also facing lot of stress due to several types of debt. In Jul 2021, SBI indicated highly increased pressure from holding debt (due to the COVID-19 outbreak). In 2019-20, the Indian government opted for ten public sector bank amalgamation to lower the number to 4. This was to reduce the debt risk and better financial operation. But, the situation is going so that it might be possible for private banks to face a similar amalgamation, which may lead to severe layoffs.


Until now, whatever disasters financial companies have faced, everything got saved by the proper implementation of data analytics and AI innovation. J.P. Morgan, Accenture, and Goldman Sachs are lightning examples of such cases.

But the risk of layoffs in the BFSI sector can be easily overcome by adapting the DS and AI skills. The industry is in massive need of such talents.


Many people who work for IT companies, BPO companies, or technical and professional service businesses use this word. It stands for "Banking, Financial Services, and Insurance." They make data processing, test software applications, or write software for this business. This is because people have more money, and India's banking, financial services, and insurance (BFSI) industry are expected to develop dramatically.

In the last 15 years, the BFSI sector has undergone many changes, and it will be a big part of India's economic development based on inclusive growth.

An illustration shows four bankers standing, lifting their hands, and carrying coins, calculators, rupees, and an insight symbol.

Possibilities and Challenges:-

  • The BFSI business is expected to grow a lot in the future as India's economy grows and people become more aware of financial goods and services.
  • New and broader items will provide a plethora of options for specialized development.
  • Regarding these computer systems, RSM is well-equipped to offer a wide range of services. This is why the business world now sees IT as an essential part of its strategy.
  • People with many rules and regulations will need to be aware of all the time and use a lot of risk-reduction strategies all of the time.

Data Science in Banking Finance Services & Insurance Sector

The banking and insurance industry has changed from being a business that cares about people to one that cares about big profits. The financial industry's watchwords quickly became revenue and profit. They found that their customers were more innovative than they thought. These people, too, wanted to beat the banks and other financial institutions at every turn.

To stop the money from leaving, banks used historical data analysis to look for common trends from the past. This way, they could prevent the money from going out of the door. This was likely the start of data science. This project quickly evolved into a potential source of employment.

Data science is a nebulous subset of computer science that has piqued the interest of many experts seeking new prospects. Finance is a manifestation of data at several levels in and of itself. Only that is financial data, which is critical for financial firms.

History shows that data science was used before it became a separate field of computer science, as shown in the short history above. Decisions are being made based on data because there is so much information.

To make things even faster for banks and other financial institutions, they can now quickly look at a lot of customer data like their personal and security information a lot more quickly.

An image titled 'APPLICATION OF DATA SCIENCE IN FINANCE AND INSURANCE DOMAIN'  shows a human mannequin at the center.

Source: By the Author

How did data science help the Banking Financial Services and Insurance businesses handle problems?

In the banking industry, data science is used in various ways.

Fraud detection:-

Because fraud can happen in many different places, it's crucial to find and stop it with the help of data science. A bank needs to spot a scam before it happens, which is very important for the safety of its customers and employees. The sooner a bank finds out about fraud, the sooner it can stop account activity and cut down on losses.

When banks use various fraud detection methods, they can get the protection they need and avoid losing a lot of money. People do this for things like getting data samples for a model estimate and testing and for things like model estimation.

Lifetime value prediction:-

Client lifetime value (CLV) predicts how much value a company will get from a customer over time. This is because these numbers help build and keep good relationships with specific clients, allowing the company to make even more money and grow faster than before.

Unfortunately, banks have difficulty getting and keeping customers who are worth their while. Banks must now have a 360-degree view of each customer to spend money wisely. This is because the competition is getting tougher. In this case, the data science field comes into play.

First, data about how many customers are added and how long they stay must be looked at. Banking products and services that people use, how much money they make and where it comes from, and how many customers come from particular places all play a role in how people use banking services.

Customer segmentation:-

Segmenting people into groups based on how they act or look is called customer segmentation. Data scientists need to know how much each customer group is worth. Some tools they use to figure this out include clustering, decision trees, logistic regression, and more. These tools help them determine which groups have the most negligible value.

Making groups of customers makes it easier to allocate marketing resources and make the point-based approach, as well as selling chances for each group of customers, the best they can be. No one needs to see this. Remember that customer segmentation is intended to enhance customer service and aid in customer loyalty and retention, which is critical in the banking industry.

Data Science Applications in the Financial Services Industry:-

Algorithmic trading:-

An algorithm helps financial companies make intelligent decisions based on the most up-to-date data because they can do this immediately. People who trade this way look at traditional and non-traditional data when making their trades. This kind of work needs professionals to be able to quickly look at this data because it's only valid for a short time. When real-time and predictive analytics are used in this field, there is a new way to look at things.

There used to be a lot of mathematicians who worked for financial companies, but that has changed. To make trading algorithms that could predict what would happen in the market, they made statistical models and used data that had already been collected. People who practice data science now have tools that can help speed up and improve getting data.


Many people in the world of finance use Robo-advisors all the time. In the app, people can write down how much money they have and what they want to do with their money.

For example, they can write down how much they want to save by 50. A robot adviser is then used to put the person's current assets into different investment options based on their risk preferences and what they want to do with the money.

Insurance is something that people buy online from a lot of companies that use robots to help them make individual insurance policies for each customer. Hiring a robot financial adviser is cheaper because they can give personalized and calibrated advice tailored to each person's needs.

An AI-powered robot for advising customers on different financial and other investents policies.

Source: By the Author

In the insurance industry, data science is used in various ways.

Underwriting and credit scoring:-

The Top Data science field is good at underwriting and credit scoring, which happens significantly in finance and insurance. There are tons of consumer profiles that data scientists use to train their models. Each one has lots of data points. In real life, a well-trained algorithm can do the same job as an underwriter and credit scorer. Human workers may work considerably quicker and more precisely with such scoring algorithms.

Insurance for automobiles:-

Wireless "telematics" devices could be used to send real-time driving data to an insurance company. Imagine a room full of car insurance agents drooling over their desks. Progressive introduced telematics-based insurance in 1998, and it has been around since then. But, in the intervening years, technology has advanced significantly.

Personalized marketing:-

Personalized marketing is not an anomaly in the insurance sector. Insurers must ensure a digital connection with their clients to satisfy these needs. Data science jobs and advanced analytics use a lot of demographic data, preferences, interactions, behaviour, attitude, lifestyle information, interests, hobbies, and other things to make insurance more personalized and relevant for each person. This makes insurance more personalized and appropriate for each person.

Banking Finance Services & Insurance Domain Modules

BFSI will assist you with the following:

* Learn how to use modern tools and technology, as well as established methods, to win in an increasingly competitive industry.

* Master data analysis and design a dynamic dashboard to summarize your findings.

* A better leader can learn more about data and make smarter decisions about who to target, what to sell, and what to do in the market. This can help both you and your team.

The people who work in data science are critical. They can gather, summarize, and predict fraudulent activity in customer databases, which makes them vital people—before data science and big data, looking at customer records and developing reliable data was impossible. In addition, artificial intelligence (AI) and Machine Learning may assist banks in combating fraud.

Is Data science beneficial to finance?

People in the finance industry often use data science to manage risks and make decisions. This is called "data science." In the end, businesses that deal with money make more money when people do more research. So companies also use business intelligence tools to look at data trends.

What are the Modules for Banking Financial Services and Insurance training?

  1. Data Science in Banking, Finance, Services and Insurance Sector is introduced.
  2. Institutions of Finance and the Services They Provide
  3. How can financial institutions create profits?
  4. Customer data management, customer segmentation, and real-time and predictive analytics are just a few services that can be used to improve your business.
  5. Security, Process Automation
  6. For investment banks, fraud detection, underwriting and credit rating, and risk modelling are all essential things to keep an eye out for.

Benefits of DS in Banking Finance Services & Insurance Domain

The essential benefits data science certifications have had for the BFSI business should be discussed. These small changes have significantly impacted people's lives, primarily how they work.

1. Financial trend forecasting:-

When businesses want to make good decisions about their goods and services, they need to know how much demand there will be for them and how much supply there will be. This is called forecasting. It also helps them tell their customers how to make smart financial decisions using predictive models.

2. Automating tasks:-

Making tasks easier for financial services analysts, managers, and their coworkers make them more productive and make it easier for them to do their jobs. For example, online apps and algorithms make it much easier to determine whether a customer is a financial drain. People working at a bank can quickly figure out if they should give that personal service.

Many people also like not having to go into a bank anymore to apply for things and services. Also, they can fill out most of their applications online at home if their browser is set up to remember their address, phone number, and name when they return to it. The more automation makes it easier for people to interact with businesses, the happier people will be with it. Their productivity also goes up.

3. Assessing risk:-

Using a person's credit score and financial activities, It is effortless for data science algorithms to determine if a person or group is a bad investment. This will determine whether or not this person or company can get a loan or if they should be turned down because of their bad credit history.

4. Fostering inclusivity:-

There are no exceptions to this rule when financial companies use algorithms. They must treat everyone the same no matter what their ethnicity or sexual orientation is. This is because the decision-making process is based on what the customer does with their money. As a result, customers will be able to see more clearly how they can get the things they want. There is also no discrimination, which could happen in more subjective applications. But, again, this is because it doesn't allow for that.

5. Banking Finance Services and Insurance Capstone Projects

  • Prediction of Loan Default.
  • Fraudulent credit card transactions should be identified.
  • Prediction of Claims.
  • Estimating Insurance Premiums.
  • Risk Analysis in the Financial Industry.
  • Algorithmic Trading.

6. Scope of Banking Financial Services and Insurance in India

NSDC did a study and found that India is one of the few countries with a strong foundation for high productivity and global integration in recent years. It's important to note that two main things are at play during the digital transformation of the BFSI: Digitization and the digitalization of things, and they are both critical. Learn about and test new technologies and business processes that could do your BFSI service better with these new tools, like:

* Partnerships between payment banks and fintech firms.

* Artificial Intelligence and Cognitive Analytics

* Blockchain.

* Automation of Robotic Processes.

* Cybersecurity is an important topic.

Even though digitization promises more security and cost savings, its value comes from giving people what they want. However, with the introduction of new fields like services and insurance in India and business consulting, banking has become one of the most popular jobs in India. It's a big problem for the industry because the Indian government is building new offices to bring banking to more rural areas. It is also seen as a socially acceptable and stable occupation.

Companies in the banking finance services and insurance sectors in India in 2021:-

An chart shows the package offered by BFSI companies for data scientists such as:-

Bajaj Finance Ltd:-

It focuses on consumer loans, small- and medium-sized business loans, and commercial loans, as well as many other types of loans. Several things are essential to the company: fixed deposits and rural loans. In addition, value-added services are also necessary.

Muthoot Finance Ltd:-

Finance and making electricity are two parts of Muthoot Finance. When it doesn't have formal credit for a long time, it gives out personal and business loans to people who need short-term cash.

Tata Capital Financial Services ltd:-

If you want to buy something for yourself, your business, or the city itself, there are a lot of financial services that can help you. They come from here all the time. A lot of different things it does: managing wealth, home loans, and infrastructure management are just a few of them.

L & T Finance Holdings Ltd:-

As you can see, there are many different businesses that it does, such as information technology and financial services. They also build and make products, and so on. For example, the company sells power and electrical equipment and ships and heavy equipment. You can buy these things from the company. Also, people can buy other stuff from them.

Aditya Birla Finance Ltd.:-

It can help with many different things. It can help with commercial mortgages, corporate finance, and more.

There are more and more of these businesses in the BFSI industry. To work in the banking or financial sector, you must learn about Data Science. There has been a huge rise in the amount of data that needs to be analyzed and used in this field.

Banking Finance Services and Insurance job positions:-

  • Agents in the insurance industry.
  • Sales representative for banks and financial products.
  • Sales representative for equity products.
  • Representatives of investment firms.
  • Stockbrokers.

Required abilities:

In this field, there are a lot of different skills that are needed to get a job. Some of the most common are sales skills, math skills, knowledge of the stock market and mutual funds, and knowledge of how banks work.

Salary/Remuneration Package in Banking, Finance, Services, and Insurance

Those with one year or more of experience can expect to earn 4,62,321 per year. A seasoned expert may also receive various incentives, such as a 7-30% share of revenue, based on the work level completed.

This bar graph represents the respective roles' minimum and maximum annual salary.

Source: CollegeDunia


Professionals with more than one years of expertise in the BFSI area are required in the workplace. The BFSI sector has immense potential for newcomers and working professionals will benefit through this education. Therefore, a thorough study is essential to achieve your dream of a data science career in BFSI industries.

Non-BFSI professionals who want to learn about the most up-to-date technology, data science, artificial intelligence, data analysis, and business analyst methodologies that drive strategic development can learn through Learnbay's Facebook, Youtube, Linkedin, Twitter.