Introduction to Banking, Financial Services, and Insurance

The BFSI  industry is witnessing a major 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 of employment. 

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 in India, Banking and Financial services need 1.6 million skilled workforces 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 major 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 is influencing the financial industry and how it can help secure your career. Let us discuss data science in banking, finance, services, and Insurance sector.

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

Indian Banks are also facing lots of stress due to several types of debt. In July 2021, SBI indicated highly increased stress from holding debt (due to the COVID-19 outbreak). In 2019-20, the Indian government opted for 10 public sector bank amalgamation to lower the number to 4. The reason behind this was to lower the debt risk and better financial operation. But, the situation is going in such a way that it might be possible, for private banks also face a similar amalgamation- this may lead to severe layoffs.

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

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

A lot of 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 do data processing or test software applications or write software for this kind of business. This is because people have more money, the banking, financial services, and insurance (BFSI) industry in India are expected to develop dramatically. In the last 15 years, the BFSI sector has undergone a lot of changes, and it will be a big part of India’s economic development based on inclusive growth. 

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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.
• When it comes to these kinds of computer systems, RSM is well-equipped to offer a wide range of services. This is why the business world now sees IT as an important part of its strategy.
• People who have a lot of rules and regulations will need to be aware all the time and use a lot of risk-reduction strategies all of the time.

Data Science in Banking, Finance, Services & Insurance Sector

People have strived to handle money effectively since the invention of money. Temples were used as banks by the ancient Greeks and Romans. This was partly due to the temples’ ability to keep people’s hard-earned money secure. Money storage became insufficient after a while. Banks were expected to provide more to their customers. As a result, the financial business has grown significantly. The financial business began to expand in leaps and bounds. 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 smarter than they thought. These people, too, wanted to beat the banks and other financial institutions at every turn. In order to stop the money from leaving, banks used historical data analysis to look for common trends from the past. This way, they could stop the money from going out of the door. This was most 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, this 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 out there now. 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.

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

In the banking industry, data science is being used in a variety of ways.

• Fraud detection: 

Because fraud can happen in a lot of different places, it’s important to find and stop it with the help of data science. A bank needs to be able to spot fraud before it happens, which is very important for the safety of both 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 a variety of fraud detection methods, they can get the protection they need and avoid a lot of money being lost. People do this for things like getting data samples for a model estimate and testing, as well as for things like model estimation.

• Lifetime value prediction:

Client lifetime value (CLV) is a prediction of 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, which helps the company make even more money and grow even faster than before. Banks are having a hard time getting and keeping customers who are worth their while. In order to spend money wisely, banks must now have a 360-degree view of each customer. This is because the competition is getting tougher. In this case, the data science field comes into play. Data about how many customers are added and how long they stay must be looked at first. Banking products and services that people use, how much money they make and where it comes from, and how many customers come from certain 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. It’s important for data scientists to know how much each customer group is worth. Some of the tools they use to figure this out include clustering, decision trees, logistic regression, and more. These tools help them figure out which groups have the most and least 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 for each group customers. 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 quickly make smart decisions based on the most up-to-date data because they can do this right away. People who trade this way look at both traditional and non-traditional data when they make their trades. Good at this kind of work needs to be able to quickly look at this data because it’s only useful for a short time. When real-time and predictive analytics are used together 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 do data science now have tools that can help speed up and improve getting data.

• Robo-advisory: 

A lot of people in the world of finance are using 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 the age of 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 unique insurance policies for each customer. It’s cheaper to hire a robot financial adviser because they can give personalized and calibrated advice that’s tailored to each person’s needs.

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In the insurance industry, data science is being used in a variety of ways.

• Underwriting and credit scoring:

The Top Data science field is good at things like underwriting and credit scoring, which happen a lot in finance and insurance. There are tones of consumer profiles that data scientists use to train their models. Each one has a lot 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 the aid of 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, behavior, attitude, lifestyle information, interests, hobbies, and other things to make insurance more personalized and relevant for each person. This makes insurance more personalized and relevant for each person.

Banking, Finance, Services & Insurance Domain Modules

BFSI will assist you:

• 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.

What is the Data Science team’s role in the banking business?

The people who work in data science are very important. They can gather, summarize, and predict fraudulent activity in customer databases, which makes them very important people. Before data science and big data, it was impossible to look at customer records and come up with reliable data. Artificial intelligence (AI) and machine learning may assist banks in combating fraud.

Is Data science beneficial to finance?

People in the finance industry use data science a lot 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. Businesses 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 of the 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 modeling are all important things to keep an eye out for.

Benefits of DS in Banking, Finance, Services & Insurance Domain

The most important benefits that data science certifications have had for the BFSI business as a whole should be talked about. These small changes have had a big impact on people’s lives, especially how they work.

• 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 by using predictive models.

• Automating tasks: 

Making tasks easier for financial services analysts, managers, and their coworkers to do makes them more productive and makes it easier for them to do their jobs. Online apps and algorithms make it much easier to figure out whether or not a customer is a financial drain. People who work at a bank can quickly figure out if they should give that personal service or not. A lot of people also like that they don’t have to go into a bank anymore to apply for things and services. Also, they may be able to fill out most of their applications online at home if their browser is set up to remember things like their address, phone number, and name when they come back to it. The more automation makes it easier for people to interact with businesses, the more happy people will be with it. Their productivity also goes up.

• Assessing risk: 

Using a person’s credit score and financial activities, It is very easy for data science algorithms to figure out 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.

• Fostering inclusivity: 

There can’t be any 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 whole 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. This is because it doesn’t allow for that.

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.

Scope of Banking, Financial Services, and Insurance in India

NSDC did a study and found that India is one of the few countries that have 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: These are digitization and the digitalization of things, and they are both very important. Learn about and test new technologies and business processes that could make 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 real 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:

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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 important to the company: fixed deposits and rural loans. Value-added services are also important.

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. The company sells power and electrical equipment, as well as ships and heavy equipment. You can buy these things from the company. Also, people can buy other things from them.

Aditya Birla Finance Ltd.: There are a lot of different things it can help with. It can help with commercial mortgages, corporate finance, and more.

There are more and more of these businesses in the BFSI industry. If you want to work in the banking or financial sector, you need to 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 a variety of incentives, such as a 7-30% share of revenue, based on the work level completed.

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Banking, Finance, Services, and Insurance Course:

You should enroll at Learnbay institute, if you want to pursue a profession in the Banking, Finance, and Service Insurance area. It gives you a certificate that is recognized around the world. This will help you get more attention and make you stand out from the rest of the people. You’ll also be able to get live interactive sessions so that you can ask questions. Learnbay’s BFSI course includes Project Life Cycle Expertise, as well as two capstone projects and the opportunity to work on real-world projects. By visiting the Learnbay institute, you can learn more about the domain. Learnbay provides one of the greatest data science courses in Bangalore, and I definitely suggest it.

Prerequisites for BFSI:

Course Professionals with 1+ years of expertise in the BFSI area are required. Non-BFSI professionals who want to learn about the most up-to-date technology, data science, artificial intelligence, data analyst, and business analyst methodologies that drive strategic development can learn through Learnbay’s Facebook, Youtube, Linkedin, Twitter handles.

• Bibliography:

https://360digitmg.com/applications-of-data-science-in-finance-and-insurance

https://activewizards.com/blog/top-9-data-science-use-cases-in-banking/

https://www.investopedia.com/ask/answers/030315/what-financial-services-sector.asp

https://financialservices.gov.in/insurance-divisions/List-of-Insurance-Companies

https://www.payscale.com/research/IN/Industry=Insurance_and_Financial_Services/Salary