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Day: July 21, 2022

Here’s How Tech Changed The Credit Underwriting Process

Posted on by Imarticus Learning

Last Updated on 4 years ago by Imarticus Learning

Here’s How Tech Changed The Credit Underwriting Process

In this digital age, Could credit underwriting be done to produce a more accurate profile and assist urgent need gaps?

A credit rating system considered an individual’s or business’s income/revenue, current debt levels, and prior loans was the only basis for granting loans approximately a decade ago. In this case, having a solid score would increase the likelihood of getting a loan soon and at a reasonable interest rate. 

However, this paradigm ultimately neglected a substantial portion of people and companies nationwide by omitting them. Today companies are steadily succeeding at tapping into the vast data sets that have not previously been considered and mitigating risks to open the door for a clearer picture and, as a result, more immediate, accurate, and efficient underwriting by utilizing emerging technologies like Big Data and predictive analytics.

What are big data and machine learning?

Machine learning and big data are the most critical technologies in the modern IT sector. Out of massive data sets, big data warehouses evaluate and extract information. On the other hand, machine learning is the capacity to learn from experience and improve without being expressly programmed automatically.

Big Data describes a collection of massive and complicated data sets that are challenging to handle and analyze with conventional database administration and processing tools. Capturing, curating, storing, finding, sharing, transmitting, analyzing, and visualizing this data are all challenges. 

How did big data and machine learning change the credit underwriting process?

Traditional credit underwriting relies heavily on manually reviewing financial data and making subjective decisions about a borrower’s ability to repay a loan. However, with machine learning and big data, lenders can now automatically and objectively assess a borrower’s creditworthiness.

Big data refers to the complex data sets now available to lenders. Machine learning is artificial intelligence that allows computers to learn from data and improve their predictions over time. Using these technologies, lenders can now more accurately assess a borrower’s risk of default. 

Machine learning is particularly well-suited for credit underwriting because it can automatically identify patterns in data that humans would not be able to see. For example, a machine learning algorithm might locate that a borrower with a history of making late payments is more likely to default on a loan than a borrower who has always made timely payments.

Lenders can make more informed decisions about which borrowers to approve for loans, and they are also able to offer more personalized loan terms to individual borrowers. This is just the beginning – as data sets continue to grow and machine learning technology continues to evolve, the potential for further innovation in credit underwriting is vast.

Explore the credit risk analyst certification with Imarticus Learning

Students learn about the lending environment, credit underwriting, and regulatory requirements with this credit risk certification in India. 

Course Benefits For Learners

  • The practical career-focused program complies with internationally accepted standards and incorporates the most recent global trends and best practices.
  • The curriculum for credit management courses online consists of 145 hours of live lectures, five case studies, and social learning.
  • Online credit risk modeling certification is practice-based, tied to globally recognized standards, and industry-focused. It is unique because it includes the most modern educational advancements worldwide!

Contact us through the chat system, or drive to our training centers in Mumbai, Pune, Thane, Chennai, Bengaluru, Delhi, and Gurgaon.  

A 5-Step Process To Excel In Business Development

Posted on by Imarticus Learning

Last Updated on 4 years ago by Imarticus Learning

A 5-Step Process To Excel In Business Development

Business development can be defined as a set of activities and procedures designed to create and implement profitable and sustainable growth opportunities for firms. However, most businesses use the phrase differently in practice, depending on what they want to accomplish.

All businesses, irrespective of size, must prioritize business development. Today organisations are investing heavily in corporate development and training, which is the key to excelling in any business.

Business development: What is it?

Business development is the process of identifying long-term strategies to increase revenue by growing markets, clientele, and contacts. A business developer’s day-to-day activities and techniques may differ depending on the industry, but their overall goal remains the same. Some of the best corporate training programmes focus on raising self-awareness and helping business developers gain self-confidence to lead the business successfully. Additionally, many Massive Open Online Courses(MOOCs) and institutions offer courses to develop leadership skills to help leaders combat the stress and uncertainty of their roles.

Here’s a 5 step process to excel in business development:

Step 1: Setting action plans

Your business objectives should align with your firm’s needs and requirements. Think about your long-term and short-term business goals. Once you have identified what you have set out to achieve, then devise a strategy to excel in your chosen field.

If you spend time, money, and resources on business growth projects without having a strategy, it won’t help your company expand. Thus, planning must take precedence in your business development strategy.

Step 2: Building networks and relationships

A business development executive must build strategic alliances, invest in networking, and close new deals to expand the organisation. Successful business development managers know how to “read people’s minds effectively” and how to solidify cross-departmental, long-term business partnerships.

Step 3: Getting along with others

Since starting a new business entails responsibility, hence, business development executives must learn to persevere, practice patience, and carry out the relevant tasks. It also teaches you how to manage your sales leads, qualify them, develop them into mature prospects, and seal the deal.

Step 4: Boost earnings and increase profits

Business development teams frequently concentrate their efforts on increasing revenue. This may entail reaching out to new audiences and looking for cheap ways to attract more customers. While this is not the same as sales, it is comparable to the methods that aid in boosting sales.

A firm’s worth is often determined in terms of profits. While a client may appreciate a firm for various reasons, a company’s intrinsic worth is directly related to its profits.

Step 5: Be self-motivated

A competent business developer must prioritize activities and be self-motivated to accomplish their goals. They must embrace temporary setbacks with enthusiasm instead of giving up. Still, when you succeed in your initiatives and witness how much your team and business have grown, all the challenges and hard work would seem worthwhile. It can inspire you to set even greater goals to succeed and excel in business development.

Conclusion

Never forget that business development is all about identifying prudent business prospects and developing relationships. As a business development officer, you must focus on developing resilience and negotiation skills. When it comes to business development, all you must have is grit and gumption.

 Learn More About Corporate Training Programs

 

Do you know everything about financial valuation? Think again

Posted on by Imarticus Learning

Last Updated on 4 years ago by Imarticus Learning

Do you know everything about financial valuation? Think again

Financial valuation is no longer just a field for analysts and investors. It’s a fundamental part of business growth and acquisition, especially as a way for startups to raise money. This post will explain some of the critical questions on every entrepreneur’s mind regarding financial valuation — and how you can use valuation-based methods to help solve them quickly and effectively.

What is financial valuation?

When it comes to financial valuation, there is a lot to know. Valuation is the process of determining the value of an asset or company. There are many different valuation methods, and knowing which one to use can be challenging. Financial valuation is essential for investors because it helps them decide whether to buy or sell a stock. It is also crucial for companies because it can help them raise capital.

There are many different types of financial valuation. The most common method is to use earnings. Earnings are the profits that a company makes. Valuing a company based on earnings is called the earnings approach. Another standard practice is to use the book value. 

Valuing a business is no easy task – many factors to consider and no definitive way to do it. However, understanding the various valuation methods and thinking critically about the business’s value makes it possible to come up with a fair and accurate valuation.

What Does Valuation Indicate?

When attempting to ascertain the fair value of a security, defined by what a buyer is prepared to pay a seller, providing both sides join the transaction freely, a valuation might be beneficial. 

On the other hand, the idea of intrinsic value relates to a security’s perceived worth based on future profits or some other corporate quality unrelated to the market price of a security. This is where valuation comes in. Analysts perform valuations to evaluate if the market has overvalued or undervalued a firm or asset.

The different types of financial valuation

There are different types of financial valuation, each with its quirks and challenges. 

Here’s a quick rundown of the most common types of valuation:

  • Asset-based valuation. This type of valuation focuses on the value of the company’s assets, such as its property, plant, and equipment. It is significant to note that this valuation doesn’t consider the company’s liabilities.
  • Market-based valuation. This type of valuation looks at the company’s stock price and compares it to similar companies. 

 Financial valuation is an essential part of any business decision. It is a process of determining the value of a business, and there are many different valuation methods.

Discover IIM Lucknow financial services course with Imarticus Learning

Through our diploma in Financial Services and Capital Markets course, students will learn about investment banking, capital markets, risk management, and fintech. The top business school established this demanding six-month program at IIM Lucknow. Middle managers with experience who want to restart their careers in the financial services sector would find this training valuable.

Course Benefits For Learners:

  • Students can connect with their peers and business experts as part of this finance management course.
  • Students will understand critical topics, including investment banking, capital markets, risk, and fintech.
  • A Financial Valuation course teaches students all they need to know about the financial sector and its operations.

Contact us through chat support, or drive to our training centres in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. 

5 Impressive Quora Questions On Data Analytics

Posted on by Imarticus Learning

Last Updated on 4 years ago by Imarticus Learning

5 Impressive Quora Questions On Data Analytics

Data analysis is becoming a highly sought-after career path both in and outside of India. Data is an asset, as the saying goes in modern society. Every enterprise, regardless of size, heavily relies on data.

For instance, ABC is a clothing-related manufacturing business. While the business in Arunachal Pradesh was shrinking in 2020, ABC made enormous profits in West Bengal. The conclusion that was reached above rests on a solid foundation of data analysis. What actual figures pertain if West Bengal has been a prosperous market for ABC? Which products are less popular and which ones are in high demand? It’s all based on available data.

Likewise, exact amounts and figures should be presented if Arunachal Pradesh proved to be a dubious market for ABC. A data analyst’s responsibility is to compile a thorough report of the information and keep it in the database for future use.

What is Data Analytics?

Data analysis is a field that encompasses anything and everything related to data. From management to storage, a data analyst helps an organization create a voluminous database for frequent referencing. The advent of newer technologies makes this field even more exciting.  

Don’t we all know what “Big Data” implies? Large volumes of unstructured and structured data comprise “big data.” In simpler words, big data is a combination of data that varies in complexity, volume,  and mobility. Data analysts are responsible for handling and managing massive amounts of data.

5 Impressive Quora Questions On Data Analytics

People are curious about data analytics. Particularly the tech-savvy generation is relying highly on this stream as a lucrative career choice. Thus, it is no wonder that you will come across numerous queries online regarding data analytics. Some of the common questions are answered below. 

Is Data Analytics a good career choice?

The field of data analysis is constantly expanding, and new technology is being introduced on a regular basis. The data analysts’ repertoire has been expanded with new equipment and tools. Particularly since AI technologies emerged, there have been many job prospects for data analysts that promise good pay.

How can I start a career in Data Analytics?

Before you ponder about the best data analytics certification courses, let us be clear that you should focus more on the long-term outcomes. If you go through the grinding of the conventional undergraduate/ postgraduate/ diploma course on data analytics, you will be favored higher by the recruiters. Aim to join trusted institutions like Imarticus and undertake proper training. This will prepare you for the upcoming days when you may be working with leading companies like Infosys, HSBC, Standard Chartered, Deloitte, and many more.    

What are key areas of employment for a Data Analyst?

Business management,  quantitative data analysis, data management, big data data management, predictive data analysis, and business analytics are just a few of the domains where data analytics has a bright potential. One of your primary duties as a data analyst will be to turn raw data into a structured compilation of insights that a company can use to refer to. Data analysis is necessary for all industries, including sports and education. Therefore, you can enjoy seamless opportunities if you learn data analytics from an esteemed institution. 

How Data Analytics is the future of IT?

Data analysis offers you chances you could never have imagined. One of the most pervasive myths regarding data analysis is that it is considered to be the new big thing. Data analysis is already here, not just in the future. Since the 1990s, when the value of data analytics in organizations was discovered, a large number of companies have benefited greatly from it. Data analytics is the most scientific method of business analysis, and decisions for the company’s profit can be made based on the technical research of a data analyst.  

Is there any scope for Data Analysts outside India?

Data analysis is now a popular career option both in and out of India. As the saying goes, data is a valuable treasure. Each business, no matter how big or small needs data. Western countries depend highly on the mechanical interpretation of data and thus a thorough analysis is an integral part of their life. You will often hear about mass recruitment happening in India where international MNCs and enterprises are hiring competent data analysts with handsome salaries. 

Best Data Analytics Certification Course

Imarticus is among the leading institutions that offer the best data analytics certification course. You will incur in-depth knowledge from the veteran tutors. Special care will be taken to make you absolutely job-ready. Complete a postgraduate program in data analytics today and become a highly sought-after professional tomorrow.  

Data Analytics Online Training

It is no secret that data drives today’s commercial sector. You can learn everything there is to know about Data Management, Data Integration, Governance, and Data Quality Control with data analytics online training. 

The top analysts in the country work in a specialized area of data analytics called data visualization. If you want to have a safe and wealthy future, learn data analytics today. It will help you grab the greatest career opportunities as a data analyst. 

Data science and machine learning professionals are career optimistic – The statistics show why.

Posted on by Imarticus Learning

Last Updated on 4 years ago by Imarticus Learning

Data science and machine learning professionals are career optimistic – The statistics show why.

Advanced technologies like artificial intelligence and machine learning have grown rapidly in recent years. They are expected to grow further in the upcoming years at the same lightning speed.

As per a forecast, the artificial intelligence market is expected to grow at a Compounded Annual Growth Rate (CAGR) of thirty-eight percent from 2022 to 2030. The adoption of artificial intelligence and machine learning can be seen across various sectors like healthcare, finance, automobile, and finance, to mention a few.

This will give rise to the demand for data science and machine learning professionals in various job roles across these sectors. Individuals having the skills and expertise in artificial intelligence and machine learning will be recruited from the junior-most to the senior-most levels on a large scale.

Job Roles Available for Data Science and Machine Learning Professionals

As stated earlier, there is a myriad of job roles available for data science and machine learning professionals in various industries. Some of the job roles include:

  • Machine Learning Engineer
  • Business Intelligence Developer
  • Software Developer
  • Natural Language Processing (NLP) scientist
  • Computational Linguist
  • Data Scientist
  • Data Engineer
  • Marketing Analyst
  • Business IT Analyst
  • Data Architect

Why Data Science and Machine Learning Professionals Are Optimistic

We are living in a world of big data. The amount of data produced is increasing with each passing day. It is estimated that the volume of global data will reach 180 zettabytes by 2025. There will be a huge demand for professionals who can handle, manage, and convert this huge volume of data to derive actionable insights that can help businesses enhance and expand their operations.

As per a report, there were over one lakh job opportunities in the data science domain in India in June 2021. Data science jobs witnessed a forty-seven percent increase in requirements in 2021 compared to 2020. This is despite the COVID-19 scenario.

Another report has monitored the continuous rise of artificial intelligence and machine learning. It found out that data science jobs have witnessed a tremendous six hundred and fifty percent growth since 2012. The rise is set to continue in future years. It is estimated that the growth of data science will create more than eleven million job openings in the field by 2026.

These trends, therefore, indicate that now is an opportune time to start a career in data science. Thus, you will be required to acquire the requisite knowledge, expertise, and skills in artificial intelligence and machine learning domains.

Benefits of Choosing a Career in Data Science and Machine Learning

So, why choose data science as a career option? Let’s look at some of the major benefits of being a data science and machine learning professional.

  • Ever-Increasing Demand

As stated earlier, the demand for data science, artificial intelligence, and machine learning professionals is only expected to increase further in the future. Thus, there will be no shortage of jobs in this field.

  • High Salaries

Data science and machine learning professionals earn handsomely, irrespective of their job position, experience, and organisation. Some of the average annual salaries in different job roles are discussed below.

Thus, we can see that data science and machine learning professionals are some of the best-paid individuals. In addition to such fat packages, they are also entitled to bonuses, incentives, paid vacations, stock options, and other perks, depending upon the organisation.

  • Versatile Field

Professionals can find job opportunities in various sectors like manufacturing, retail, eCommerce, and healthcare. They can also switch easily from one field to another if they want to explore other domains. Thus, unlike most other career paths, data science and machine learning professionals aren’t tied to one particular field.

Skills Required for Data Science and Machine Learning Professionals

To be successful, professionals need to possess certain skills that can help them excel in their work and enable them to climb the professional ladder quickly. Some of the skills include:

  • Problem-solving intuition
  • Analytical and critical thinking
  • Business sense
  • Communication
  • Mathematics and statistics
  • Programming
  • Management
  • Leadership
  • Cloud computing
  • Data visualisation
  • Calculus
  • Data wrangling
  • Machine learning
  • Deep learning
  •  DevOps
  • Business Intelligence tools

To acquire these skills, you will need to complete a certification course in artificial intelligence and machine learning. You can opt for such courses after completing your bachelor’s or master’s certification.

While there are tons of courses out there, we recommend you check out Certification in Artificial Intelligence and Machine Learning offered by E&ICT academy, IIT Guwahati. Some of the program highlights include:

  • Industry-approved curriculum
  • Real industry projects
  • Certification by IIT Guwahati
  • Live online training

The 9-month course will impart the foundational skills that can prepare you for diverse roles in the data science and machine learning domain. Individuals have landed lucrative job roles in top companies like Accenture, Wipro, HSBC, and Oracle, to name a few.

Want to learn Machine Learning IIT AI Course? Feel free to contact our chat support. Alternatively, you can also visit our training centers in Mumbai, Thane, Pune, Chennai, Bengaluru, Delhi, and Gurgaon. We would be more than happy to serve you.

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