If we look back at the past decade or so, no one would have imagined how far technology has come since then & how deeply it has impacted everyone’s lives. From the digital revolution in the loan process, the task to find credit score, track applications, compare lenders, etc., every credit process has witnessed the impact of changing technology.

And with continuous innovation in bringing technology closer to our day to day lives, the power of the internet and smartphones has grown exponentially. Unlike previous decades, borrowers today need not visit various banks’ branches to avail loans or credit cards. You can even check credit score for credit card at your fingertips itself, through websites or apps.

Technology has gradually made the financial sector, especially lending, the most interesting segment to look forward to in coming years.

Below are the three major innovations which have already landed in the Fintech sector and are being used actively by various financial institutions:

Chatbots- Financial institutions like Fintech companies, credit card issuers, banks, NBFCs etc., are increasingly improving their customer service by adopting algorithm-powered chatbots, which work as a tool to completely enhance customers’ experience online. They enable the company to save a lot of time and money, along with problem-saving ability delivered due to a combination of artificial intelligence and machine learning together. 

Chatbots not only help to find credit score but even make recommendations on the basis of your personal as well as transactional data. Therefore solutions offered by them are reliable and customizable since they are free from any human error and bias. 

Chatbots have become quite popular amongst the young population since they generally prefer digital modes to fulfil various needs and do numerous tasks online. These are always available on the lender or company’s website unless a technical glitch occurs, providing quick services along with zero waiting time. Moreover, since thousands of conversations done through chatbots are thoroughly analyzed regularly, they continuously improve their quality and solve more complex queries as each day passes.

For example- Suppose you log in to your bank’s online portal to check credit score for credit card, and a chatbot welcomes you and then reminds you regarding an upcoming credit card payment that is due in a few days. Or it may help you decode the rise or fall in your credit score and then even help you directly find credit score.

This way, the chatbot not just saved you from forgetting your credit card bill payment and thereby saved on the high interest cost you could have incurred if you had delayed your credit card payment, besides preventing any harm on your credit score too.

Therefore, chatbots are those digital assistants that have made a purchase of financial products extremely convenient and hassle-free for consumers, with personalized communication at a large scale and enhancement of consumer experience.

Image recognition- Gradually, the task of performing checks on your credit score for credit card is becoming smoother and easier. Digital transformation has even enabled customers to conveniently purchase financial products online within a few seconds and with minimal efforts required on the consumer’s part. 

Rather than filing tons of forms and other paperwork, even for little tasks such as find credit score, consumers can leverage this digital transformation and get their credit score quickly, besides getting loans and cards processed completely paperless, thereby saving time and money. What image recognition does is that a machine would fill all your personal details digitally; you just need to upload the basic information through KYC documents such as Aadhaar or PAN. The system will read and store this information, populating other fields such as name, address, DOB etc., next time automatically.

Image recognition is rapidly disrupting financial services, leading to increased convenience for consumers. Although this technology has proven to be efficient and helpful, it’s important for consumers to use technology carefully, especially regarding the apps which require access to your photos, media or location. Customers must carefully scrutinize the websites on which they are providing their details and also the brand whose technology they are using, as carelessness in this sphere can lead to frauds, data loss and scams. 

Big data analytics- Another technology that holds the potential to largely transforming the financial sector and services, especially lending and the world of credit score, is Big data analytics. From performing searches such as find credit score,  or comparing loan and credit card lenders, to regular reminders to check credit score for credit card, big data has the scope for exponential growth to further transform these financial products and services in India and will continue to enable large scale employment generation as well.

Big data analytics transforms and organizes large and complex data to identify patterns and draw conclusions. Data scientists with this technology’s skill can manipulate data queries and translate results on a large scale basis.

Risk is a major component of the lending process. Most of the lending institutions assess applicants’ repayment capacity before providing them with any form of credit. For the past decade or so, this assessment has been done by fetching a customer’s credit report, as it depicts the level of credibility based on credit history. Therefore, most borrowers with low or no credit scores were outrightly rejected. However, since the arrival of big data analytics, this scenario is gradually changing.

To access borrowers’ creditworthiness, many new lenders have begun using unconventional data points, thus breaking from the traditional ways of assessing credibility and therefore enabling the once rejected customers to fetch credit through alternate lending.

Alternate lending largely analyzes data points such as the size of your utility bills, social media activities, mobile usage patterns etc. These big data models enable new-age lenders to create a more detailed and comprehensive customer profile, therefore resulting in more accurate underwriting decisions. 

For example, today, a 25-year-old borrower, who has just started working a few months back and hasn’t taken any credit yet nor checked credit score for credit card, can be granted a loan digitally, within a few minutes through analysis of data points through big data analytics.

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