The Future of Credit Ratings in Digital Banking:
Trends and Innovations
As we progress toward a digital and data-driven world with development and innovation at the forefront, traditional methods of credit rating are also evolving.
The procedure of credit scoring, which has been an age-old tradition, is currently being revolutionized by innovative emerging technologies and cutting-edge techniques. It helps to know that artificial intelligence (AI) and machine learning simply act as catalysts for processing accurate, efficient, and transparent data analytics.
What is a credit rating? In simple language, credit rating is evaluating a money-lenders financial position to understand and assess their potential to repay the money so loaned. You see, this assessment to evaluate the debtor’s assessment is typically conducted by credit rating agencies (CRA), which consider a wide range of financial factors such as income, debt level, and payment history, and once these factors are considered, a credit rating is assigned by the agency.
The borrower may be any entity – an individual, a group, a business, an NPO, the Government, and even other countries.
What is Bank Credit Analysis and how does it work?
In the banking world, credit analysis is a rather significant process that is mandatory for any individual and customer who intends to apply for a loan.
You may have potentially found your dream car, the Skoda Slavia and you have most of the payment ready but you are falling short of a few lacs and would prefer not to ask any friends or family – instead you prefer to ask your bank, where you enjoy the privilege of being a valued customer.
You may apply for a car loan, and before being granted the application; your bank will want to evaluate your creditworthiness to check the level of risk they are putting themselves into by granting you a loan to ensure that you repay the loan within the stipulated period.
So you see, credit rating analysis and banks go hand in hand – and it is a no-brainer that high-level risk clients are a big no-no in the credit rating industry. This is because there is a high likelihood of defaulting on their loan obligations and the credit rating would be incredibly low.
On the other hand, low-risk clients are more desirable as they enjoy high creditworthiness and thus the banks approve their loan applications quite easily. Those with a higher credit rating also enjoy attractive offers like lower interest rates whereas those with a low credit rating are plain and simply unfavorable and also undesirable.
It must be noted that banks consider keeping collateral which to be provided for the loan. This should be either equivalent in value to the debt amount or, higher than the amount – thus in case of default, the bank can repossess the collateral for the damages due to the inability of the repayment. A credit analyst uses software to analyze data about the financial history of the client and this software does the needful regarding the creditworthiness reports.
As part of the protocol, banks check credit repayment history, client character, financial solvency, reputation, etc. to help determine credit risk and subsequently, the amount of credit that the client can afford without defaulting.
Credit Rating Trends and Innovations To Look Out For in 2023:
In the world of technology, innovation, fintech companies, and credit rating agencies – digital banking is emerging as one of the leading business models in the coming years. Credit rating is undergoing a phenomenal transformation as new technology, data sources are becoming available thus creating opportunities for lenders thus making way for better and more informed decisions. Here are a few credit rating trends and innovations to look out for:
AI for more transparent credit rating: In the digital era, credit rating and credit scoring use artificial intelligence and machine learning thus learning more and more. To ensure accountability and justice, banks must adopt explainable AI which will allow them to shed light on how AI assesses creditworthiness and make credit decisions. By doing so, banks ensure transparent and easy-to-understand results, thereby building consumer engagement as well.
Resilience in decision-making via high-frequency data: With digital data in the forefront, banks can improve credit rating and offer better and more accurate repayment behavior by using high-frequency data.
The Covid-19 pandemic has shown the benefits of using such data to build resilience in decision-making departments, thus allowing banks and lenders to understand their customers at a deep-rooted level, and extract more value from the existing data. For ghost consumers that have no credit history, alternative data sources may be used which has shown potential in improving their credit access.
Data analytic professionals play a broad role: With digitalization on the rise, there is an expected increase in the volume of data and change in granular data sets. This leads to a direct relationship with data analytic professionals as they need to broaden their skill sets to keep up with the new requisites. Advanced skill sets and competencies are needed to analyze and interpret data into actionable insights. In fact, D&A professionals have a more influential role in credit rating and risk management as banks rely more on data-driven decision-making.
Digital Banking and Credit Ratings: Is it a win-win?
In recent times, banking has become increasingly technology and data-driven thus getting ‘tech’ and ‘touch’ has become the ‘it’ thing of the 21st century – this is because they can deliver experiences that new generation clients expect.
With the constant advancements in big data analysis, banks get the opportunity to improve credit-based decision models that support their lending process. The fresh, new models allow banks to review and define capital lending parameters better and more intimately, thus giving banks the innate opportunity to sharpen their ability to approve low-risk customers and reject high-risk customers.
This however does not mean that banks are free from struggles and challenges as they transition to a more advanced model. They face significant issues with technology, cultural obstacles, heavy reliance on assessments from relationship managers, underwriters, outdated models etc.
Considering these factors, banks have certainly outperformed by including high-performance credit-decision models thus bringing digital lending into the limelight. These offer several benefits such as:
Increasing revenue: New credit decision models have led to a revenue increase of approximately 5-15% thanks to higher acceptance rates, lower cost of acquisition, and overall better customer experience. Differentiating between creditworthy and non-creditworthy becomes easier and by doing so, banks get to improve acceptance rates and pricing.
Reduction in rates due to credit-loss: Just as there is an increase in revenue thanks to digital banking offering credit ratings; companies have also seen a decrease of about 20 to 40% in credit losses by using new digitized models that precisely point at a customer’s likelihood to default.
Improved efficiency: The usage of new models has resulted in 20 to 40% efficiency, all thanks to a killer combination of high-automated data extraction, case prioritization, and model development. This all leads to an increased level of efficiency.
Do these points make credit ratings in digital banking a win-win situation?
You see, using a credit rating model is a powerful way to pull up profits – that’s a given. However, doing so is also considered a business-critical competitive move. Banks need to to implement more automatic credit-rating models so as to tap new data sources, understand and review customer behaviors, react efficiently to changes in the business environment, etc.
By having the ability to do all the above mentioned, banks will have the competitive advantage of being able to serve their clients better, grow the business and compete with other fintech companies and other banks that are constantly trying to up their tech-game and looking for opportunities to grab the market share.
So to answer that question, the above-mentioned points certainly make credit ratings in the digital banking world an absolute win-win situation.
