Indian banks are struggling with the aftermath of bad loans and NPAs they have faced in the recent past. Following the series of deteriorating trends, the banking stability indicator worsened further due to the global economic uncertainty in 2020. Gross non-performing assets (NPAs) of Indian banks are all set to worsen to 11.3-11.6 per cent from 8.6% in March 2020 by the end of this financial year, due to disruptions caused by the coronavirus pandemic.
Estimates suggest that an increase in stress on asset quality and profitability banks may need Rs 45,000-82,500 crore of capital under a weak credit growth scenario. Moreover, the lockdown has impacted the debt-servicing ability of Indian borrowers. In the end, the extent and speed of revival in economic activities following restriction uplifting will dictate the impact on the asset quality of banks.
The overall surge in the number of fraudulent activities in the banking sector and the corresponding number of NPAs has led RBI to develop the concept of Early Warning Signals. The objective of the Early Warning Signal framework is to facilitate timely reporting to ensure that the banking operations and their risk-taking ability are not impacted.
What is an Early Warning System a.k.a. EWS?
As it is, banks are looking for a more stringent credit monitoring program and stronger risk management controls. Early warning systems can optimally replace legacy lending procedures by keeping biased lending decisions at bay. Using advanced technologies like Artificial Intelligence and Machine Learning, they can detect red flags, allowing lending institutions to gain control over their decision making. Relying on multiple sources of data, early warning systems measure and monitor risks efficiently.
Early Warning Systems (EWS) can help safeguard a loan origination process in the following ways:
1. Assist Loan Disbursement Decisions
Lending management frameworks with early warning systems integrate third parties sources like CIBIL to ascertain a borrower’s financial stability, repayment behaviour and willingness to pay back, etc. It presents a clear picture for the lender who otherwise struggles to decide if they should sanction the loan or deny it.
2. Minimise the Chances of Borrower Default
Early warning systems can help lenders scrutinize a customer portfolio regularly, to ascertain that all EMIs and instalments are paid in a timely fashion minimizing delinquencies. Modern lending management software accesses individual custom profiles at the very beginning, and if they suspect any early warning signals while scanning the loan portfolios of such customers, they place them under ‘watchlists’ and keep a strict check on their repayment behaviour.
3. Saves the Lender from Exposure to Defaulting Borrowers
Early warning systems in loan management software monitor different types of lending profiles, borrowers and their overall portfolios. This gives it access to the most risk-prone segments and helps them guide the loan decision making officer to steer clear of high-risk borrowers by presenting substantial proof.
How to Build an Early Warning System?
Building a comprehensive early-warning system to help lenders lower their risk is crucial to the health of all lending businesses. Here is a brief guide on how to make an early warning system:
Credit Assessment Tools
Begin with creating a system of well-synchronised credit assessment tools that use data from a variety of sources, robust quantitative models and state of the art online workflow solutions. Such a system in place exposes lenders to multiple markets based and fundamental indicators that highlight the possibilities of potential defaults. Innovative online workflow solutions allow risk assessment teams to set alerts and use customizable dashboards to build an early warning mechanism for potential credit risks.
Finezza is a robust lending management software that offers innovative features like Bank Statement Analysis (BSA) that analyses the deep topical domain for complete credit evaluation.
Regularly Updated Private Company Database
Once you have a system of Early Warning Solution in place, you need to feed it with accurate data. This data comes from multiple quantitative and qualitative sources which could be internal or external in nature. The internal data is an accumulation of borrower’s history and profile. There is also a need for regular updation of these data to stay ahead of the game.
Taking into account transaction history and data of a borrower, Finezza is an early warning system that creates multiple visualisations and insightful reports for the benefit of the lender’s credit evaluation process.
Timely News and Research
External sources of borrowers’ data are also vital and can be sourced from the customer’s online activities, browsing histories, online spending patterns, data from external aggregators, etc. With the help of timely news and research, lenders can develop a better understanding of the drivers of risk and financial realities that matter the most to their business. To develop an early warning system that diminishes the risk for lenders, there is also a need to leverage third-party research from buying and sell-side analysts.
Lenders can also use macroeconomic data to determine external factors that could affect their operations in order to develop an early warning system. The state-of-the-art lending management software red flags fraudulent statements, circular transactions, irregular payment patterns, transactions, and other such discrepancies to significantly reduce NPAs for lenders.
Lenders do well with ongoing support to help them explain and demonstrate their capabilities, which leads the risk assessment team to enhance efficiencies and leverage the solution to optimal capacity. Finezza empowers distressed lending companies with advanced risk analytic capabilities and helps them reap the benefits of a practical assessment of loan applications.
How to Fortify Early Warning Systems?
There are multiple aspects of early warning systems that need to work seamlessly for the lending management solution to be capable enough. No doubt, early warning systems are innovative tools when it comes to better decision making and loan portfolio management.
Here are some steps that need to be taken to fortify the systems:
- Strong collaboration between banking processes, technologies being leveraged and loan assessment officers.
- Work out an in-depth and accurate data repository after a strict data selection process
- Pre-integrated efficient data corroboration mechanisms
- Sketch risk profiles based on the borrower’s profile
- Deal with frauds and credit risk in a transparent manner
To Sum Up
Most early warning systems in the market today are based on advanced risk analytics. They allow modern financial lending firms to restructure their operating principles to meet current investment trends strategically. The use of analytical data along with various other useful resources and programs helps better analysis of the risk that lending firms face. All lending institutions must leverage a competitive edge through analytics backed early warning systems to improve their client satisfaction as well as remain profitable.
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