What are non-performing loans and why are they called so? Why have I been reported as having a non-performing loan? As a lender do the number of non-performing loans need to be reduced and how do we mitigate against non-performing loans? How can my institution use data analytics to reduce non-performing loans? These are questions that have plagued the minds of not only consumers who have their loans classified as such but also lenders and credit granters who have the responsibility of monitoring the portfolio of their organizations.
What is a non-performing loan?
When a loan is taken by a consumer or corporate entity and the scheduled payments are missed for a period of time, usually 90 days or 180 days, it is reported both in the institution’s books and to a credit bureau as non-performing. It is important to note that the timeline associated with a loan being reported as non-performing is based on the sector of the economy the lender is from. Therefore different lenders may have different timelines for reporting a loan as non-performing and as such customers will need to understand the terms and conditions and abide by them. For commercial Banks a customer is said to be in default once repayments are overdue by 90days or more. The time from default to classification as a non-performing loan may also be determined by government rules and policies.
For a borrower, either consumer or corporate, being classified and reported as having a non-performing loan is grave as it not only affects your credit score negatively, reduces your chances of getting other loans, postpaid services and possibly employment, it also may affect your chances of getting lower interest rates.
For lenders, the level of non-performing loans should always be kept to the barest minimum. This is largely due to the loss of funds which may negatively impact the lender’s books, profit and loss accounts, etc arising from loss of revenue and inability to pay operating costs. The lender also may experience a reduced ability to serve other loan customers as the funds given out are yet to return.
Attracting investors may also become extremely difficult as investors always want to see “healthy” books of companies, as potential investors always look at the profitability and liquidity position of the companies they are investing in. A large number of non-performing loans may even affect stock prices for lenders who are publicly listed on the Stock Exchange.
There are several other possible outcomes for example the lender selling the non-performing loans. Therefore it remains very important for lenders to take adequate measures to keep the level of non-performing loans to the minimum.
Thankfully, with CRC’s Risk Calculator, lenders and credit granters can now keep non-performing loans at the minimum and increase profitability.
What is the CRC Risk Calculator?
The CRC Risk Calculator assists financial institutions/lenders reduce non-
performing loans by helping them enhance their risk management system. This service uses industry wide customer historic data from all sources in our repository to build an AI (Artificial Intelligence) model that predicts how risky a customer is. The CRC Risk Calculator can assist lenders to:
- prevent financial losses that could arise from non-performing loans.
- have a better understanding of their customer behavior and help them structure their loan requests accordingly.
- Arm the marketing team to prioritize which customer to try to convert again i.e. it helps the marketing team engage in targeted-marketing for effective sales management.
- develop risk-based pricing and new products based on the institution’s acceptable risk levels.
- understand the level of provisioning needed to be made during the financial year.
- increase or reduce credit lines based on the acceptable risk levels.
The algorithm uses a risk scale to classify loan applicants as:
- Low Risk Customer
- Medium Risk Customer
- High Risk Customer
For categorizing a customer as Low Risk, Medium Risk and High Risk, the parameters considered are customer's identity, social/financial status, nature of business activity, mode of payments, volume of turnover, information about the clients' business and their location etc. While considering the customer's identity, the ability to confirm identity documents through online or other services offered by issuing authorities may also be factored in.
Low Risk Customers
Individuals (other than High Net worth) and entities whose identities and sources of income can be easily identified and transactions in whose accounts by and large conform to the known profile may be categorised as Low Risk customers. These include:
- Salaried employees
- People belonging to lower economic strata of the society
- Government departments
- Government owned companies
- Regulatory and Statutory bodies, etc.
For the above category, the KYC requirements of proper identification and verification of proof of address would suffice. Bank of Maharashtra. (Sept 2020).
Medium Risk Customers
Customers who are likely to pose a higher than average risk to the Bank should be categorised as medium or high risk. For this category, higher due diligence is required which includes the customer's background, nature and location of activity, country of origin, source of funds and his/her client profile, etc. besides proper identification. The following customers are classified as Medium Risk Customers:
- Gas Dealers
- Car/boat/plane dealers
- Electronics (wholesale)
- Travel agency, Telemarketers, Telecommunication service providers, Pawnshops , Auctioneers , Restaurants, Retail shops, Movie theatres
- Sole practitioners
- Accountants – Blind
Bank of Maharashtra. (Sept 2020).
High Risk Customers
For this category, higher due diligence is required which includes the customer's background, nature and location of activity, country of origin, source of funds and clients profile, etc. Banks shall subject such accounts to enhanced monitoring on an ongoing basis.
- Trusts, charities, NGOs and organizations receiving donations.
- Companies having close family shareholding or beneficial ownership
- Firms with sleeping partners‘.
- Accounts under Foreign Contribution Regulation Act.
- Politically Exposed Persons (PEPs).
- Customers who are close relatives of PEPs and accounts of which a PEP is the ultimate beneficial owner.
- Those with dubious reputation as per public information available.
- Accounts of non-face-to-face customers.
- High Net worth Individuals
- Non-Resident customers.
- Accounts of Cash intensive businesses such as accounts of bullion dealers (including sub-dealers) & jewelers.
Bank of Maharashtra. (Sept 2020).
The objectives taken into consideration before granting a loan should include;
- The credit worthiness of the customer by looking at the Cs of credit; character, cash, capacity, collateral, conditions and control. The Cs of credit helps banks to identify whether the customer can pay out the credit when due.
- Is it possible to properly structure and document the agreement?
- Can the lender complete its claim against assets or earnings of the customer? These objectives help banks identify bad loan applications and good loan applications.
The need to identify early warning signs of non-performing loans has become an important activity for the managers and credit controllers. By ranking customers according to predicted default probabilities, lenders have a chance to minimize the expected default or misclassification rate.
With the CRC Risk Calculator, lenders can identify risks and mitigate them. They could follow up on borrowers and through risk monitoring recommendations can be made on where the loan performance is poor to ensure default rates are kept to the minimum.
Bank of Maharashtra. (Sept 2020). Policy Guidelines on KYC/AML/CFT-2020-21