NEW DELHI: CMR uses machine learning algorithms to predict the probability of an MSME becoming NPA in the next 12 months. CMR provides a ranking to the MSME based on its credit history data on a scale of 1 to 10, CMR1 being the least risky MSME and CMR10 being the most risky MSME. The higher the CMR the higher the risk of NPA associated with the MSME.
Driving access to finance for MSMEs while controlling the quality of portfolios is the topmost priority for banks and credit institutions. Speaking at the launch in Mumbai, the Managing Director and CEO of TransUnion CIBIL- Satish Pillai said, “Financial inclusion and credit penetration are the keystones of propelling India on a sustainable high growth trajectory. Availability of credit to MSMEs is the lifeblood of our economy, but the sector is facing an ongoing challenge of rising NPAs. We believe resolving information asymmetry will be a contributor to making objective credit decisions while ensuring a wider and faster access to funds for MSMEs.”
Currently, the Indian MSME credit portfolio is estimated at INR 12 lakh crores. The NPA rate for MSMEs has increased continuously over last few years to reach 8.7 percent as of March 2016 and is expected to rise to 9.8 percent as of March 2017. As per the latest risk assessment, MSMEs falling in the highest risk bracket of CMR 7- 10 have a credit outstanding of INR 54,799 crores which is at risk of going into NPA.
Additionally, banks and credit institutions have been showing a keen interest in the sector due to which the credit lending had increased by 11 percent last year. TransUnion CIBIL will continue to support the credit growth in the sector by equipping banks and credit institutions with CMR on 2.1 million MSMEs.
Speaking on the benefits that CMR launch will bring for MSMEs, V G Kannan, Chief Executive, Indian Banks’ Association (IBA) said, “CIBIL MSME Rank is yet another initiative from TransUnion CIBIL to fortify the MSMEs to gain access to formal financial institutions with set parameters. Essentially, credit scoring throws light on the credit worthiness of the customer which would be of immense help to banks. It is a “win-win” for both MSMEs and banks and would automate the entire loan processing in the financial eco system.”
TransUnion CIBIL has considered all the requirements of a Basel compliant model while developing CMR. It is trained on over 7 years of through-the-cycle credit history data. It is developed specifically for MSMEs which are classified based on aggregate exposure between INR 10 lakh to 10 crore.
Banks and credit institutions in India are enthusiastic on the prospects of CMR to remove information asymmetry and support credit growth. “CIBIL MSME Rank will be a very helpful tool for credit decisions considering that MSME sector is largely unorganized and therefore collection of information is very difficult. More important is that CMR will provide lenders an outcome which is more consistent in view of model assumption asymmetry. This will help in reducing turnaround time for acquisition of new MSME customers, rule–based bulk renewals along with setting and monitoring of rank based limit for portfolio,” said Animesh Chauhan, Managing Director and Chief Executive Officer, Oriental Bank of Commerce.
Jairam Sridharan, Group Executive & Chief Financial Officer at Axis Bank said, “Small business lending is an important focus area for Axis Bank. We believe CIBIL MSME Rank can provide critical insights for managing risk and thereby enable greater credit opportunities for deserving small businesses. With that in mind, we will be piloting the use of CIBIL MSME Rank in credit decisions in this segment over the next few months”
TransUnion CIBIL is committed to support the credit industry with content, insights, products and solutions for driving business growth while catalyzing access to finance for deserving MSMEs. We are confident that the CIBIL MSME Rank will effectively help banks and credit institutions to make objective credit decisions, improve turnaround time & control NPAs and help MSMEs have access to faster and cheaper credit.