Non-Banking Finance Companies (NBFC) along with other Financial Institutions (FIs) have been providing credit largely to unorganised sector of the economy, encountering challenges in conserving their risk capital.
However, with the increased use of technology platforms and simultaneous availability of other lending options, various dynamics of business processes have undergone realignment, especially in the area of customer acquisition; credit assessment; asset quality monitoring and for meeting stringent regulatory reporting requirements. FIs, including NBFCs, are facing the issue of burgeoning Non Performing Assets (NPAs) as never before. Monitoring potential NPAs and following NPAs for effective recovery is a top priority.
Stress Precedes Defaults; Identify Stress to Manage Defaults It is estimated that stressed exposures account for nearly 9 to 10 per cent of the outstanding loans. In the conventional approach, the potential defaults and its severity are identified through Days Past Due (DPD) method for monitoring and follow up. However, the dynamics of market forces influencing lending eco-systems, demand corresponding robust approaches to enable proactive interventions for arresting slippages or minimise the rate of NPA creation.
D2K Technologies’ CRisMac EWS is the comprehensive Risk Engine which leverages latest in technology with predictive capabilities. CRisMac EWS system uses advanced web crawlers to collate data from over 2500 sources, analysis transaction behaviour, track backward and forward linked sectors or segments to discern stress and use advanced statistical modeling techniques to generate a readable EWS or Credit Risk Score. CRisMac EWS facilitates Customer Analysis, Industry insights and identify over 175 plus risk triggers. The system assimilates dynamic data in conjunction with institutional memory flowing through the organisation and sets a bench mark score for comparison with its corresponding peers. CRisMac EWS enables plough-in both structured and un-structured data seamlessly to the point of use by field and monitoring staff.
The dynamic CRisMac EWS score is rendered on mobile devices including tablets for ease and rich user experience. The predictive models help in identifying a default prone exposure at least 9-12 months in advance to enable the NBFC to identify the stress and apply remedial measure. The CRisMac EWS Risk engine can be proactively used for origination, monitoring, review and monitoring of existing exposures and compute Risk Capital requited as per Basel norms. where in a vast amount of the dealing experience remains outside the NBFC’s Institutional Memory.
The real time alerts enable the monitoring staff to proactively intervene and arrest the asset from becoming a NPA. The changing face of lending risk largely goes unrecognised and poses avoidable risk of asset quality erosion. A data-driven, technology enables CRisMac EWS cover the gap in mitigating the Asset quality risk effectively.
Views expressed in this article are of V K Sudhakar, Chief Executive Officer, D2K Technologies. www.d2ktechnologies.com