BCT Digital launches ‘IND AS 109 Product Suite’ to tackle Expected Credit Loss

Automating the Credit Risk Monitoring Process for effective Credit Loss Management

BCT Digital launches ‘IND AS 109 Product Suite’ to tackle Expected Credit Loss - rt360

Automating the Credit Risk Monitoring Process for effective Credit Loss Management

Chennai, 28 July 2020: BCT Digital, a global Fintech company specializing in BFSI, Predictive Analytics, and Risk Management, has announced the launch of rt360-ECL solution from ‘IND AS 109 Product Suite’ for Expected Credit Loss (ECL) reporting. The rt360-ECL is an integral part of the IND AS 109 Product Suite and has been designed exclusively keeping in mind the unique and specific nuances of Indian Financial Institutions and the Indian Regulatory Environment.

With the introduction of the global International Financial Reporting Standards-9 (IFRS 9) and its equivalent Indian Accounting Standards (IND AS) 109, financial institutions are moving towards adopting scientific methods for computing credit losses. The first set of guidelines in this regard were issued by the RBI in February 2016, which was followed by a series of amendments, and the latest one was issued in March 2020. This amendment announced the implementation of the Indian Accounting Standards, including IND AS 109 for NBFCs and Asset Reconstruction Companies.

IND AS 109 requires financial institutions to take the Expected Credit Loss (ECL) approach as opposed to the Incurred Loss approach. Under the ECL approach, credit losses must be granularly and systematically estimated and provided for throughout the life span of a loan. The rt360-ECL is a business-driven technology solution that enables banks to compute Expected Credit Loss as per regulatory guidelines, while addressing requirements such as Point-In-Time Probability of Default (PD), Validation and forward-looking estimates.

“During these unprecedented times, banks are facing huge credit losses as their customers suffer through the COVID-19 pandemic. Managing credit risk in a volatile financial market is very critical. If not carefully monitored, the systemic risks can easily snowball, and this can impact not only the banking network, but also the financial health of the country at a macroeconomic level. The rt360-ECL is an integral part of BCT Digital’s IND AS 109 product suite and has been exclusively designed keeping in mind the unique nature of the Indian regulatory environment and specific nuances of Indian financial institutions.” said Jaya Vaidhyanathan, CEO at BCT Digital.

The rt360-ECL aggregates banks’ historical data and estimates parameters such as Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD) and Effective Interest Rate (EIR). It’s inbuilt standard functions support validation and calibration of models to ensure that the process is efficient and robust. It’s essential value additions include automation of credit risk monitoring processes, faster turnaround time to achieve regulatory compliance and internal reporting and proactive credit risk assessment and monitoring. The core features of the rt360-ECL include computing 12 months’ and lifetime ECL for both fund-based and non-fund-based facilities; automated computation of Probability of Default, (Loss Given Default and Exposure at Default); Effective Interest Rate computation; automated validation of parameters as per RBI/Basel requirements through a pre-built library of model validation tests; integration with other solutions, such as core banking/Asset Liability Management systems& and prebuilt dashboards for management reporting. Click here for more information.

BCT Digital being a FinTech specialist and pioneer in risk management solutions aims to empower banks and financial institutions to recognize expected change in credit risk and provide a framework to manage forward-looking credit loss through the rt360 Risk Management Suite. rt360 risk products are a 100% “Made in India”, by BCT Digital, keeping in mind the complexity of internal and external risk factors faced by banks.

About BCT Digital

BCT Digital focusses on the risk management needs, and regulatory needs of the banking and finance sector (BFSI), on a global scale. The core of BCT Digital’s offerings lies in the ability to identify gaps and building solutions that are both specifically suited to India and yet scalable to the global markets. BCT Digital a niche player in the RegTech arena, adopting emerging technologies to mitigate risks, ensure liquidity and improve customer engagement. For more information, visit https://www.bctdigital.ai

About Bahwan CyberTek

Bahwan CyberTek (BCT) was established in 1999 and is a provider of digital transformation solutions across industry domains and has delivered solutions in twenty countries across North America, Middle East, Far East, Africa and Asia. Driving innovation through outcome-based business models, proven and powerful IP solutions, BCT is a trusted partner for over 1000+ customers, including Fortune 500 companies. With strong capabilities in Big Data & Analytics, Mobility, Cloud and UX / UI, BCT has over 2800 associates with technical and domain expertise in delivering solutions to Oil & Gas, Telecom, Power, Government, Banking, Retail and SCM / Logistics verticals. With a focus on joint innovation, BCT has partnered with leading global technology organizations such as Oracle, IBM and TIBCO to deliver differentiated value to customers.

For queries reach out bctdigital@bahwancybertek.com

Share On

Also Read

aibased, Thought Leadership
By rt360 January 13, 2020

AI-based Models and Model Risk

AI-based models are more susceptible to certain risks than their conventional counterparts, unless they are put through proper governance and oversight mechanisms. We will look at some of the model risks AI models may be susceptible (over its conventional counterparts).

Kasthuri Rangan Bhaskar
VP, Financial Services Practice & Risk SME (Lead) at BCT Digital

Read More

machinelearning, Thought Leadership
By rt360 December 23, 2019

Machine Learning and Credit Fraud Detection

Machine-Learning-based algorithms lend themselves as useful tools for analysing the possibilities of credit fraud. This is typically done by running the algorithms on various transactional data and analysing for hidden patterns.

Kasthuri Rangan Bhaskar
VP, Financial Services Practice & Risk SME (Lead) at BCT Digital

Read More

Publications