Measures to maintain liquidity and asset quality through good governance

Many NBFCs are structured in a manner that leaves room for inherent asset-liability mismatch. If we take the example of infrastructure HFCs, usually the assets are long-term, while the funding is short term.

Jaya Vaidhyanathan

Dr. Jaya Vaidhyanathan
President — BFSI & Strategic Initiatives and CEO, BCT Digital

Many NBFCs are structured in a manner that leaves room for inherent asset-liability mismatch. If we take the example of infrastructure HFCs, usually the assets are long-term, while the funding is short term. The onus lies on the system to ensure that the cash flow generated out of the assets is both viable and timely. The same wisdom held true in the IL&FS crisis of 2018. The sheer nature of the business of IL&FS demanded effective management of assets and liquidity in the short- and long-terms.

Interestingly, in the case of IL&FS, even though there were startling discrepancies in the balance sheet, auditors and rating agencies noted them and moved on – or arguably, did not take notice at all.
Any stringent regulatory guidelines aimed at improving the liquidity situation of NBFCs were in the transition phase.

In this context, the role of a robust monitoring mechanism becomes most important for safeguarding the health of the system. In retrospect, in the IL&FS scenario, adhering to a four-tier governance framework – involving both internal and external lines of defence – could have perhaps accelerated intervention and remediation by authorities.

More power to RBI through the ratification of new regulations

Perhaps the silver lining – a direct consequence of the NBFC liquidity crisis – was the much-needed shakedown of the shadow banking system jointly by RBI and SEBI. Steps towards remediation included: grouping HFCs under the RBI ambit (pulling them away the National Housing Bank); stripping several non-compliant NBFCs off their licenses1; granting the RBI power over NBFC boards (Union budget FY20)2; new norms to improve the liquidity situation, and so on.

Come 2020, the extension of a gradually scalable LCR and NSFR from banks to NBFCs will also be a strong step by the RBI in this direction.

Liquidity powered by an advanced technology suite like rt360

The liquidity risk management framework of a bank or an NBFC is a decisive factor in how effectively the liquidity position of a financial institution is measured and maintained. The best outcomes are when stakeholders from different levels of the NBFC (organizational-level, business-level and user-level) are involved in the process as independent, yet accountable members. As the final frontier, external regulators, auditors, and credit rating agencies, need to play proactive roles in identifying risk factors, flagging and following through to closure.

rupixen

The potential risk of liquidity crisis can be mitigated through these best practices:

  • Creating a robust framework incorporating three ALM pillars viz., ALM information system, ALM organisation (Asset-Liability Management Committee or ALCO) and ALM processes
  • Monitoring structural and short-term dynamic liquidity at both the gap-analysis level and stock approach
  • Maintaining a good balance of high-quality liquid assets and stable funding
  • Leveraging advancements in technology to empower and drive the liquidity governance framework across levels 1, 2, 3 and 4 (external)
  • Early identification, continuous monitoring and remediation of liquidity issues in the short-term and long-term
  • Scheduled stress testing for pitfalls, accounting for both institutional and market risks
  • Planning for contingencies and de-escalation strategies

Across the NBFC sector, asset-liability management (ALM) is at the nascent stage, and needs to be structured at par with scheduled commercial banks. The RBI’s latest guidelines, involving the ALCO, and its rules enforcing new monitoring mechanisms, have fuelled an urgency among NBFCs to adopt technology for liquidity risk management.

In today’s volatile marketplace, the interest rate risk by itself must be closely linked to funds transfer pricing, intraday liquidity and overall capital management. There is a need for a holistic approach using a robust Asset-Liability Management (ALM) framework to protect earnings and capital while reducing complexity and ensuring compliance.

A standardized system with an independent and targeted governance framework (adhering to RBI regulations and supported by specialist firms) can make an ocean of difference in the financial health of an NBFC. Such a specialist application can help banks and NBFCs meet their immediate liquidity requirements. Beyond this, it can also leapfrog them to the next level of compliance.

NBFCs can use such high-powered systems to:

  • Maintain a proper mix of assets and liabilities to mitigate liquidity risks
  • Build an appropriate mix of rate sensitive assets and liabilities to enable sustainability against Interest rate fluctuations, thereby improving the Net Interest Margin (NIM) and increase of shareholder’s value
  • Maintain high levels of asset quality and liquidity through regular stress testing using Basel III recommended LCR, accounting for potential threats from select business streams
  • Measure concentration risk like Top 20 depositor’s ratio, funding sources, counterparties etc.. that enables FIs in diversification of their funding profile
  • Robustly monitor intraday liquidity position, stress testing and sensitivity analysis for the FIs to prepare for potential risk events
  • Implement and enable a liquidity workflow system across the governance framework, involving various stakeholders
  • Track and record transactional activities for audit and action
  • Identify, measure and remediate shortfalls on real-time and periodical basis, converting data into analytical insights
  • Stay future-ready and flexible to accommodate the changing demands of users, evolving business models in FinTech, and the fluctuating regulatory landscape, using highly-scalable micro-services based architecture

rt360

As a FinTech specialist and pioneer in financial risk management solutions, BCT Digital, a division of Bahwan CyberTek (BCT) helps banks and financial institutions mitigate risk and safeguard operations through its flagship product suite rt360. Made in India – and built by bankers for bankers – rt360 is a game-changing solution suite that provides NBFCs the ability to drive sustained growth. The competencies it brings to the picture place NBFCs in a competitive position to take advantage of dynamic market changes while mitigating the associated liquidity risks.

Capabilities:

  • Time buckets for measuring liquidity risk
  • Residual maturity pattern for measuring liquidity gaps
  • Intraday liquidity management through BIS metrics and monitoring tools
  • Liquidity risk management through stock ratios including LCR, NSFR, balance sheet ratios, funding concentration
  • Interest rate risk in the Banking Book (IRRBB) measurement
  • Duration computation
  • Stress testing/scenario analysis on liquidity and interest rate risk
  • Mapping of general ledger heads
  • Business rules-based scenario/what-if-analysis
  • Granular insights with interactive dashboards
  • Behavioural studies for non-maturing items
  • Impact analysis
  • Cash flow accounting
  • Data aggregation and multiple risk reporting formats, leveraging BCBS 239 principles
  • Open architecture for seamless integration with multiple touch points
  • Increased scalability and high degree of customization

Benefits

Adopting a comprehensive, automated approach towards ALM through rt360 offers several measurable benefits:

  • Liquidity risk mitigation thereby enabling NIM and equity in both the short-term and long-term respectively
  • Improved ability to strategically hedge interest rate risk by measuring the impact of interest rate fluctuation on NBFCs’ P&L (NII) and equity (EVE)
  • Early identification of intraday liquidity gaps to meet potential stress situations
  • Improved regulatory compliance by adhering to Basel guidelines, and automated regulatory reporting on liquidity and interest rate risk
  • Accelerated decision-making, due to end-to-end automation of data aggregation, reporting, and superior visualization through dashboards
  • Automated stress testing for short- and long-term, institution-specific and market-wide scenarios, enabling NBFCs to maintain adequate liquidity and capital under stress conditions

Authors

Jaya Vaidhyanathan

Dr.Jaya Vaidhyanathan

CEO, BCT Digital

Dr. Jaya Vaidhyanathan is an independent Director on several Boards and is focused on bringing in the best global corporate governance principles to India. Her work has found coverage in top news websites like The Hindu and The Times of India. Recently, she pioneered award-winning Early Warning Systems for Indian banks, which have found acclaim in the industry and among counterparts.

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Managing credit risk in a volatile financial market with Early Warning Systems

Collaborating, brainstorming, improvising and iterating without boundaries. It’s every innovator’s dream. For the Indian banking industry, this dream has finally arrived – heralding an era of extraordinary change and progress

Jaya

Dr.Jaya Vaidhyanathan
CEO, BCT Digital
Shankar R

Shankar Ravichandran
Senior Manager at BCT Digital

The financial world is not without risks. As part of their fiduciary duties, banks operate with intense systemic risks every day, while empowering small firms to large multinationals begin new ventures, innovate and incubate, and ultimately act as the custodians of trust. If not carefully monitored, these 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.

A real-world scenario

When a corporate takes a loan has taken loan from a bank for building a plant. Normally, the bank will disburse the loan amount in tranches, using which the borrower will continue to pay suppliers for plant construction. Now, let us assume that the borrower attempts to defraud the bank by diverting the loan funds. In the guise of making vendor payment, the borrower sends the money to a “distributor” – a shell corporation that exists only on paper. Can the bank be defrauded?
Let us examine the whole gamut of information to which the bank is already privy:

  • The list of approved parties with whom the borrower is expected to transact for the project. Source: Project documentation
  • The fact that the sum transferred to the “distributor”, is very similar to the amount disbursed by the bank for the project. Source: core banking and transaction systems
  • The purpose of availing each loan installment. Source: the CA certificate to be mandatorily submitted to the bank
  • Whether the distributor is a blacklisted company or in the news for the wrong reasons, subject to frequent tax raids or audits. Source: Big data

If all of the above information (available at the different branches and locations of the same bank) can be shared with the authorities on time, the bank can proactively prevent fraud and save itself from an unsavory and litigious situation involving painful asset quality deterioration.

Credit risk management in perspective of the RBI mandate

The premise for Early Warning Systems is set here It all begins with credit risk. Broadly speaking, there are two aspects to defaults – ‘inability to repay’ and ‘no willingness to repay’. Both could potentially result in NPAs or Non-Performing Assets.

Following the Asset Quality Review of 2015, the RBI rolled out a string of regulations mandating the adoption of EWS as a best practice in identifying and mitigating the risks posed by Red Flagged Accounts (RFAs). The guideline issued mandated systems that would consider 45 indicators of stress in borrower accounts, measure the accounts with respect to each indicator, and flag incidents to authorities. Indeed, a laudable effort from the RBI.

Technology service providers were able to unearth much more data on borrowers from big data sources in addition to traditional data sources and this has aided with insightful decision-making:

  • Massive data ingestion and analysis of loan portfolios of banks across the country, products, and industries/customer segments, to take management calls on pulling back or expanding credit to specific sets of customers
  • Detect the stress of borrowers from what is reported in semi-public sources, including legal cases, share pledging, dubious business dealings, and so on.
  • Listen to rating agencies on what they are saying about their borrowers, industries or the economy
  • Listen to online and social media chatter on the promoters of a borrower

Now is the opportunity to leapfrog from just analyzing the transactional data of borrowers’ accounts to looking at them strategically.

pietro jeng

To begin with, the sanity of data itself is a big factor. The key is in knowing where to look for data and when, and this is no easy task. If we examine industry-leading banking risk management systems, like rt360 built by BCT Digital, which are custom-built for the Indian banking sector, they have some of the most extensive sources and credible touchpoints, making data compilation all the more effective. The advanced algorithms and rules engine are extremely effective in mitigating false positives and unwarranted alerts – an area that is particularly hard to manage. The rules as such are far more exhaustive; for instance, rt360 is configured to flag 200 warning scenarios – well more than the 45 proposed by regulators.

How Artificial Intelligence is transforming Early Warning Systems

Early Warning Systems rely on tens of thousands of data points to measure and monitor risks, which is almost impossible for humans to replicate. Artificial Intelligence can transform Early Warning Systems, enabling them to make instantaneous predictions and extract actionable insights from disparate data sources, using these four distinct transformative components:

  • Collating data from multiple touch points
  • Cleansing, validating and restructuring data into valuable information
  • Algorithmic processing using next-generation technologies and data modeling to generate insightful early warning signals/alerts
  • Case management by channeling alerts to decision-making authorities

The future will reveal to us the role of EWS in strengthening asset quality. Furthermore, for the system to achieve its full potential, there needs to be open collaboration between the bank and its technology partner, and this is where partnering with a service provider that has specialized risk management expertise is bound to show results.

Authors

Jaya Vaidhyanathan

Dr.Jaya Vaidhyanathan

CEO, BCT Digital

Dr. Jaya Vaidhyanathan is an independent Director on several Boards and is focused on bringing in the best global corporate governance principles to India. Her work has found coverage in top news websites like The Hindu and The Times of India. Recently, she pioneered award-winning Early Warning Systems for Indian banks, which have found acclaim in the industry and among counterparts.

Shankar Ravichandran

Shankar Ravichandran

Senior Manager at BCT Digital

His profound expertise in the field of corporate and retail banking spanning across Credit Risk, Transaction Banking, Service Delivery and Product Management is close to decade. He is an MBA graduate from Indian Institute of Management, Bangalore.

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Innovation Sandbox and Indian Banks – A close look at one of RBI’s most visionary initiatives of our time

Collaborating, brainstorming, improvising and iterating without boundaries. It’s every innovator’s dream. For the Indian banking industry, this dream has finally arrived – heralding an era of extraordinary change and progress

Jaya Vaidhyanathan

Dr.Jaya Vaidhyanathan
CEO, BCT Digital
Shankar R

Shankar Ravichandran
Senior Manager at BCT Digital

Collaborating, brainstorming, improvising and iterating without boundaries. It’s every innovator’s dream. For the Indian banking industry, this dream has finally arrived – heralding an era of extraordinary change and progress

“Innovation sandbox” – the phrase itself is so liberating. A place where thinking out of the box is the norm; the only rule is that there are no rules (or maybe just the bare minimum) and where mistakes are not only pardoned; they are encouraged. But how applicable is it in an institutionalized and conformist set-up, like banking, where rules and regulations are hardwired into the system and straying far from the rulebook can have serious, often fatal, repercussions on the economy of a nation?

In 2019, the RBI formally announced a draft “Enabling Framework for Regulatory Sandbox”, or the innovation sandbox. The framework seeks to enable technology-led companies to build (subject to limitations) and test financial products or services that facilitate innovation and positive change within the Indian banking industry, in return for possible regulatory relaxations, prior to actual launch. In this manner, it will attempt to bridge the gap between innovation, technology and the banking sector.

The RBI framework and the “amazonification” of banks

It is easy to see why the innovation sandbox is extolled by the industry as a welcome initiative by RBI. For one, similar initiatives have seen widespread success in other countries, UK being the first1, and later in Singapore and Estonia, which are shining examples of innovation in the digital realm. However, will the sandbox meet with unequivocal success in the Indian banking context?

The topic is certainly debatable, but if previous instances have taught us anything, it is that change is good, but disruption, even better.

If we take UPIs as an example – there was a time when the technology was still in the nascent stage and adoption rates were low. Before we go into the triggers that launched UPI to the fore, there are two factors we need to consider, in the context of UPIs.

  • 1. Indian Banks by nature are reluctant to share internal and user data, which they consider sacrosanct.
  • The back-end technology is not immune to risks, given that data changes hands several times – between the telecom service provider, the bank and a third-party gateway integrator.

nordwood

The NPCI, who developed the system2, was quick to identify the need for a framework to manage the risks and bottlenecks associated with UPIs. They released an experimental set-up – a controlled interface for all parties to collaborate on, learn and improve. This was perhaps one of the early triggers to the launch of the innovation sandbox in India. As of today, with close to 800 million transactions in March’193, UPIs are a highly effective industry-specific innovation, and a game-changer for the Indian banking industry.

At a glance: multiple benefits

In effect, the innovation sandbox interfaces a “black hole”, which is constituted by previously inaccessible core banking data, with technology innovations. In the above manner, working within a controlled environment, it will drive across-the-board innovations that can simplify banking related processes – for example, speed-up payments, lower risks, reduce transactional costs and so on.

Another aspect working in favour of the sandbox is the current “amazonification” of the banking industry aimed to connect bankers to new-age customers. The millennial population in particular need indian banks to become more contextual in their understanding of user needs. So, we have simple algorithms tracking usage patterns and collecting data to dispatch relevant and targeted information (e.g., promotional offers) to users. There has also been an exponential increase in the number of channels by which indian banks can interact with customers. Beyond the regular kiosks and bank branches, there are the mobile devices, credit/cards, UPIs, doorstep banking, ATMs and so on.

With this explosion in touchpoints and technologies come more vulnerabilities and more risks.

The airline industry was one of the most recent victims; a reputed airline was defrauded of millions in a scam. These sorts of occurrences call for an ecosystem where innovations are not only nurtured, but risks are identified and averted in the nick of time. The controlled yet real-life environment hosted by the innovation sandbox not only places confidence on technology service providers, but also provides them access to customer feedback right from day-1. This in turn reduces iterations, fast-tracks time to market and lowers costs. A calibrated launch model helps to limit risks and control losses for stakeholders, which empowers them to think and act freely, and work cohesively with indian banks towards mutually beneficial goals.

easybenefits

The flip side: Manifold risks

The absence of a strict policy on customer data privacy is one of the primary hindrances to the guaranteed success of the innovation sandbox. All said and done, the success of the innovation sandbox is directly related to the extent at which private user data, transactional records and confidential information are made available for experimentation. And as with all experiments, things can seriously go wrong. To ensure this is not the case, beyond the present Information Technology Act, India needs a strong policy restriction, as in the case of Europe with its GDPR regulations.

Of lesser magnitude, yet a concern nonetheless, is the fact RBI regulations expressly prohibit testing on cryptocurrencies. Blocking progress in this domain, especially given how Blockchain technologies are gaining traction across the globe, can be very limiting.

Fighting fire with fire

As things stand, it is too early to comment on how and when the concept of the innovation sandbox will finally take flight, and up to what extent. But there is no doubt that the RBI initiative has vast transformative potential. Current risk management systems, which manage and predict credit, liquidity and operational risks, make use of statistical models to make accurate and timely forecasts. The innovation sandbox can open new avenues of assessing, measuring, monitoring, controlling and preventing risks, while improving access to vast repositories of user and banking related data by bypassing regulatory restrictions. Equally noteworthy is how this collaborative ecosystem will accelerate technology adoption, promote out-of-box thinking and increase competitive user offerings.

But perhaps most important is its role in building solutions to issues that have been long plaguing the Indian banking system, including money laundering and NPAs. The current state of the industry, which is in dire need of innovative fintech intervention, dwarfs any apprehensions of data privacy violation, provided the RBI heightens measures to protect the use of valuable and confidential information.

Authors

Jaya Vaidhyanathan

Dr.Jaya Vaidhyanathan

CEO, BCT Digital

Dr. Jaya Vaidhyanathan is an independent Director on several Boards and is focused on bringing in the best global corporate governance principles to India. Her work has found coverage in top news websites like The Hindu and The Times of India. Recently, she pioneered award-winning Early Warning Systems for Indian banks, which have found acclaim in the industry and among counterparts.

Shankar Ravichandran

Shankar Ravichandran

Senior Manager at BCT Digital

His profound expertise in the field of corporate and retail banking spanning across Credit Risk, Transaction Banking, Service Delivery and Product Management is close to decade. He is an MBA graduate from Indian Institute of Management, Bangalore.

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Practitioners’ Insights On Credit Monitoring

In an industry-first survey on Credit Monitoring Practices of Indian Banks, Bahwan CyberTek highlights the need to take a holistic approach to credit monitoring with organizational ownership combined with an urgent need for automation as well as data integration.

Bahwan CyberTek, a leading global provider of innovative software products and solutions, has launched a report based on India’s first ever survey on ‘Credit Monitoring Practices of Indian Banks’; the report titled ‘Practitioners’ Insights on Credit Monitoring’.

In an industry-first survey on Credit Monitoring Practices of Indian Banks, Bahwan CyberTek highlights the need to take a holistic approach to credit monitoring with organizational ownership combined with an urgent need for automation as well as data integration.

Bahwan CyberTek, a leading global provider of innovative software products and solutions, has launched a report based on India’s first ever survey on ‘Credit Monitoring Practices of Indian Banks’; the report titled ‘Practitioners’ Insights on Credit Monitoring’. This was part of an event organized by the company where industry leaders and practitioners from private and public sector banks shared their experiences, both from a regulatory and a banker’s viewpoint and the latest regulatory developments in the Indian banking system, for credit monitoring.

The survey was conducted between October 2016 and February 2017, amongst senior bankers spearheading the credit risk monitoring or are part of the management unit, spread across 25+ public and private sector banks in India of varying asset sizes; this included banks whose total asset size comprised 42% of the combined asset size of all Indian scheduled commercial banks, as of March 2016.

Commenting on the launch of the report, Jaya Vaidhyanathan, President – BFSI & Strategic Business Initiatives, Bahwan CyberTek said, “We at Bahwan CyberTek believe in proactive action as opposed to merely reacting to an action. As a key priority for 2017 and years to come, we think it is important for Indian banks to make full use of the technology which will help automate and therefore improve their credit monitoring techniques, given that the health of our country’s economy depends on it.
“This therefore brings about the need for an Early Warning System where bankers can predict and assess the health of a borrower, for instance, and take the necessary measures. Moreover, such a system should help gauge the performance of all critical sectors that contribute towards the growth of the Indian economy”, she added.

Some of the key findings from the survey include:

  • No bank has completely automated the SMA (Special Mention Accounts) monitoring process
  • Banks largely rely on internal data to monitor the borrower health that might cause trouble in the future; the absence/ minimal use of external data (from an availability and quality point of view) doesn’t help in taking sound decisions.
  • Majority of the responding banks (>70%) see a need for a separate Early Warning System rather than making modifications to the existing systems, and have planned for one.
  • With regard to reporting, data collection is fully manual for 40% of the responding bank
    • For over 75% of the banks, report generation, dissemination and follow up actions is either fully manual or just partially automated

Speaking at the launch, T. N. Manoharan, Chairman, Canara Bank, said, “I would like to congratulate Bahwan CyberTek for undertaking this survey. I am sure that the findings will be of immense value to both banking personnel and the BFSI industry as a whole, and I personally hope to be enriched by the insights presented in the report. With regard to the banking industry, the two major challenges faced by the sector in the last one year have been the Asset Quality Review issued by the RBI, and demonetization. However, the banking industry is returning to normalcy, after having faced these hurdles.”

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