The magnitude of the spread of the COVID-19 pandemic has forced the world to come to a virtual halt, with a sharp negative impact on the economies worldwide. The last few weeks have seen one of the most brutal global equity collapse, spike in unemployment numbers, and negative GDP forecasts. With the crisis posing a major systemic financial risk, effective credit risk management in these times is the key imperative for the banks, fintech and lending institutions.

Expected spike in delinquencies and credit losses post COVID-19

The creditworthiness of banking customers for both retail and commercial portfolios has decreased drastically due to the sudden negative impact on their employment and income. In case of continuation of the epidemic for a longer-term period, the scenarios in terms of defaults and credit losses for banks could potentially be much higher than as observed in the global financial crisis of 2008.
expected spike in delinquencies and credit losses post covid-19

Need for an up-to-date, agile and analytics driven credit decisioning framework:

The existing models that banks rely upon simply did not account for such a ‘black swan event’. The credit decisioning framework for banks based on existing risk models and business criteria would be suboptimal in assessing customer risk, putting the reliability of these models in doubt. There is an immediate need for banks to adapt new credit lending framework to quickly and effectively identify risks and make changes in their credit policies

Incedo’s risk management framework for the post COVID-19 world

To address the challenges thrown up by the COVID-19, it is important to assess the short, medium and long-term impact on bank’s credit portfolio risk and define a clear roadmap as a strategic response focusing on changes to risk management methodologies, credit risk models and existing policies.

We propose a six-step framework for banks and lending institutions which comprises of the following approaches.


  1. COVID Risk Assessment & Early monitoring Systems

Banks and lending institutions should focus on control room efforts and carry out a rapid re-assessment of customer and portfolio risk. This should be based on COVID situational risk distress indicators and anomalies observed in customer behaviour post COVID-19. As an example, sudden spike in utilization for a customer, less or no credit of salary in payroll account, usage of cash advance facility by transactor persona could potentially be examples of increasing situational risk for a given customer. In the absence of real delinquencies (due to moratorium or payment holidays facility), such triggers should enable banks to understand customer’s changing profiles and create automated alerts around the same.


  1. Credit risk tightening measures

Whether you are a chief risk officer of a bank or a credit risk practitioner, by now you would have heard many times that all your previous credit risk models and scorecards would not hold and validate any longer. While that is true, it has also been observed that directionally most of these models would still rank order with only a few exceptions. These exceptions or business over-rides can be captured through early monitoring signals and overlaid on top of existing risk scores as a very short term plan. Customers with a low risk score and situational risk deterioration based on early monitoring triggers are the segments where credit policy needs to be tightened. As the delinquencies start getting captured, banks should re-create these models and identify the most optimal cutoffs for credit decisioning.


  1. Personalized Credit Interventions

There are still customers with superior credit worthiness waiting to borrow for their financial needs. It is very important for banks to discern such customers from those that have a low ability to payback. To do this, banks require personalized interventions to reduce risk exposure while ensuring an optimal customer experience through data-driven personalized interventions. Banks need to help customers with liquidity crunch through Government relief programs, bank loan re-negotiation, and settlement offers while building a better portfolio by sourcing credit to ‘good’ customers in the current low rate environment.

  1. Models Re-design and Re-Calibration

A wait and watch approach for the next 2-3 months period to understand the shifts in customer profile and behavior is a precursor before re-designing the existing models. This would enable banks to better understand the effect of the crisis on customer profiles and make intelligent scenarios around the future trend for delinquencies. There would be a need to re-calibrate or re-design the existing models. Periodic re-monitoring of new models would be a must, given the expected economic volatility for at least next 6-12 months period.

  1. Model Risk Management through Risk Governance and Rapid Model Monitoring

There is an urgent need for banks to identify and quantify the risks emerging due to the use of historical credit risk models and scorecards through Model monitoring. While the risk associated with credit products has increased, the delinquencies have not yet started getting captured in the bank’s database due to the payment holiday period facility introduced by govt’s of most of the countries. In such a situation, it is critical to design risk governance rules for new models that may not have information related to dependent variables (e.g. delinquency) captured accurately.

  1. Portfolio Stress Tests aligned with dynamic macro economic scenarios

Banks and lending institutions need to leverage and further build on their stress testing practice by running dynamic macro-economic scenarios on a periodic basis. The stress testing practice has enabled banks in the US to improve their capital provisioning and the COVID crisis should further enable banks across the geographies to use the stress tests to guide their future roadmap depending on how their financials would fare under different scenarios and take remedial actions.

The execution of the above-mentioned framework should ensure that banks and fintech’s are able to respond to immediate priorities to protect the downside while emerging stronger as we enter the new normal of the credit lending marketplace.

Incedo is at the forefront of helping organizations transform the risk management post COVID-19 through advanced analytics, while supporting broader efforts to maximize risk adjusted returns.

Our team of credit risk experts and data scientists has enabled setting up the post COVID early monitoring system, heuristic post COVID risk scores, and COVID command centre for a couple of mid-tier US based banks over a period of last few weeks.

Learn more about how Incedo can help with credit risk management.

While the reckless overextension of credit lines by lenders and banks was the root cause of the financial crisis of 2007-09 and it had the US primarily as its central point, this time the financial crisis has been caused by a virus with rapidly evolving geographical centers and covering almost the entire world. The banks though are in a catch 22 situation, they need to support the government’s lending and loan relief measures while also maintaining low credit loss rates and enough capital provisioning for their balance sheet. Effective risk management and credit policy decisioning was never as challenging for the banks as it is now in the post covid-19 world.

COVID-19 implications and challenges for banks and lending institutions

Sudden shift in risk profile of retail and commercial customers – The surge in unemployment, deteriorated cash flow for businesses, etc has led to a sudden shift in the credit profile of customers. The data that banks used to leverage before COVID might not provide an accurate picture of the consumer’s risk profile in the current times.

Narrow window of opportunity to re-define credit policies – Bank’s credit policies in terms of origination, existing customer management, collections, etc have been designed over years with a lot of rigor, market tests, design and application of credit risk models and scorecards, etc. The coronavirus has caught the bankers and Chief Risk Officers by surprise and there is a narrow window of opportunity to make changes in existing models and risk strategies. While a lot of banks had built a practice of stress testing for unfavorable macroeconomic scenarios, the pace and impact of coronavirus have been unprecedented. This requires immediate response from the banks to mitigate the expected risks.

Government relief programs like payment moratoriums – The introduction of payment holidays and moratorium programs are effective to take some burden off consumers but prevent the banks from understanding high risk customers as there is no measure of delinquency that banks can capture from existing data.

Four-point action plan and strategy to navigate through the COVID-19 crisis

Banks will need to go back to the drawing board, re-imagine their credit strategy and put in accelerated war room efforts to leverage data and create personalized risk decisioning policies. Based on Incedo’s experience of supporting some of the mid-tier banks in the US for post COVID risk management, we believe the following could help banks and lenders make a fast shift to enhanced credit policies and mitigate portfolio risk

  1. Covid situational risk assessment – As a starting point, Risk managers should identify the distress indicators that capture the situational risk posed post Covid-19. These indicators could be a firsthand source of customer’s situational risk (e.g. drop in payroll income) or surrogate variables like higher utilization or use of cash advance facility on credit card etc. Banks would need to leverage a combination of internal and external parameters, such as industry, geography, employment type, customer payment behavior, etc. to quantify COVID based situational risk for a given customer.

  2. Early warning alerts & heuristic risk scores based on a recent behavioral shift in customer’s risk profile – A sudden change in the financial distress signals should be captured to create automated alerts at the customer level, this in combination with a historical risk of the customer (pre-COVID) should go as a key input variable into the overall risk decisioning process. The Early warning system should issue alerts, alerting the credit risk system of abnormal fluctuations and potential stress prone behavior for a given account.

  3. Executive Command Centre for COVID Risk Monitoring – The re-defined heuristic customer risk scores should be leveraged to quantify the overall risk exposure for the bank post COVID. Banks need to monitor the rapidly changing credit behavior of customers on a periodic basis and identify key opportunities. The rapid risk monitoring based command center should focus on risk across the customer lifecycle and various risk strategies and help provide answers to some of the following questions of the bank’s management team
    • What is overall current risk exposure and forecasted risk exposure over short term period?
    • How has the overall credit quality of existing customer base changed, are there any patterns across different credit product portfolios?
    • What type of customers are using payment moratoriums, what is the expected risk of default of such customer segments?
    • Quantification of the drop in income estimates at an overall portfolio level and how it could affect other credit interventions?
    • What models are witnessing significant deterioration in performance and may need re-calibration as high priority models?executive-command-centre-for-COVID-risk-monitoring
  4. Personalized credit interventions strategy (Whom to Defend vs Grow vs Economize vs Exit)  – To manage credit risk while optimizing the customer experience, banks should use data driven personalized interventions framework of Defend, Grow, Economize & Exit. Using customer’s historical risk, post COVID risk and potential future value-based framework, optimal credit intervention strategy should be carved out. This framework should enable banks to help customers with short term liquidity crunch through government relief programs, bank loan re-negotiation and settlement offers while building a better portfolio by sourcing credit to creditworthy customers in the current low interest rate environment.


The execution of the above-mentioned action plan should help banks to not only mitigate the expected surge in credit risk but also enable a competitive advantage as we move towards the new-normal. The rapid credit decisioning should be backed with more informed decision making and on an ongoing basis, the framework should be fine-tuned to reflect the real pattern of delinquencies.

Incedo with its team of credit risk experts and data scientists has enabled setting up the post COVID early monitoring system, heuristic post COVID risk scores and COVID command center for a couple of mid-tier US based banks over a period of last few weeks.

Learn more about how Incedo can help you with credit risk management.

Over the past two months, COVID-19 has not only created a global health crisis but also led to socio economic disruption and affected major industry sectors, including healthcare, banking, insurance, capital markets and so on.

Wealth management is one of the vulnerable sectors with highly correlated revenues to capital market performance and has already started experiencing loss in revenue and growth. The stock market response to the COVID-19 pandemic has been panic driven and volatile and could continue to be so until the spread of the virus is contained. With the economic data likely to worsen in the coming months, stock markets could experience another round of correction.

As a result, firms have initially struggled and are now implementing plans to reduce costs, assess spending, with continued efforts to tackle extremely high trade volumes and keep critical processes running. Most firms have now dealt with the initial priorities to ensure large scale business continuity and set up the majority of the workforce to work remotely. These firms are now working to identify data and information security risks and reprioritize organization strategies and projects.

There are a few firms that are yielding benefits of prior investments in digital transformation, automation and infosec who are slightly ahead in the digital maturity curve while others are just starting out to plan and strategize their digital journey for  the near future.

From our experience, we believe there are four key themes shaping up during this crisis which will help wealth management firms stay resilient:

  1. Focus on cost reduction and rationalization: To tackle market volatility, there is an increased focus on optimizing costs and improving operational efficiency. With a growing volume of business transactions, deployment of tactical automation solutions to automate trade processing and compliance reporting will embed the much needed flexibility and improve productivity. Outsourcing additional processes for short to medium term will also help address the increase in workload without huge cost investments. On the technology front, leveraging cloud solutions would be a quick win to reduce fixed costs immediately.
  2. Prioritize risk and data security: Given millions of resources are working remotely, companies will have to revisit cybersecurity best practices and enhance/upgrade systems to protect from unauthorized access, phishing scams, etc. With unsecured channels and networks for remote employees, wealth management firms will also need to reassess access to applications depending on criticality due to the increasing threat of cybersecurity. Adoption of multi-factor authentication and enhancing security incident management protocols would be vital in maintaining data security.
  3. Continue to focus on Digital Transformation: Firms need to double down at their digital transformation practice to defend their core business and emerge as a winner in this new normal. Digital analytics is critical for companies to refine their portfolio strategy, help automate critical processes through usage patterns, strengthen market research and insights to better communicate with advisors, broker dealers and investors. The significance of omnichannel and well-designed advisor & investor portals could have never been higher. Simple and intuitive portals will help communicate account/portfolio performance and help stakeholders make data, transaction requests faster and understand how they are being impacted in real time. It’s critical to harness the data across the web, mobile, branches, CRM to make sure the best of the experience can be provided to clients and advisors.
  4. Enhance IT resiliency: Most firms were unprepared for a crisis of this magnitude, given its unprecedented nature. While on the one hand, businesses have managed to get their workforces set up remotely, it is critical that they continue to assess the impact of network traffic, volumes,  on the infrastructure. They should also prepare and update plans to address security breaches, network breakdowns, and critical resource unavailability in a proactive manner.

In spite of the downfalls, every crisis helps businesses realize their underlying strengths and helps them define their strategy roadmap for the next journey. We strongly believe that investments in operational efficiencies, digital transformation and customer experience optimization while continuing to work on data security and BCP will be the key pillars of running a resilient business during this crisis. They will continue to remain important in the ‘new normal’ that will emerge post the pandemic as well.

The Covid -19 pandemic continues to disrupt the Pharma industry. As uncertainty around the pandemic lingers and refuses to go away, Pharma leaders are facing extraordinary challenges due to the following forces at work:

Rapid shift in demand of drugs due to the impact of Covid-19 – The pandemic has impacted the demand of drugs for various therapeutic areas differently. There is an unprecedented surge in demand for drugs which are being considered as treatment candidates for Covid-19 e.g  Remdesivir (Gilead), Actemra (GNE) and Kevzara (Regeneron). There has also been a significant upsurge in demand for symptomatic medicines like antivirals, pain medications and ICU medicines which are used for managing complications from Covid-19. On the other hand, delays in elective surgeries and non-essential treatments have led to huge drop in Rx for many categories, and a rise of product switching in favor of self administered drugs

Geographical risk due to Covid-19 changing very quickly – After weeks of shutdown, some countries and states are cautiously reopening their economy. As regions open up, there are new emerging hotspots which can modify the density of cases, and hence the downstream impact on key decisions for Pharma Cos like inventory allocation for treatment therapies, supplier management  and execution of clinical trials. Given the rapidly evolving dynamics with Covid-19, companies need to ensure that they are using the most updated data and case forecasts for decision making

Pharma forecasts are broken – For an Industry which relies very heavily on forecasting, the historic data on which all forecasting, planning and distribution systems are built on has changed. Many of the previous signals used for forecasting like seasonal patterns, events, channel characteristics and patient behavior might not hold true going forward. There are new behaviors like hoarding, preference for self administered drugs and movement to telehealth which challenge pre-existing assumptions. Forecasters need to factor in this “black swan” scenario into their assumptions, and the geographical risk of cases would be one of the key factors impacting Pharma KPIs

Given this scale of disruption, how can Pharma companies solve this?

Unprecedented problems can still be solved with conventional solutions. With the right tools, Data science can provide much needed clarity, direction and guidance on what is happening now , and what is expected to happen ahead. We propose a 5 step approach with a Covid-19 Control Room for Pharma companies which composes of the following components.

  1. Covid-19 geographic risk assessment – Assess how the Covid-19 epidemic would play out with estimation of Covid-19 cases at Country, State and County level. There are multiple sources of forecasts like IHME, Northeastern University, Columbia University or you can build custom SIER Models. Models are only as good as their assumptions, so it is advisable to look at forecasts from multiple models to capture the possible range of outcomes for assessment of the geographical risk. A dashboard view like the one below, with the ability to customize the forecast would be a foundation for the Covid-19 Control room. This base estimation of geographical risk can be used to model scenarios for a range of decisions e.g inventory allocation, supplier risk and clinical trial management being some of them

    Covid-19 geographic risk assessment

  2. Segmentation of drugs based on categories of consumption – If you observe the pattern of how demand is getting disrupted across therapeutic areas, there are 3 key demand archetypes that would emerge.
    • Direct impact – For drugs which are in late stage clinical trials for treatment of Covid-19 e.g Actemra (GNE), Kevzara (Regeneron), Lopinavir+Ritonavir (AbbVie) – effects of hoarding or upsurge are leading to more than 5X increase in  sales, with demand quickly outstripping supply. This has already led to shortages. Remdesivir which received emergency use authorization by FDA might be in shortage for a long time – Gilead reported there’s only enough of it for 200k patients around the world
    • Secondary impact – For drugs which help in symptom management e.g pain/anaesthetic drugs like Paracetamol & Ibuprofen, antivirals like Rapivab and respiratory drugs have seen a huge uptick in demand e.g 91% increase in Paracetamol, 27% in Beclometasone, 23% increase in Salbutamol in the first week of Mar’20 compared to Mar’19. There are also a class of drugs used for Covid-19 complication management e.g  ICU drugs like Epinephrine, Fentanyl and Oxycodone which have seen demand surges and reported shortages
    • Negative or no impact – For some categories, demand has fallen sharply. In office administration volumes show huge drop in demand including certain categories of prescription drugs e.g -45% Rx for Pediatric Antibiotics. There are shifts based on mode of administration e.g IV administered oncology therapies show decreased demand relative to oral therapies
  3. Calibrate demand sensing for each demand archetype – Understanding the demand archetype of drugs in the company’s portfolio would enable forecasters to calibrate the demand post disruption and improve the accuracy of their forecasts. One of the key signals of drug demand at the distributor level is the geographic risk. For some like Actemra and Kevzara, the increase in demand would be directly proportional to the number of cases with Covid-19 in any region. E.g we know that Kevzara is a treatment candidate for patients with severe pneumonia due to Covid-19. Signals like number of expected cases, admission rates, patient demographics & access to the drug can be used to derive an accurate estimate of the demand for the drug. Similar analysis is needed based on demand archetype to calibrate forecasting techniques for other therapeutic areas  given this ‘structural break’ in historic time series data due to Covid-19
  4. Develop strategies for short, medium and long term – Once you have a sense of impact on the therapeutic area, organize your efforts for  the Covid-19 Control room which would provide a perspective on  short term ‘Crisis management’, medium term ‘Risk management’ and long term ‘Restoration to normal’ initiatives. For Supply chains, the initiatives would be:
    • Short term Crisis Management – Inventory risk assessment & allocation
    • Medium term Risk management – exploring options for ramping up production, managing supplier risk and reducing lead time
    • Long term Restoration to Normal – capacity planning, planning for recurring cycles of pandemic

    For example, here is an illustration of Inventory Risk assessment with key insights on Inventory Allocation at county level for a demand archetype with direct Covid impact.  An inventory risk assessment and allocation solution would compute the mismatch between demand and supply – measured by the ‘shortfall from required DoH’ to surface alerts. This would ensure that inventory allocation is optimal – precious drugs are sent to the critical locations and hospitals who need it most.


  5. Build early warning indicators – Covid-19 infections, as some expect, might stay and relapse long into the future – even after the first wave. Machine learning can be used to constantly analyze and correlate parameters like case rate, death rate and growths with anomaly detection systems which detect shifts in cases and identify emerging hotspots of infection. This will help companies quickly recalibrate decisions e.g  here is a view of how an autonomous Anomaly detection system for the Covid Control room is built at country, state and county levels enabling decision makers to zoom in and out to identify hotspots quickly.


As we have all experienced, every day is a new unprecedented chapter in this outbreak of Covid-19. Strategies leveraging data and tools at our disposal can help Pharma companies win the battle against this pandemic. Companies that execute on these strategies will have a clearer view of what is expected to happen, and hence better prepared to face the challenges which lie ahead.

This Article is part 2  in the series – ‘Managing Pharma Supply Chains in times of Covid-19

For more  insights on how Pharma companies can Optimize their Supply chains, please click here.

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