How did our risk assessment framework enable a large bank to create a credit policy?

Sep 29, 2022

Highlights of the Case Study: 

Particulars Description 
Client A leading international bank serving over 150 markets worldwide wanted an advanced rating-based approach to assess the risk involved while framing credit policies for its high-net-worth clients. 
Business Challenge The client wanted to do provisioning and create safeguards against potential defaults and loan losses by identifying and estimating the risk exposure using Quantizig’s quantitative tools and risk assessment framework.  
Impact Quantzig’s risk assessment framework helped the client make informed decisions on credit disbursal based on risk limits, which reduced the credit default rate significantly. 

Game-Changing Solutions for the Banking Industry

 The 2008 sub-prime crisis, which now seems to be a distant past, changed the way regional-, public-, private-sector, and international banks emerge and do business. Risk concerns continue to be the top priority for bankers while creating various procedures and policies for the products and services they offer. Quantzig’s risk assessment framework identifies and quantifies risks related to transaction fraud, credit default and losses, and the default risk for a mortgage lender. By taking a unified approach, Quantzig provided its clients with a holistic view that will help in two ways – bring in a slew of financial and operational risk mitigation standards and enable informed decision-making at all levels.  

The Challenges of the Client 

A leading international bank serving over 150 markets worldwide wanted an advanced ratings-based approach to assess the risk involved while framing the credit policies for its high-net-worth clients; hence, it approached Quantzig. The client wanted to leverage our credit risk assessment framework that uses quantitative models to identify and estimate the risk exposure and probability of defaults, enabling the client to do provisioning and create safeguards against potential defaults and loan losses. 

The client’s risk compliance department was facing the following issues: 

  • Rapidly evolving regulatory guidelines – banking regulatory authorities like OCC and FRB have no specified risk assessment methodologies. 
  • An extensive analysis of macro and micro economic and country risk factors involved at the granular level – these risk factors cannot be ascertained based on historical deviations. 
  • In-depth data preparation – summarize and analyze defaults, fraud, credit losses, market capital requirements, and trend projections every month. 

Quantzig’s Risk Assessment Framework for Banks 

Quantzig adjusted its risk assessment framework model in line with the client’s requirements based on the risk-bearing capacity and the customers’ risk profile. Our risk assessment framework puts down the risk limits in terms of value at risk (VAR), portfolio or credit risk, and earning risk. It also puts down the stress scenarios that measured the variance or any unusualness in the market economic conditions and monitored the variance between the predicted risk and the actual market risk. This helped the client’s risk compliance department to identify and measure the risk associated with default and develop adequate policies for high-net-worth individuals (HNIs) while pricing complex products and mortgages. 

Impact Analysis of Quantzig’s Risk Assessment Framework in Banking 

Our risk assessment framework helped the client make informed decisions on credit disbursal based on risk limits, which reduced the credit default rate significantly. Using our risk assessment framework, the client could calculate – exposure at default (EAD), probability of default (PD), and potential losses over the life span of the loan period. Quantzig’s BFSI analytics team worked collaboratively with the client’s risk compliance department and created comprehensive and detailed documentation describing the risk scenarios based on market assumptions. This not only helped the client cover the financial risk but also cut down on its operating costs as it did not have to set up its own risk assessment framework and face the challenges of frequently evolving banking regulations. 

Key Outcomes 

Rapidly evolving regulatory guidelines have changed the lending and borrowing course in banks over the past decade. The fear that emerged from the global financial crises has transformed risk functions, and therefore, bankers around the world are incorporating a risk assessment framework in framing credit policies and procedures. Our client wanted to limit the risk exposure by setting up strict guidelines that define the selection criteria and manage the default risk thereafter. Quantzig’s risk assessment framework optimized the risk by factoring in capital adequacy, liquidity, and leverage ratios. This way, we helped the client set up a highly analytical strategy optimization and risk assessment process. 

Broad Perspective on Risk Assessment Framework in the BFSI Sector 

The banking, financial services, and insurance (BFSI) sector has been intensifying and becoming more competitive and future-oriented than ever before, thereby empowering banks as well as customers. In recent years, tech companies such as Google and Paytm are diversifying their reach into the BFSI sector, developing banking and payment apps. They are penetrating into the FinTech field by forming alliances and leveraging their active customer base and rising ease of Application Programming Interface (API) payments integration to gain a hold of the competition.  

Key Takeaways 

  • The client could mitigate the risk and make smarter decisions on credit distribution, which would reduce the credit default rate significantly. 
  • The client could predict the potential losses by tracking the credit profiles of customers over the life span of the loan period. 
  • The client could curb financial risks as well as operational risks. 
  • The client could calculate the key indicators of default risk – EAD (exposure at default) and PD (probability of default) with 99 percent accuracy. 

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