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July 20, 2017

Asset pricing is an important aspect in credit management. How a bank prices its loans holds the clue to whether it makes or loses money. If a bank underprices its loans, it loses money. If it overprices, it may make money for some time, but will eventually lose business to other banks that offer lower rates of interest. So what is optimal pricing? It is debatable, as pricing is a function of several variables, which differ for banks.

The predominant method followed by most banks for pricing assets is risk-based pricing. It not only allows them to recover the cost of funds and overheads, but also offers an opportunity to earn a reasonable profit on a risk-adjusted basis. Simply put, banks add a premium to the interest rate to cover probable default risks.

The concept of risk-based asset pricing looks appealing in theory, but can banks really implement it? The answer is in the negative.

If a bank prefers risk-based pricing to competitive pricing, it may risk losing its customers to competitors that offer better options. On the other hand, if the bank applies competitive pricing to retain customers, the expected rate of return (RoR) may decline on account of any possible default of the customer. Banks are therefore forced to make a difficult choice.

They can make a decision based on these parameters:

  • Risk appetite: A high risk appetite may translate to lending to customers on more liberal terms , and a low risk appetite may impel banks to play safe
  • Risk strategy: Closely aligned with risk appetite, this aspect determines whether the bank is willing to absorb risks, or transfer them
  • Alternative lending opportunities: If opportunities are limited or if they do not generate RoR as much as the current one on hand, banks might agree on competitive pricing
  • Opportunity cost of idle funds
  • Spinoff benefits from the counterparty, for example, additional business or float funds

Why pricing is a tricky affair

Conflicting viewpoints:

Often teams within the bankthe credit relationship team and the credit risk teamview assset pricing differently. Relationship managers work in a competitive environment, with the objective of increasing the market share of their banks. In pursuit of their objectives, they may pilot credit proposals on liberal pricing terms. However, while credit risk managers may not agree on the competitive pricing, they add a risk premium to the pricing, based on the risk rating of customers. These conflicting viewpoints can add to the problem.

Lack of critical insight into data:

Banks require both internal and external data to make effective pricing decisions. While structured and semi-structured internal data lies scattered across myriad systems within the bank (like credit, finance, risk, investment, and CRM systems), unstructured external data is available in the form of social media posts, blog posts, and feeds that have an impact on customer risk profiles, the industry, and so on. Banks that focus only on internal data may miss out on potential business opportunities, or even fail to predict possible credit default or credit quality deterioration. Banks are thus forced to take hurried (and often incorrect) decisions for fear of losing market share.

What is the way out?

To address the conflicting viewpoints of relationship managers and risk managers on pricing, banks should clearly spell out the resolution mechanism of asset pricing in their credit policy documents. For instance, a typical credit policy document may state that, if the general manager (GM) is the authority for credit approval under normal circumstances, any deviation could be decided by an authority above the GM. The authority approving the exceptional pricing should clearly document the quantum of pricing concession and the additional non-pricing conditions or covenants (like additional collateral and more frequent reviews of the loan in question) to mitigate the risk, if any. This would greatly resolve friction within the bank.

To get timely and critical insights into data, building a central repository with a highly robust predictive analytics system is the need of the hour. The central repository is indispensable for holding all relevant data related to counterparty, industry, market intelligence, and economic indicators in a clean and harmonized format to facilitate meaningful data analyses. Armed with insights, banks can weigh risk-based asset pricing and competitive asset pricing as part of the credit underwriting process to make effective pricing decisions.

Ramanan Ramachandran is a Senior Domain Consultant with the Banking and Financial Services (BFS) business unit at Tata Consultancy Services (TCS). A Financial Risk Manager (FRM) from the Global Association of Risk Professionals, USA, and a Management Accountant from the Institute of Cost Accountants of India, Kolkata, he has over 20 years of experience across banking and IT industries. Ramachandrans areas of expertise include credit analysis, portfolio analysis, rating analysis, risk analysis, asset-liability management, and policy formulation. He works with the Risk Management Practice to support risk transformation projects across banks in the area of enterprise risk management and regulatory reporting, and in creating new offerings. He has worked with Centers of Excellence of third-party analytical solutions.


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