Indian Housing Finance . . And The Asset Liability Management "Conundrum" . .

Housing Finance Companies are indirect lenders and lack access to stable funding from CASA deposits thereby making them more vulnerable to market dynamics . .

Liquidity is an institution’s ability to meet its liabilities either by borrowing or converting assets.  Asset Liability Management (ALM) addresses the risk faced by a bank due to a mismatch between assets and liabilities due to liquidity.  Apart from liquidity, a bank may also have a mismatch due to changes in interest rates, as banks typically tend to borrow short term (fixed or floating) and lend long term (fixed or floating).

Over the last few years the financial markets worldwide have witnessed wide ranging changes at fast pace.  Intense competition for business involving both the assets and liabilities, together with increasing volatility in the domestic interest rates as well as foreign exchange rates, has brought pressure on the management of banks to maintain a good balance among spreads, profitability and long-term viability.

These pressures call for structured and comprehensive measures and not just ad hoc actions.  Banks must base their business decisions on a dynamic and integrated risk management system and process, driven by a comprehensive ALM strategy. 

Like any other financial institution, Housing Finance Companies (HFCs) are exposed to several major risks in the course of their business – credit risk, interest rate risk, foreign exchange risk, equity and commodity price risk, liquidity risk and operational risks.  Majority of HFCs are indirect lenders and lack access to stable funding from CASA deposits thereby making them more vulnerable to dynamics of the market. 

HFCs create multiple fund sources.  Borrow money from banks – term loans – and re-lend them, thereby creating long term assets with short-to-medium term liability.  When the term loan matures it may be re-priced thereby creating a potential ALM mismatch.  Raise external commercial borrowings in USD or any other currency, potentially creating foreign exchange risk and subsequent ALM mismatch.  Though, technically, these are secured loans, the collateral is not easily liquefiable, thereby again creating potential for ALM mismatch that may arise from loan defaults and worse in case of default of loans given for under-construction property.  Rising competition also brings threat to loan assets in the form of balance transfers. 

ALM directly or indirectly impacts key ratios for an HFC.

ALM process rests on three pillars – ALM Information System, Management Information System, and Information Availability, Accuracy, Adequacy and Expediency, which in turn are functions of people process and technology.

Although HFCs do file ALM status periodically, as per regulatory norms, the calculation is based on a deterministic approach.  Stochastic approaches have not found their way into the system. 

Interest Rate Risk lies at the core of ALM and is studied from two perspectives: economic value and earnings.  Sensitivity of Economic Value of Equity (EVE) arising from market shifts helps observe Fair Value Volatility.  Modelling this volatility of earnings under different scenarios, using advanced simulation techniques, is essential to study the impact on the future balance sheet and income.  Scenarios Analysis must then be fundamentally extended to examine, manage and stress the structural liquidity gap, Liquidity Coverage Ratio (LCR), Net Stable Funding Ratio (NSFR), and the liquidity survival horizon.

Answer lies in an integrated risk management framework that allows for strategic planning, a state one arrives when the budgeting process tactics and ALM are in complete control.

Automating the ALM process of data collection and MIS may help it become more real time business intelligence solution.  In addition to staying on top of market trends, HFCs need to make conscious efforts to develop, design and deploy stochastic models, leveraging macroeconomic data, indices, market data and other alternative data.  

Leveraging the power and speed of big data, advanced analytics and intuitive yet powerful visualizations these stochastic approaches ideally should be able to:
•           Analyze and predict the impact of market dynamics on assets and liability
•           Able to differentiate the impact leading to prescriptive corrective measures
•           Adapt and evolve with trends, both technological and business
•           Continuously improve and learn

Developing such capabilities would provide an edge to the organization in this hyper competitive business of borrowing and lending.  Stochastic approach would help HFCs mitigate ALM risks, efficiently deploy capital and execute wiser hedging strategies.