this current environment, the issue of financial literacy from these perspectives has become more urgent, particularly in the emerging market economies of asia, where household consumption is becoming an important driver of growth. the expanding cumulative domestic market in asia is becoming massive, a factor that has been important in facilitating intra - asian trade and thus driving the economic integration of the asian region. this trend has the potential to contribute to the rebalancing of global growth and thus to address the structural imbalances currently prevailing in the global economy. households therefore need to be financially strong if this trend is to be sustainable. financial literacy will allow households to have the increased confidence to make sound decisions regarding their consumption expenditure. of importance to central banks is that consumer credit remains within prudential limits and do not impose undue risk to the consumers that can often result in financial stress. consumers not only need to be able to assess their capacity for expenditure, savings and debts but also have to be able to select from the array of financial products and delivery systems that will best meet their requirements. households need also to be aware of and understand the financial risks associated with their transactions. greater financial literacy can contribute to mitigating these financial risks. the growth in household debt is an increasingly evident phenomenon in asia. over the period of 2000 to 2004, the volume of consumer loans across seven major asia pacific economies grew at an average annual rate of 9 percent, relative to total loan growth of 5. 2 percent and corporate credit growth of 2. 6 percent. the risk emerges when debt reaches a level where it cannot be sustained, and ultimately leads to increased financial stress. it is therefore important that borrowers are financially savvy to manage financial risks in a proactive and constructive manner. the environment we are operating in is becoming increasingly challenging. individuals may not know where to seek information or do comparative shopping. the aggressive marketing by financial institutions may lure [UNK] borrowers into financial transactions that cannot be sustained in the longer term. a number of regional economies have seen aggressive marketing of credit cards, that have led to situations where financial institutions were eventually compelled to write - off many bad loans. the observation from surveys is that many consumers do not fully understand relatively simple financial calculations, and hence do not realise the risks involved. for some countries, the cost of borrowing may increase substantially depending on the prevailing conditions. this may result in difficulties in servicing the debt. also this would depend on the extent of the household gearing. for asia pacific economies, this

complicated operation. they are typically greater when associated with innovation and they grow as product structures become more complex. we all need to recognize this. regarding models, aside from the technical parts, it ’ s important to consider the less quantitative. for instance, are the inputs sound? are the model parameters based on sufficiently robust and accurate data? are the assumptions reasonable? one needs to understand the business and risk management principles, but that does not require a “ quant. ” in modeling, “ gigo ” - garbage in, garbage out - always rules. data integrity is growing in importance in effective risk management. in today ’ s world of credit risk models, especially for centralized underwriting in areas such as consumer, mortgage, and small business credit, the responsibilities of data input may reside with the lending officer. to ensure effective underwriting, the culture and incentives for loan officers should support accountability for valid information going into a model. in the “ old days ” when individual loan officers made credit decisions, any weaknesses in underwriting were confined to that lender ’ s portfolio. it was the responsibility of loan reviewers to identify those weaknesses before losses became extensive. today, the responsibility for effectively predicting defaults and loss given default resides with the senior credit officer responsible for the credit scoring model. when the underwriting results are then tested for reliability, it is critical to identify the root cause of errors due to model specifications and changes in customer behavior. the risk of centralized, model - based underwriting is that errors are no longer limited to the portfolio of a single loan officer. rather, model errors can create significant systemic risks across that loan product portfolio. we are still trying to learn how to estimate these types of risks. in our current regulatory efforts to develop internal rating - based capital standards for credit risk, we find that simply identifying and describing “ minimum ” data requirements can be a challenge. what is adequate and robust for a given purpose and what is not? each company ’ s practices are unique - as they should be. we do not wish to create the moral hazard and greater systemic risk associated with a highly specific, government - dictated procedure to measure risk. rather, we want the discipline that can be gained from requiring that the input data and the parameters used for regulatory purposes are as much as possible - the same as those used for business purposes, so that they can be markettested. differences among model results will occur, but both management and regulators must decide what is good enough for their respective purposes