View source for Advanced Measurement Approach (AMA)

'''Advanced Measurement Approach (AMA)''' is one of three possible [[Operational Risk|operational risk]] methods that can be used under [[Basel II]] by a bank or other financial institution. The other two are the [[Basic Indicator Approach]] and the [[Standardized Approach]]. The methods (or approaches) increase in sophistication and [[Risk Sensitivity|risk sensitivity]] with AMA being the most advanced of the three. Under AMA the banks are allowed to develop their own [[Empirical Method|empirical model]] to quantify required capital for operational risk. Banks can use this approach only subject to approval from their local regulators. Once a bank has been approved to adopt AMA, it cannot revert to a simpler approach without supervisory approval.<ref>Definition - What is Advanced Measurement Approach (AMA)? [https://en.wikipedia.org/wiki/Advanced_measurement_approach Wikipedia]</ref>


'''Qualifying Factors for Advanced Measurement Approach (AMA)<ref>Best Practices to Qualify for AMA [https://www.metricstream.com/insights/AMA_Roadmap.htm Metric Stream]</ref>'''<br />
AMA’s qualifying factors makes a bank’s risk assessments more forward-looking and reflective of the quality of control and operating environments. Directives imply that any [[Operational Risk Management (ORM)|Operational Risk Management (ORM)]] tools / systems aiming to qualify for AMA status, must be aware of, and be closely aligned with, the business strategies of the firm and the external factors that could impact its risk profile. Few of best practices to qualify for AMA are:
*Integration: By adopting an integrated operational risk framework, companies can ensure that all ORM initiatives are sustained and aligned with the corporate strategy elements & methodologies ([[RCSA (Risk Control Self Assessment)|RCSA]] & [[Key Risk Indicator (KRI)|KRI]]) used to measure risk and operate as a natural system. It should also support evidential data (Loss Events) of the organization, which can be furnished to the model in a useable manner.
*Evolved Scenario Analysis: [[Scenario Analysis|Scenario analysis]] broadens the data set to understand and gauge the operational risk events on different plausible scenarios. It gives an opportunity to think outside the box and helps in making AMA futuristic. This is a key to organizational efficiency and calculating economic capital.
*Strategic Risk & Capital Allocation: When designing an ORM structure, the bank’s overall risk scenario should serve as a guideline. This includes initiatives like laying down a hierarchical structure that leverages current risk processes, developing risk measurement models to assess regulatory and economic capital, and allocating economic capital vis-à-vis the actual risk confronted. Centralized aggregation of operational risk information collected via various self assessments across the organization, further, provides useful insight for the desired hierarchical structure. The implementation of these concepts allows risk to be handled consistently throughout the organization
*Correlation & Dependency: Even though all the potential loss events don’t happen at the same time, under stress conditions like 9/11, uncorrelated risks become correlated. Within the capital model, the bank should look to identify and display the correlated and uncorrelated expression of exposure. This will allow dependence between specific risk event categories in the context of the business, product, channel and budget to be dimensioned.
*Risk Adjusted Return on Capital: The bank should take on the initiative of Risk Adjusted Return on Capital and translate that to internal initiatives that allow the management to be more reactive to potential events. This should, however, be done in a balanced manner so that the executive decisions are supportive of a wider scope that accepts balanced benefit of cost.

Today, AMA is considered the most scientific method of the measurement of Operational risk in terms of continuum sophistication and risk sensitivity. The loss model approach leveraged by AMA is mostly used by the internationally active banks in developed economies. As put by one of risk experts, “The Actuarial loss model approach has become accepted by the industry as the generic AMA for the determination of operational risk regulatory capital for the new Basel II accord. The important step in the measurement of operational risk is the collection of relevant internal loss data for operational risk for a period of at least five years which is comprehensive, relevant and clearly linked to bank's current business activities and future vulnerabilities to risks.”


Benefits of the Advanced Measurement Approach<ref>Benefits of the Advanced Measurement Approach [https://www.bis.org/ifc/publ/ifcb33p.pdf BIS.org]</ref><br />
One of the most visible effects of implementing an advanced approach for operational risk management is the positive impact on reputation and perception by stakeholders. More sophisticated and advanced [[Risk Management|risk management]] certainly sends a clear message of solid and sound risk management to shareholders, clients, rating agencies and the market. This reassurance is extremely important and gives comfort to stakeholders, especially in times of economic turbulence and uncertainty. 

The use of internal models to calculate capital requirements under the AMA may also lead to a reduction in regulatory and economic capital. Capital is based on risk exposures and not on income levels as is the case for the more basic approaches. 

The most significant benefit, however, is that implementation of the AMA leads to improved risk management processes and more sophisticated risk measurement mechanisms. In many cases advanced risk measurement techniques (such as risk scenarios and the use of external data) were put in place earlier than originally anticipated to facilitate the successful implementation of an AMA system. Better-quality risk management ultimately protects the bank’s value and the interests of stakeholders. 

The AMA implementation has also resulted in improved relationships between deployed risk managers and centralised (Group function) risk specialists. Deployed risk managers had to take on extensive responsibility for the implementation of all operational risk measurement and management components in their business units. Guidance, frameworks and policies for these implementations were developed by centralised risk specialists, and therefore close cooperation between Group functions and business risk managers was required.


===See Also===
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