ALM product of the year: Oracle

Asia Risk Technology Awards 2019

Oracle Venky
Venky Srinivasan, Oracle Financial Services

With market and regulatory forces driving the integration of finance and risk, it is no longer just the chief financial officer who needs an accurate view of profitability, earnings stability and overall risk exposure of the balance sheet. Increasingly, the chief risk officer, treasurer and head of market risk also require this information.

By enabling financial institutions to measure and model every loan, deposit, investment and off-balance-sheet instrument individually, using both deterministic and stochastic methods, Oracle’s enterprise asset and liability management (ALM) system helps officers across the bank to gain a better understanding of the risks they have assumed and the sensitivity in economic conditions.

“Today, many banks have disparate systems and inadequately sourced data, where the combination of the two does not allow a bank to properly model the interest rate and liquidity risks on their balance sheet,” says Venky Srinivasan, group vice-president, and head of sales for Asia-Pacific and Japan, and the Middle East and Africa, at Oracle Financial Services.

“To ensure all risk is being captured, cashflow for every instrument should be calculated and aggregated together for the assets, liabilities and off-balance exposures.”

In addition, behavioural assumptions such as non-maturity core and volatile run-off assumptions, as well as prepayment and early redemptions, should be considered in the cashflow generation. “This allows for maximum detail when analysing the market value, economic value of equity, duration of equity, and interest rate and liquidity gap results on the balance sheet side, as well as the net interest income and profitability from the income statement,” says Srinivasan.

The Bank of China recently sought such a solution. It wanted an enterprise-wide ALM framework that could support high data volumes, computational complexity, and ensure speedy and accurate calculations. An essential requirement was the need to capture instrument-level characteristics of every customer relationship, so it could measure its interest rate risk accurately.

The firm was also having to deal with an increasing volume of regulatory guidance coming from the People’s Bank of China (PBoC), particularly the need to measure its exposure to liquidity and market risk correctly.

…you can analyse your current book of business and also use a plethora of forecasting methods to evolve the balance sheet over time
Venky Srinivasan, Oracle Financial Services

Oracle’s ALM solution helped the Bank of China to simplify maintenance and operations, and capture all customer relationship characteristics effectively. With this data, it was able to assess how customers behaved in different environments and then measure the impact on its bottom line.

The system also enabled the bank to model the exotic financial instruments it used accurately and consistently. These tools enable the firm to measure sensitivity to market and economic circumstances more readily, as well as to manage its exposures and test methods of mitigating excessive risks. The system has also enabled it to simplify the process for stress testing its balance sheet under alternative environments. Customised reporting capabilities have sped up reporting process for the PBoC.

Historically, approaches to ALM at the business-line level have been static and reactive, without much alignment with the wider bank strategy. Often, this has resulted in an accumulation of poorly originated exposures, leading to strategic imbalances and, subsequently, to an increase in the cost of managing resultant risks. By helping to align the asset and liability sides of the business, Oracle enables banks to reconcile the goal of profit maximisation with balance sheet optimisation.

Greater transparency

This approach also provides greater transparency on the overall funding mix, and the incremental values and risks of different deposit products, as well as of customers, all of which contributes to a better picture of a bank’s overall liquidity profile. Furthermore, the bank can be assured that deposits are not mispriced when they are used to fund riskier investment activities, thereby simultaneously lessening regulatory risk.

Oracle’s ALM calculates and stores a variety of financial risk indicators, including: value-at-risk, earnings-at-risk and probability distributions; static and dynamic market value, duration and convexity; static and dynamic gap (based on repricing and liquidity); and income simulation.

Income cashflow is available on an actual as well as a transfer-priced basis for any number of predefined rate paths. Users can control the levels at which results are aggregated, both in terms of time frequency (modelling buckets) and product categorisation.

“The application supports deterministic and stochastic processing for both static analysis and dynamic new business, which means you can analyse your current book of business and also use a plethora of forecasting methods to evolve the balance sheet over time to get a view into the profitability from a net interest income, net interest margin and earnings at risk perspective,” says Srinivasan.

Scalability and traceability

Oracle’s ALM solution is engineered to be scalable and perform well, with large data volumes offering full traceability and auditability back to instrument-level cashflow. A single cashflow engine is used for multiple risk and finance use cases, including fund-transfer pricing (FTP), liquidity risk, ALM, and calculations to meet International Financial Reporting Standards 9 and 17.

Oracle’s ALM approach steers both the trading and banking book through several FTP techniques, designed to arrive at the target balance sheet profile. The application uses FTP as a dynamic tool to provide an incentive for growth or to divest certain products, thereby actively contributing to setting the target profile of the banking book. The solution also assists the ALM function to manage compliance with liquidity coverage ratio, short-term liquidity metrics, funding concentration and other regulatory requirements.

An Asia Risk Awards judge says: “Oracle’s ALM system derives benefits from an integrated accounting heritage, with modules to meet today’s regulatory requirements, such as IFRS 9 and current expected credit loss. It offers a unified and comprehensive data strategy, and strong scenario simulations and economic forecasting.”

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