Leaping beyond adopting traditional ALM automation, the bank has chosen to approach to embrace change through digital disruption and transformation

On 15 Oct, Malaysia’s Alliance Bank announced it has implemented a new asset and liability management (ALM) solution to  bolster its risk monitoring and oversight for its interest rate risk and liquidity risk management.

By enabling advanced stress testing, scenario analysis, and predictive analytics capabilities, the bank announced it is now able to make faster and more accurate business decisions in response to a changing interest rate environment, and to gain competitiveness.

The cloud-centric ALM solution chosen by the bank features robust daily-reporting capabilities and advanced tracking of depositor concentrations and liquidity analytics that allow the bank to manage liquidity based on immediate funding needs and fully automate 90% of processes. This is in alignment with its commitment to comply with Bank Negara Malaysia’s (BNM) Interest Rate Risk on Banking Book (IRRBB) and liquidity guidelines.

Other benefits promised by the new ALM system include:

  • A tenfold improvement in system scalability, transaction per second, and 24/7 system availability and uptime
  • A more-than-10% savings on operational costs, manpower costs, and time spent on production processes
  • Reductions in the average time needed for risk assessment and compliance to less than one day
  • Minimization of time-consuming, error-prone tasks — this will allow staff to focus on more strategic and value-added activities

Said the bank’s Group Chief Risk Officer, Jacob Abraham: “From a cost-efficiency standpoint, this streamlined data sharing, reduced manual interventions, and heightened operational efficiency is forecast to help us realize an annual savings.”

According to Wilson Yap, Director and Head of Risk Banking Solutions, SAS Institute, the firm providing the ALM solution: “Due to complex challenges in the industry, ALM processes must come with a high degree of granularity and transparency,” where implementing a comprehensive package of analytical, computational, and governance capabilities can deliver “a broader balance sheet management process that integrates the whole spectrum of risk dimensions.”