Almost all deposit-taking institutions, such as, banks and credit unions face one common risk, tenor mismatch, that changes in severity as the rates change. With increased volatility in rates, tenor mismatch can transform into basis risk, which can cause a liquidity event with potential to trigger bank failures. Even global systemically important banks have become vulnerable to interest rate volatility as was evidenced by doomed Credit Suisse. Increased interest rate volatility requires an overhaul of assumptions and calibrations of ALM systems. For instance, the assumption that term structure is flat or moves up or down in parallel movements is no longer relevant. According to a recent study by BBA, most ALM systems are underestimating the severity of tenor mismatch.

Today, banks need a partner who understands the importance of deposits, immunizes the balance sheet from interest rate volatility and mitigates the impact on business. Whilst the industry faces shrinking interest margins, our clients can be assured of accuracy in rates based on advanced estimation techniques. BankingBook’s proprietary asset liability management software solution, BB-ALM™, uses Machine Learning algorithm to slice and dice the deposits into core, volatile and interest sensitive cohorts, explaining more than 90% of the dynamic changes in the term structure of benchmark rates using Principal Component Analysis (PCA). It also sets up Treasury function as a profit center that frees up managers to add earnings performance.

BB-ALM™ is a powerful combination of 5 strategic models, covering Financial Planning & Analysis (FP&A), Asset and Liability Management, Strategic CECL/IFRS 9, Capital Stress Testing and Lifetime Income. BB-ALM™ provides coverage of the following risks:

BB-ALM™’s use of a single data source, offers two distinct advantages. Firstly, it reduces operating cost by cutting the expense of maintaining multiple large data clusters. For example, 10TB of data, a 200-node cluster costs almost $30,000 per month. Imagine running multiple clusters that consume same data but generate different reports. With BB-ALM, this cost is reduced at least by 4x as we use a single data source to produce the reports required by ALCO, risk and management committees. This also has an impact on FTE spend. Secondly, due to integrated reporting of 5-in-1 models, BB-ALM™ removes silos. Organizational corporate structures at banks are dominated, even inadvertently, by functional silos. Each of these functions own a different set of data and processing mandates. Since data processing is often done in a sequential order, any changes identified at one silo triggers reprocessing at another - inefficient, ineffective and hazardous to overall performance.

Collecting and reporting data is time consuming with time lags often in excess of 1 month. This delay in performance reporting and issue identification creates a significant source of surprise with missed opportunities to minimize losses and maximize profits.

Featuring high-speed cloud computing and a dashboard that provides a snapshot at 10,000 feet and drill down capability of discrete loan performance within the portfolios, BB-ALM™ allows CEOs and function heads to quickly identify and execute on tactics that enhance the loan book’s performance and promoting high performance across verticals. BB-ALM™’s integrated reporting facilitates on-going assessment and optimization of your strategy and plan, enabling you to continuously assess the impact of stressors on your funding strategy, contingency funding plan and key performance metrics and ratios, mitigating your liquidity planning processes.

No more potential for gaming of the system and reporting delays:

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