Author: Mel Chamber

BNF Bank announced a robust financial performance for the year 2023, recording a profit before tax of €13.0 million – a 6.75% increase over 2022.

Higher profitability in 2023 was primarily due to increased net interest income of €32.5 million (2022: €25.8 million). In addition to net interest income, net fees and commission income and other ancillary income contributed to a net operating income for 2023 of €36.2 million (2022: €30.1 million). The Bank’s cost-to-income ratio reflects the technology investment the Bank is undergoing, which will be in the Bank’s long-term financial interest. The cost-to-income ratio stood at 65.1% for 2023 (2022: 61.7%). In 2023 the Bank wrote back expected credit losses (‘ECL’) of €0.4 million (2022: ECL write-back of €0.7 million).

Net lending to customers increased by 5.2% to €950.3 million, whilst the percentage of credit impaired lending was contained at 2.65% (2022: 2.63%). The Bank’s Capital Adequacy Ratio stood at 19.3% (2022: 19.6%) and the Common Equity Tier 1 Ratio stood at 14.6% (2022: 14.6%), both being well above overall capital requirements and supervisory pillar two guidance. The Liquidity Coverage Ratio (‘LCR’) as of 31 December 2023 was 335.3% (2022: 237.7%), and the Net Stable Funding Ratio (‘NSFR’) was 140.2% (2022: 139.8%).

Following the conclusion of the reporting period, the Board of Directors is proposing a net dividend of €0.045 per nominal share of €0.7552, totalling €4,489,300, to be distributed to shareholders subject to regulatory approval and will be presented for resolution at the AGM.

BNF’S Chief Financial Officer, Mark Micallef said that in 2023, BNF Bank successfully concluded its Vision 2023 Strategy, achieving targeted growth milestones, completing the licensing process for a UK third-country branch, and fulfilling its capital plan objectives. “The robust financial performance in 2023 is a reflection of the Bank’s customer focus and was sustained by steadfast adherence to focused and rigorous risk management practices.”

David Power, CEO of BNF Bank, commented, “In 2023, BNF Bank maintained its pivotal role as a cornerstone of the local economy and as a trusted financial ally for both individuals and businesses. This achievement is a testament to the unwavering dedication and perseverance of our team.”

He continued, “As we navigate the evolving financial landscape of 2024, I am confident that we will rise to the challenge with resilience, strategic planning, and ambition. Our Vision 2026 Strategy remains firmly on track, and we eagerly anticipate achieving our milestones in both business growth and digital transformation.”

BNF Bank’s Annual Financial Report for 2023 may be downloaded from www.bnf.bank/investor-relations

For yet another year, Bank of Valletta has renewed its commitment towards Earth Hour by symbolically switching off the lights on the facades of some of its main premises, including its BOV Centre and Premium Banking Centre in Santa Venera, Zachary Street Offices in Valletta, as well as the Chairman’s Office situated at the House of Four Winds, also in Valletta.

For the eighteenth consecutive year, World Wildlife Fund (WWF), the organiser of this worldwide movement, issued an invitation for participation in the ‘lights off’ movement to raise awareness on climate change and nature distress. During last year’s event, around 410,000 hours were given back to the planet across 190 countries, with year’s event predicted to be even bigger.

Speaking about the Bank’s role in this event, Ernest Agius, Chief Operations Officer at Bank of Valletta explained that “Earth Hour is an opportunity to create greater collective consciousness about the importance of safeguarding our environment. At Bank of Valletta, our commitment goes deeper than the symbolic gesture. In fact, we consider the green stakeholder to be key for both our CSR programme and our commitment to the Environment, Social, and Governance (ESG) principles. We have continued to undertake a series of environmental initiatives aimed at protecting our environment, while spurring the local business community to act in a responsible manner”. In this respect, he mentioned the Bank’s 500+ PV panels across different sites, double glazing windows offices, and the replacement of air condition units with more efficient ones that produce less harmful refrigerants.

The refurbishment programme currently underway across the Bank’s branches and other offices is already harnessing the concept of environment-first. All-natural and fast-renewing materials are being used, together with LED lighting and recyclable flooring material.

“This concept has also driven our ongoing works at BOV Centre, redesigning the working environment of our Head Office into open-plan designs that allow more natural light and fresh air. The Bank also has two large water reservoirs with a combined estimated capacity of 600,000 litres. This second-class water is used for toilet flushing bowls and firefighting water tower,” explained Mr Agius. The amount of rain water that is typically harvested by the rainwater harvesting system as well as condensation from air-conditioning Units at BOV Centre is over 4,000 cubic metres a year.

Batteries are currently being collected for Hospice under the GreenPak campaign.

Given the permanent nature of the material, metal requires less intervention for it to be recycled as it keeps its material properties. An estimated 15,000kg of metal has been sent for recycling and reuse by the Bank.

Continuous efforts are also made throughout the year to raise awreness among employees to increase their commitment towards the environment, encouraging waste separation and providing regular educational tips about how one can take care of the environment in the long-term by making small adjustments to one’s lifestyle. “Cumulative small steps lead to bigger and more meaningful actions,” concluded Ernest Agius. “For us, this is the spirit of Earth Hour, which we try to live on both an operational and strategic level.”

Bank of Valletta hosted a financial education seminar highlighting important aspects of the local economy and investment basics with a view of helping the public make informed decisions when dealing with their financial wellbeing. The Bank is investing heavily in the financial literacy of the communities it serves. As explained by BOV CEO Kenneth Farrugia, “We feel it is our responsibility to disseminate financial knowledge and help the public to become better informed, so that they can choose financial products that really suit their requirements”. As a Bank of systemic importance, with a legacy of fifty years operating across the islands, the Bank has taken on board the responsibility to support customers in navigating the financial services world, so that they can make the most of the financial options available at different stages of their lives.”

Malcolm Bray, who heads the Bank’s Economic function, gave an overview of the local economic landscape. He highlighted several variables like the sectoral diversification achieved over the past decades, the record low unemployment rate, coupled with the expected easing of inflationary pressures, the record year for tourism, and the ongoing growth in residential house prices. “The present favourable economic conditions are also supported by the low pass-through of ECB rates to domestic lending rates. Indeed, household rates and corporate rates are currently the lowest among euro area countries,” he explained. Mr Bray also referred to the life cycle theory of consumption to highlight the critical importance of saving during our working age so that we can maintain existing consumption patterns once we retire when income decreases. 

Bond and Equity Markets were particular areas of interest in the information session. Attendees were given an overview of bonds, how they work, and the main factors that affect the bond market, such as inflation, interest rates, credit rating, liquidity, and bond maturity. An overview of the local Equity Market, both by sector and industry, was also put forward, with particular emphasis on how shares entail more risk than bonds but entitle the holder to become part of the ownership of a company, with the possibility of earnings coming from dividends or increases in share price. Informative statistics about the local equity market showed a predominance in Malta by finance and real estate.

The public’s response to the financial education seminar shows that there is a growing demand in the market for further knowledge in finance, an area that Bank of Valletta is keen to invest in. The personal customer segment is showing particular interest to these sessions, with financial skills and investment basics at taking centre stage. The Bank encouraged anyone interested to participate in similar future evets to approach the Bank’s Business Development Unit by calling 22751122.  Satisfaction with participants’ response to the content was expressed by Kenneth B Micallef, who heads the Bank’s Business Development arm, as well as Clayton Scicluna, one of the Bank’s Lead Portfolio Managers and David Pace Ross, Senior Manager within the Bank’s Stockbroking and Capital Advisory arm who presented the content to participants.

KAIZEN™ in Maintenance focuses on equipment efficiency and maintenance improvement through an integrated optimisation model with production – Total Productive Maintenance.

Switching From Reactive to Predictive Maintenance

Maintenance is one of the most significant business areas in an industrial company, with a direct impact on all stages of the production process. Industries tend to invest in high-quality equipment and machinery with a long-life cycle which must be managed and preserved effectively. Efficient maintenance ensures the continuous flow of the production process, allowing excellent operational results to be obtained in the form of cost reduction and increased productivity.

Considering that maintenance costs represent on average, 15 to 40% of the operational costs and planned stoppages result in a 5-10% loss in equipment efficiency, it is necessary to apply a model with the clear objective of reducing these and other relevant indicators like Mean Time Between Failures (MTBF), Mean Time to Repair (MTTR) and Overall Equipment Effectiveness (OEE). The implementation of Total Productive Maintenance (TPM) has resulted in successful cases in several industries, proving to be the approach that addresses all variables that affect equipment performance.

TPM is an approach based on a balance between planned and autonomous maintenance interventions with the objective of achieving an ideal production environment, seeking to maximize efficiency, based on a strong alignment between the operational teams – production and maintenance.

Dealing with unplanned downtime should be seen as a priority for organizations. In the automotive industry, each stop costs about $1.3 million per hour, which is represented by lost production time and, consequently, lost sales.

Despite the significant impact of downtime, 70% of companies still don’t have visibility into when their equipment should be stopped and intervened to avoid unplanned stops.

Only 26% have adopted a predictive maintenance strategy based on data and algorithms that make it possible to identify the optimal moments for equipment maintenance with greater precision.

Efficient maintenance teams are prepared to solve the challenges that arise. Still, they must also have the ability to anticipate future challenges by finding the right balance between working on resolving malfunctions – corrective maintenance – and preventing them – preventive maintenance. An efficient strategy to optimize the performance of maintenance teams is to evolve the TPM model in order to reduce the need to perform reactive maintenance while giving priority to predictive maintenance.

What are the three main maintenance strategies (reactive – preventive – predictive)

Reactive maintenance was the most common approach over a long period of time in different sectors of the economy. In a general way, it is about solving problems after failures occur. Following this approach, maintenance teams only act when called upon, and the stock of spare parts is small, only replenished with ad-hoc purchases.

When the organization opts for a reactive maintenance strategy, unexpected breakdowns force equipment downtime, reducing the availability of machines. Unplanned downtime can result in idle employees, production line stoppages, missed deadlines or late deliveries, the need to incur overtime, and energy overconsumption.

The occurrence of a failure in a single component can also compromise the condition of numerous other components inside the machine, increasing the time needed to repair them and leading to downtime costs for the organization and its repercussions.

While reactive maintenance is an approach to resolve failures and reset conditions to operate correctly, preventive maintenance seeks to prevent failures from happening, relying on a periodicity to check the need for maintenance or to effectively perform maintenance tasks on equipment.

Preventive maintenance is, in its definition, the set of activities carried out regularly (according to a planned schedule) to maintain equipment’s conditions and operational status.

Predictive maintenance has the main objective of formulating a forecast based on data and algorithms to find out, with high precision, when equipment maintenance is needed. The implementation of this approach consists of constantly monitoring the conditions of the equipment throughout its normal operating process to predict and detect potential problems and correct them promptly before they result in failures. It seeks to respond to two significant problems associated with organizational maintenance models:

• The high costs associated with excessive periodic maintenance – are often unnecessary.
• The high costs associated with an unplanned stoppage – which is often avoidable.
  

Predictive maintenance differs from preventive maintenance in that it is based on the actual condition of equipment and not on average or expected life statistics. This methodology tries to detect failure patterns and anomalies, learn from them, and then predict future failures of machine components so that they can be replaced before they fail.

The ‘predictive’ component of predictive maintenance stems from the goal of predicting the future trend of the equipment’s condition and it uses principles of statistical process control to determine at what point in the future maintenance activities will be appropriate.

In this strategy, repairs occur whenever the analysis of the equipment’s condition makes it foreseeable. Maintenance teams work on-call and have well-structured routines for lubrication, replacement of worn parts, inspection/measurement, and statistical analysis of performance. Spare parts stock management is based on anticipation based on the condition and/or forecast of a possible failure.

The image below shows the time distribution with comparisons between different maintenance approaches.

The goal and potential impact of predictive maintenance

Predictive maintenance should be implemented in equipment that has a critical operational function, has failure modes that can be avoided with regular maintenance and has a failure probability that increases with time or use. Equipment that has random failures that are not maintenance-related, and that do not perform a critical function, should be disregarded in this scope.

The KAIZEN™ approach to implementing predictive maintenance contains four steps:

1. Selection of components and control parameters: it is crucial to start with critical assets to improve the functioning of this specific equipment. At this stage, there’s also the criteria definition, designed to prioritize equipment based on safety & environment, quality, availability, and process speed. The control parameters are also studied and defined in this particular step.
2. Definition of diagnostic methods and baseline values: equipment condition assessment can be done through periodic (offline) or continuous (online) monitoring of the equipment’s condition. This step aims to specify how to perform instrumentalized and non-destructive tests and inspections and define the baseline values. Most predictive inspections are performed while equipment is in service, thereby minimizing disruption of normal system operations.
3. Definition of suitable technologies: the predictive analysis utilizes various statistical and machine learning algorithms to provide recommendations and answers to questions related to what might happen in the future. Since it is a probabilistic method, the accuracy of the outcome depends on the data quality. There are different technologies to use, like computerized maintenance management systems, vibration analysis, remote visual inspection, acoustical analysis, infrared monitoring and analysis, oil analysis and model-based condition monitoring.
4. Predictive intervention: this step encompasses the design of the plan with all the information, such as which components are indicated for this approach, what are the control parameters for each piece of equipment, what are the reference values, what technologies are to be applied, and also what are the inspection points?

The main advantage of using this strategy is improving the operation of critical equipment, which will result in less need for corrective maintenance and generate savings in terms of time and money due to unplanned work avoidance. The continuous state of organization and control, which is the basis for preventive (periodic or predictive) maintenance, maximizes the availability and reliability of equipment and ensures processes at the lowest cost, allowing good decision-making for the management of assets in the long term.

Switching from reactive to predictive maintenance

Today, maintenance must adopt a system more focused on prevention and less on the reaction and resolution of malfunctions; this strategy must be implemented in a global way and must necessarily be integrated with production.

The implementation of a model based on Total Productive Maintenance principles, through the application of predictive and planned approaches, which will optimize spare parts stock management and reduce equipment downtime, while maximizing efficiency, is the most effective solution to optimize maintenance processes. This new paradigm can take the organization from a repair and fault management strategy to an integrated maintenance and production management one, focused on preventing equipment anomalies.

The ultimate goal of Predictive Maintenance is to perform maintenance at a scheduled point in time when the maintenance activity is most cost-effective, and before the equipment loses performance within a threshold, reducing maintenance costs, increasing equipment availability, equipment lifetime and safety.

Impact of predictive maintenance on the overall equipment effectiveness

By implementing predictive maintenance, teams will be able to gain insights into the need for maintenance before a significant downtime occurs – keeping equipment running. This makes the companies maintain not only high production time but also superior performance levels. This adoption intends to bring about an increase in the availability of resources, considered a key variable for the success of the organization, and for the OEE calculation.

The application of the predictive maintenance strategy will increase the organization’s overall OEE as it will allow preventive maintenance tasks to be carried out just before failures occur, drastically reducing both the planned stoppages of periodic inspections and the unplanned stoppages resulting from potential breakdowns.

Top challenges faced while implementing predictive maintenance

Typical maintenance challenges involve for instance the lack of resources, funding, or training. However, recently, (and following the same logic as other business areas), maintenance has faced a paradigm shift as digitalization and innovation bring new variables to the equation.

Due to the need to remain competitive, organizations cannot neglect this aspect, and the paradigm must evolve. More companies are focusing on predicting possible future defects and channelling less effort into solving challenges at the moment they arise.

To develop predictive maintenance strategies, Industry 4.0 and the application of digital tools can also be differentiating factors.

There are solutions like:

• Data analytics and all that can lead to predictive maintenance and conditioned-based maintenance
• Digital twins and simulation improve machine reliability right from the design phase
• Augmented reality increasing global remote expertise collaboration in maintenance interventions
• Maintenance 4.0: cyber-physical systems
• Real-time machine data availability (process and machine parameters

Digital transformation and innovation can play a key role in maintenance activities and show special relevance in the implementation of the predictive maintenance strategy. Only organizations capable of embracing these methodologies and leveraging them will achieve the much-desired transition from the current paradigm of ‘solving’ to the vision of ‘preventing’.