Few letters possess the combination of simplicity, historical depth and conceptual flexibility of X. It occupies a distinctive position in the alphabet: visually economical, immediately recognisable and capable of serving as both a letter and a symbol. Across different periods, it has represented a sound, a number, an unknown quantity and a means of expressing relationships that have not yet been fully determined. Its significance has never depended upon a single meaning. Rather, X has acquired different functions as successive cultures, disciplines and institutions have found new uses for its compact form.
The history of the letter extends into the ancient Mediterranean world. The Latin alphabet developed from western Greek writing, probably through Etruscan intermediaries and the form and sound associated with X emerged through a complex process of alphabetic adaptation. The Greek alphabet itself had developed through the adaptation of a Phoenician-derived writing system. In the western Greek traditions from which the Latin alphabet descended, the crossed form was associated with the sound represented in Latin by X, broadly the consonant combination heard at the end of words such as fox. The relationship between the different Greek letter forms, their sounds and their Phoenician antecedents is complex; it is best understood as a history of adaptation rather than a single, uncomplicated act of invention.
The Romans incorporated X into their alphabet, preserving a form that has remained remarkably stable through subsequent centuries. Its familiarity today conceals the historical processes through which the Latin alphabet acquired its distinctive characteristics. A sign that now appears entirely ordinary is the product of cultural contact, linguistic change and the gradual standardisation of writing.
This history provides an appropriate starting point for considering X in a contemporary institutional context. The letter has endured not because it possesses one universal meaning, but because its form has proved capable of serving different purposes without losing its identity. It can be recognised independently of the particular function it performs. Its meaning emerges from the context in which it is used.
The application of X® by GENERAL INTELLIGENCE PLC as an artificial intelligence consultancy framework for building societies should be distinguished from the history of the letter itself. The historical record provides context for the choice of a remarkably compact sign; the consultancy framework gives that sign a specific contemporary purpose. The significance of the latter lies not in an assertion that the historical letter inherently represents artificial intelligence, but in its use to identify a comprehensive approach to institutional intelligence.
X AS A SYMBOL OF UNKNOWN QUANTITIES
One of the most consequential developments in the history of X was its adoption in modern mathematical notation as a representation of an unknown quantity. Although the origins of this convention have been debated, its influential establishment is associated with the work of René Descartes, particularly La Géométrie, published in 1637 as an appendix to his Discourse on the Method.
Descartes helped establish a notation in which letters near the beginning of the alphabet, such as (a), (b) and (c), represented known or given quantities, while letters near its end, including (x), (y) and (z), represented unknowns. The precise reason for his selection of the individual letters is not certain. What matters historically is the effectiveness of the resulting convention: an unspecified quantity could be represented explicitly, related to other quantities and investigated through a systematic method of reasoning.
The development of algebraic notation was more than a typographical convenience. It made relationships easier to express and manipulate without requiring every problem to be described entirely in words. It helped mathematics move towards a more general language in which different problems could be examined through common structures, regardless of the particular quantities involved.
X consequently became associated with the unknown, but not necessarily with something permanently unknowable. In algebra, an unknown can be investigated, constrained, related to other quantities and ultimately determined when sufficient information and an appropriate method are available. The letter represents a question within a larger structure of relationships.
This is a useful distinction for institutional intelligence. An organisation is continually confronted with quantities, relationships and future conditions that cannot be known with certainty at the point of decision. The task is not to pretend that every unknown can be eliminated. It is to establish what can be understood, what evidence is required, which relationships matter and how the resulting knowledge should inform action.
For a building society, the unknown may concern a future movement in interest rates, a change in members' savings behaviour, the ability of households to sustain mortgage payments, the emergence of a regional economic difficulty or the consequences of a technological disruption. None can necessarily be resolved through a single calculation. Each may, however, become more intelligible when examined in relation to other relevant information and the institution's wider circumstances.
The mathematical association of X therefore offers a useful conceptual parallel: an unknown should be neither ignored nor mistaken for an answer. It should be made explicit, examined rigorously and considered within the structure of relationships that may help explain it.
X, INTERSECTION AND RELATIONSHIP
The visual form of X also carries a long-standing association with crossing and intersection. Its two diagonal strokes meet at a single point, creating a simple form that can be recognised across different settings. Yet the letter itself, the mathematical multiplication sign and other cross-shaped marks are distinct symbols, even where their appearances are similar. Their histories and conventions should not be conflated.
The wider significance of intersection is nevertheless relevant to the study of complex institutions. Many of the most consequential organisational questions arise not from a single activity, but from the relationship between several activities that are usually managed separately. A change in one part of a system may alter the conditions in another; a decision that appears reasonable within one function may have unintended consequences for the institution as a whole.
A building society provides a particularly clear example. Savings and mortgages are distinct products, but they are connected through the balance sheet. The behaviour of savers influences funding; the availability and cost of funding influence lending; lending decisions influence asset quality and capital; and the wider economic environment affects both sides of the institution. The relationship between these activities is fundamental to the society's financial condition.
The same principle applies to members and the institution. A mortgage is a lending relationship, but it also concerns a household, a property, a stream of future commitments and a member's long-term financial security. A savings account is a financial liability for the society, but it may also represent an individual's precautionary resources or plans for the future. Understanding either relationship fully requires more than examining an account or transaction in isolation.
The significance of the X® framework lies partly in this system-wide perspective. It considers whether artificial intelligence can improve the institution's ability to understand relationships across its activities, rather than merely increase the efficiency of individual functions. The objective is to connect information and expertise where their combined significance exceeds that of the separate components.
X AS A DISTINCTIVE IDENTITY
Throughout its history, X has accumulated a diverse range of uses beyond alphabetic writing. It serves as a Roman numeral denoting ten, appears in mathematical and scientific notation and has been used as an abbreviation and as a marker for something unspecified. In the familiar convention of algebra, it can stand for a variable; in the language of investigation, it may signify an unknown; in other contexts, it can serve as a concise identifier.
These meanings do not form a single philosophical doctrine. They reflect the adoption of a simple sign for different purposes. The letter's historical usefulness lies in its ability to carry a specific meaning within a particular context without requiring a lengthy descriptive expression.
X® applies this quality of compact identification to a comprehensive consultancy framework. The name is concise, but the work it denotes is broad. It concerns the intelligence of the building society as an institution: its members, savings, lending, assets, liabilities, risks, people, information, local relationships and long-term purpose.
The framework is deliberately distinct from a narrowly defined technological application. It does not identify a particular artificial intelligence model, platform or operational task. Nor is it simply a collection of recommendations concerning the automation of existing processes. X® is concerned with the institution's capacity to understand itself, its members and the economic conditions in which it operates and to turn that understanding into sound decisions.
The historical associations of the letter provide a useful context for this approach, but do not determine it. Its contemporary meaning as a consultancy framework arises from the application made by X from GENERAL INTELLIGENCE PLC to the distinctive requirements of building societies.
THE BUILDING SOCIETY AS AN INTELLIGENCE SYSTEM
The building society is one of Britain's distinctive forms of financial institution. Its origins lie in mutual arrangements through which people pooled savings to support home ownership and improve their financial circumstances. Although the sector has changed considerably since the first known building society was established in Birmingham in 1775, mutual ownership remains central to its identity. Members are not simply customers whose transactions generate revenue. They participate in an institution whose purpose and commercial decisions are directed towards their collective interests.
Mutuality has consequences for the way institutional intelligence should be understood. A building society must operate with the commercial discipline, resilience and governance expected of a significant financial institution. Yet the ultimate purpose of its activities differs from that of an enterprise whose primary ownership structure is built around external shareholders. The society's long-term commercial strength and its capacity to serve members are closely connected.
X® approaches the building society as an interconnected intelligence system. It considers the relationship between member and institution, savings and lending, property and household, capital and community, human judgement and machine intelligence, institutional memory and institutional purpose. Its concern is how the society can develop a more coherent understanding of these relationships and use that understanding to improve decisions.
A building society may possess extensive information without having a sufficiently integrated view of its implications. Data may be distributed across products, systems, departments and channels. Reports may explain individual aspects of performance while failing to reveal significant relationships between them. Local observations may remain separate from central analysis; historical experience may be difficult to apply to current decisions; and emerging changes in the economy may not become visible through conventional reporting until their consequences are already material.
Artificial intelligence may provide ways of bringing these different sources of information into more useful relationships. The commercial significance lies not in aggregation alone, but in the ability to identify material connections, investigate emerging patterns and support more timely and considered judgement.
X® therefore considers institutional intelligence as a capability that extends across the building society, rather than as a technological function confined to one department.
MEMBER INTELLIGENCE
The member is not simply an account, a mortgage, a deposit balance or a customer record. A member has a financial life that may extend across savings, borrowing, property, income, expenditure, family circumstances, obligations and changing priorities over many years.
X® examines how artificial intelligence may help the building society develop a more coherent understanding of the financial relationships it maintains with members. This does not mean assembling information indiscriminately or treating every available datum as appropriate for analysis. The collection and use of information must remain proportionate to a legitimate purpose and consistent with privacy, confidentiality, fairness and the member's interests.
The objective is to distinguish a transaction from a financial event and a financial event from a meaningful change in circumstances. A movement in a savings balance may be routine; it may also reflect a change in income, a major expenditure or a new financial objective. A mortgage enquiry may concern a straightforward transaction, or it may be part of a more complex household decision. The significance of an interaction depends upon its context.
Better member intelligence should improve the society's ability to provide appropriate products and support, recognise potential difficulties and understand how the needs of its members change over time. Its value lies not in predicting every action a member might take, but in supporting an institution that can respond more intelligently to the circumstances in which those actions occur.
THE MEMBER JOURNEY AND HUMAN RELATIONSHIPS
Every interaction between member and building society forms part of a continuing relationship. Account opening, savings activity, mortgage applications, repayments, requests for assistance, digital interactions, complaints, telephone conversations and branch visits may each contain information relevant to the member experience.
Where such information remains fragmented, the institution may find it difficult to recognise repeated sources of friction, unmet needs or opportunities to improve the service it provides. Artificial intelligence may assist in identifying patterns across these interactions, subject to appropriate information controls and in bringing issues requiring attention to the notice of the relevant people.
The result should not be a relationship governed exclusively by predictions about behaviour. Nor should every interaction become an occasion for automated intervention. The objective is to help the society understand its service more fully and distinguish routine activity from circumstances that may require explanation, assistance or human attention.
This is particularly important in a mutual institution, where the quality of the relationship contributes to the society's long-term legitimacy. A more intelligent member journey is not simply a faster or more automated sequence of transactions. It is a better understanding of the relationship between the member and the institution, including where the society should improve its own conduct.
SAVINGS INTELLIGENCE
Savings are fundamental to the traditional building society model. They provide a home for members' money and constitute an important source of funding for mortgage lending and other activities. Savings behaviour therefore has significance at two levels: for the individual member and for the financial resilience of the institution.
X® considers how artificial intelligence may assist in understanding the factors that influence members' saving decisions, changes in balances, responses to interest-rate movements and evolving preferences concerning access to funds. At institutional level, these patterns may help explain the composition and stability of the funding base, provided that the analysis is grounded in suitable information and realistic assumptions.
The purpose is not simply to forecast deposit flows. It is to understand the relationship between member behaviour, economic conditions, the society's products and the institution's need to maintain a resilient funding structure. A change in savings activity may have different implications according to its scale, duration, distribution across the membership and relationship to other conditions.
X® therefore treats savings intelligence as part of the wider understanding of the institution, connecting individual behaviour with liquidity, funding strategy, lending capacity and the member proposition.
MORTGAGE AND PROPERTY INTELLIGENCE
The mortgage is one of the defining relationships between a building society and its members. It connects the institution's lending decision with a household's financial circumstances, a property and a series of obligations extending into the future.
X® examines how artificial intelligence can support a broader understanding of mortgage affordability, borrower circumstances, loan structure, repayment behaviour, property characteristics, local economic conditions and changes in the environment in which the borrower lives. It may assist in identifying patterns across large portfolios, evaluating scenarios and bringing relevant information to the attention of those responsible for underwriting and risk management.
The purpose is not to replace the discipline of lending with computational prediction. A model may identify a pattern, but the institution must still determine its significance, the reliability of the information and the suitability of the proposed lending decision. An accurate prediction of past outcomes is not, by itself, a sufficient basis for a responsible decision about an individual household.
Property must also be understood in more than financial terms. Its location, condition, value, energy characteristics, environmental exposure and relationship to the household may influence its long-term significance. The quality of a mortgage assessment depends upon the extent to which the institution understands the relevant financial and property risks, rather than treating collateral as an abstraction detached from the circumstances in which it exists.
The intelligent mortgage is therefore not necessarily the fastest or most automated mortgage. It is the mortgage whose suitability, affordability and material risks have been assessed with the greatest care appropriate to the decision.
CREDIT INTELLIGENCE AND FINANCIAL VULNERABILITY
Credit intelligence concerns the assessment of repayment, the conditions that influence it and the consequences when a borrower encounters difficulty. Artificial intelligence may assist in examining financial information, identifying changes in repayment patterns and distinguishing between different forms of credit risk. Its contribution must nevertheless be assessed against the quality of the evidence, the possibility of bias and the consequences of erroneous or inappropriate decisions.
For a building society, understanding credit risk is not solely a matter of identifying the probability of a loss. It also involves determining whether a member's circumstances are changing, whether a difficulty can be addressed and how the institution should respond.
Financial vulnerability rarely presents itself in a single, unambiguous indicator. Changes in payments, reduced savings, repeated requests for assistance or other information may become significant when considered together. Such signals are not proof of vulnerability and they should not become automatic grounds for adverse treatment. They may, however, justify a more careful review or an appropriate offer of support.
X® considers how artificial intelligence can help identify situations that warrant timely human attention. The objective is to enable the society to respond proportionately and constructively, without confusing a statistical indication with a complete understanding of an individual's circumstances.
The distinction reflects a wider principle of mutual financial judgement: the member is not merely a source of risk to be classified. The institution must understand both the potential financial consequence and the human circumstances relevant to its response.
FRAUD, SECURITY AND THE PROTECTION OF TRUST
Trust is an essential asset of a mutual institution. Members entrust building societies with their savings, financial information and, often, one of the most consequential financial commitments of their lives. Fraud, identity abuse, financial crime and cyber threats can therefore damage not only the society's financial position but the integrity of the member relationship.
X® examines how artificial intelligence may assist in identifying anomalies, connecting relevant signals across transactions and channels, detecting emerging patterns and supporting investigation. The value of these capabilities depends upon their accuracy, the quality of the information available and the arrangements through which alerts are assessed and acted upon.
Overly aggressive or poorly controlled systems can create their own problems, including false positives, unnecessary friction and the inappropriate treatment of legitimate activity. Effective intelligence must therefore balance the need to protect members and the institution with the obligation to treat people fairly and proportionately.
The objective is not surveillance for its own sake. It is to strengthen the society's ability to protect its members, maintain secure operations and respond to credible threats while preserving appropriate human judgement and accountability.
PORTFOLIO, BALANCE SHEET AND CAPITAL INTELLIGENCE
A building society must understand not only individual savings accounts and mortgage exposures, but the combined structure that they create. The portfolio embodies the consequences of numerous decisions made across different periods, economic conditions, regions, property types and member circumstances.
X® considers how artificial intelligence may assist in identifying concentrations, relationships and changes across the mortgage book, savings base and wider balance sheet. Exposures that appear unremarkable individually may become significant when they share a common geographical, economic, technological or behavioural characteristic. Conversely, apparent similarities may prove less consequential when the underlying circumstances differ.
The balance sheet must be understood as a dynamic expression of assets, liabilities, liquidity, capital, funding and institutional commitments. Conventional reporting remains indispensable, but artificial intelligence may help management investigate relationships across a wider range of information and examine the possible consequences of different scenarios.
Liquidity and capital require particular care. Their significance is not exhausted by a reported figure or a compliance measure. The institution must understand what its position means under changing conditions, how assumptions may be affected by adverse events and whether it can continue to meet its obligations while serving members responsibly.
X® therefore considers balance-sheet intelligence in the context of resilience, strategy and the society's ability to operate through uncertainty. The objective is not to replace established financial disciplines, but to improve the quality and timeliness of the understanding upon which they depend.
THE ECONOMY AND LOCAL INTELLIGENCE
A building society cannot be separated from the economy in which its members live. Interest rates, inflation, wages, employment, house prices, construction costs, taxation and confidence can influence savings behaviour, mortgage affordability, property values and the demand for credit. The effects are often uneven, differing across regions, households and economic sectors.
X® examines how artificial intelligence may bring relevant economic information into a more coherent framework for institutional judgement. Its purpose is not forecasting for its own sake, nor the production of a single authoritative prediction. It is to improve understanding of the ways in which economic change may affect members, assets, liabilities and the society's strategic position.
The local dimension is especially important. Building societies may possess relationships with particular communities and housing markets that provide insight unavailable from aggregate national information alone. Local employment conditions, infrastructure, planning, demographic change and housing supply may materially influence the risks and opportunities faced by members.
Artificial intelligence may help connect such local knowledge with broader analytical capability. The aim is to strengthen, not displace, the society's understanding of its geographical and social environment. A national economic indicator may describe a general condition; local information may explain why its consequences differ between communities.
THE BRANCH AND THE INTELLIGENT WORKFORCE
The branch should not be assessed merely as a physical channel whose future depends upon its replacement by digital services. It may also be a source of institutional knowledge. Employees develop familiarity with local circumstances, recurring service difficulties and the questions that members raise. Conversations may reveal context that is not captured in structured data, while experienced staff may recognise patterns before those patterns become evident in formal reporting.
X® considers how artificial intelligence can augment this knowledge by making relevant information more accessible, reducing unnecessary searching and helping employees connect observations with established institutional experience. This does not require every human interaction to be recorded or converted into data. It requires judgement about what information is appropriate to retain, how it should be protected and how it can legitimately improve the service.
More broadly, artificial intelligence changes the relationship between employees and information. Staff may be able to spend less time assembling fragmented material and more time explaining, investigating, advising and exercising judgement. The objective is not merely to increase productivity, but to improve the proportion of institutional effort devoted to work that genuinely benefits members and strengthens the society.
The intelligent workforce is therefore one in which technology supports professional capability without obscuring responsibility or diminishing the value of human relationships.
INSTITUTIONAL MEMORY AND LEARNING
A building society may operate across generations, accumulating experience through lending cycles, economic shocks, changes in regulation, fraud, complaints, service failures and successful interventions. Yet institutional knowledge can be difficult to preserve. Employees leave, systems are replaced and lessons from earlier events may become inaccessible or lose their context.
X® considers institutional memory as a strategic asset. Artificial intelligence may help the society retrieve relevant knowledge, relate current decisions to earlier experience and make established information more useful to those responsible for management and governance. Such an approach requires care: historical information must be interpreted in its original context and past experience cannot simply be assumed to predict future conditions.
The intelligent building society should also learn from the consequences of its own decisions. Lending outcomes test assumptions; operational incidents reveal weaknesses; member feedback exposes shortcomings; and changes in the economy demonstrate where forecasts or plans were inadequate. These experiences can improve future decisions when they are properly analysed, retained and incorporated into institutional practice.
X® therefore treats learning as a continuing process rather than a discrete technology project. The purpose is to enable experience to inform subsequent judgement, allowing the institution to become more capable without losing the accumulated understanding that gives its history practical value.
THE HUMAN BUILDING SOCIETY
The defining question for X® is ultimately human. A building society exists to serve its members through a financial institution whose interests are shaped by mutual ownership and long-term stewardship. Its legitimacy depends not merely upon financial strength or operational efficiency, but upon the manner in which it exercises its responsibilities.
Artificial intelligence should strengthen that character, not diminish it. There will be circumstances in which automation is appropriate, where consistent application of established rules improves service or where computational analysis offers a material advantage. There will also be circumstances in which the member needs an explanation, a conversation, a considered exception or an individual decision that cannot responsibly be reduced to a standardised output.
An intelligent society understands the difference. It knows when a process can be automated, when a person must review the result, when a member needs direct assistance and when institutional responsibility requires a decision to remain with an accountable human decision-maker.
This is not an argument for retaining every established practice. Nor is it an argument for human involvement regardless of circumstance. It is a demand for proportionate judgement: technology should be adopted according to its legitimate contribution, with the member and the long-term purposes of the institution remaining central to the decision.
TRUST AND MUTUAL PURPOSE
Trust is difficult to establish and can be damaged quickly. It depends upon competence, security, consistency, fairness and the belief that an institution will act responsibly when circumstances become difficult. Artificial intelligence can support these qualities, but it can also undermine them if its use is opaque, inappropriate or insufficiently controlled.
X® treats trust as a strategic and operational consideration. Significant automated decisions should be governed by arrangements that establish their purpose, boundaries and accountability. Information should be used appropriately; material errors should be identified and addressed; and members should not be treated unfairly simply because a system has produced a particular classification or recommendation.
The mutual model gives this requirement particular force. The society's relationship with its members is not merely a channel through which products are distributed. It is part of the institution's reason for existing. Its use of artificial intelligence should therefore be considered against the obligations that arise from this relationship, as well as the commercial benefits that technology may offer.
The most intelligent building society is not necessarily the one that uses the greatest number of artificial intelligence systems. It is the one that can demonstrate that its use of intelligence improves its ability to serve members, maintain resilience and make sound decisions over time.
THE X® FRAMEWORK
X® is the principal framework of the X from GENERAL INTELLIGENCE PLC portfolio and is conceived at the level of the building society as a whole. Its scope is deliberately broader than a single application or operational function. It considers the relationships between member intelligence, savings, mortgages, credit, property, fraud, portfolio risk, capital, liquidity, local knowledge, workforce capability, institutional memory and governance.
The framework is informed by the research into artificial intelligence undertaken by X from GENERAL INTELLIGENCE PLC. That research considers the development of machine intelligence from scientific, technical, organisational, economic and institutional perspectives, including computational capabilities, reasoning systems, intelligent agents, evaluation, safety, governance and regulation.
The consultancy applies that wider understanding to the strategic circumstances of the building society. It considers which developments are material, where new capabilities might create genuine value, which assumptions require further examination and how proposed applications should be evaluated against the society's objectives and responsibilities.
The approach is independent of any particular technology supplier or model. A building society's requirements should determine the technology, rather than the availability of a technology determining the problem the society is encouraged to address. In some cases, artificial intelligence may provide a substantial advantage; in others, better information, improved processes, organisational changes or the application of existing expertise may prove more appropriate.
The purpose is to establish a more coherent understanding of the institution and its options. Consultancy may therefore address strategic priorities, investment decisions, technological architecture, institutional readiness, governance, operational resilience or the practical relationship between machine intelligence and human judgement. The scope should remain proportionate to the decisions under consideration.
THE X® TEST
The X® test is whether the building society can understand more, earlier and more coherently than it could before.
- Does it understand the member behind the account, the household behind the mortgage, the property behind the collateral and the pattern behind the transaction?
- Can it relate savings behaviour to funding, individual exposures to portfolio risk and economic conditions to the circumstances of its members?
- Can it recognise material changes without confusing an uncertain signal with an established fact?
- Can it use local knowledge alongside broader analysis?
- Can it learn from its own experience, preserve institutional memory and improve the quality of future decisions?
- Can it deploy artificial intelligence without weakening mutual purpose, member trust or institutional accountability?
These questions define the standard against which a proposed application should be considered. More data is not necessarily more understanding; faster analysis is not necessarily better judgement; and greater automation is not necessarily greater institutional capability.
The objective is a society that can perceive relationships more clearly, assess uncertainty more carefully and act with greater intelligence. Its value lies in the coherence of the understanding achieved and the quality of the decisions that follow.
THE OBJECTIVE
The historical significance of X lies in the adaptability of a simple sign. Across centuries, it has served as a letter, a numerical symbol and a representation of an unknown quantity. Its uses differ, but they demonstrate how a concise form can acquire distinct meanings through the context in which it is applied.
X® gives that sign a specific contemporary role within the work of GENERAL INTELLIGENCE PLC. As an artificial intelligence consultancy framework for building societies, it is concerned with the development of institutional intelligence: the ability to understand members, relationships, risks, resources and circumstances as parts of a connected whole.
The building society of the future will need to combine increasingly capable artificial intelligence with the sound financial disciplines, institutional memory and mutual principles that have sustained the sector. Its success will depend not simply upon adopting new technology, but upon deciding which capabilities are valuable, how they should be governed and where human judgement remains essential.
X® is ultimately concerned with the creation of a more intelligent mutual institution: one capable of understanding its members more deeply, recognising risk more clearly, deploying resources more intelligently, preserving trust more effectively and learning continuously from experience. Its purpose is not to transform the building society into a technology company. It is to strengthen the society's ability to understand, decide, learn and act while preserving the mutual principles upon which its distinctive purpose depends.
Artificial intelligence is the means. Institutional intelligence is the capability. Mutual financial judgement is the discipline. Long-term trust, resilience and prosperity for members are the objectives.