This paper presents a first semantic formalization of the Brazilian financial system risk management policies, called OntoBacen, that is based on a modularized approach. We show some partial results generated by a knowledge-based system that uses an ontology constructed to address some domain questions.
Episodes like global crisis undermine people’s confidence in the financial system, but also provide lessons for the future. The 2007-2008 meltdown resulted in a significative advancement of governance policies followed by financial institutions worldwide, with some of them treating classic data management problems, as integrity and completeness. To enable the adoption of an integrated and robust global financial system, IT companies and financial institutions are joining efforts for the creation and adoption of a technological framework to better meet the industry needs.
The main goal of this work is to explore alternative approaches for the conceptualization and definition of business rules present in governance policies of the Brazilian financial system, more specifically those related to risk management. To this end, it proposes an ontology, called OntoBacen, that expresses the concepts (and their relationships) of this domain, and by using inference algorithms, can verify the compliance of hypothetical financial institutions with those policies.
For such a wide and complex domain, modularity must play a central role in the design of the proposed solution, to ensure that it results in an coherent, understandable and scalable knowledge-based system.
In the following section, the risk management setting of the Brazilian financial system is briefly introduced. We then present the main initiatives involving ontologies for the financial industry, followed by a description of OntoBacen by means of its properties and requirements. In the sequence, we show the modularization approach adopted by the proposed solution, followed by a section that details how OntoBacen has been developed and how it’s meant to be used. Some test cases illustrate the use of the proposed ontology, followed by current conclusions and future development steps.
The main good practices for the governance of the global financial system were established and formalized by the Basel Committee on Banking Supervision (BCBS), forming part of the Bank for International Settlements (BIS), that in postcrisis periods identified the need for a robust data management framework. This must ensure that banks have the capacity to aggregate risk exposure data in an integrated manner, reaching all the corporation levels, in addition to standardized risk reporting practices (BIS 2013a), confering the degrees of assertiveness and timeliness required by institutional leaders for decision-making in times of stress.
Once established the core principles for banking
supervision
The policies and guidelines to be followed by the
Brazilian financial institutions are created and maintained by the
local monetary authorities, but mainly by the executive
authority of the national financial system, the Brazil Central
Bank, also known as BACEN. In order to align their
governance policies with the Basel principles, the Brazilian
monetary authorities created a series of norms, known as
prudential regulation
These regulations are arranged to take into account the main types of risk, described as follows: Credit Risk Associated with the risk of default, the failure to comply with obligations and responsibilities.
Market Risk Related to the volatility of rates or prices over the time, such as currency exchange and interest rates, or prices of securities and commodities.
Operational Risk Associated with the probability of loss resulting from internal processes failures or deficiencies, including legal risks, such as damages to third parties arising from its activities, or violation of rules established in their jurisdiction.
This business division of the domain suggests that modularity should be taken into account (and exploited to the fullest) when dealing with risk management.
In recent years, with the greater control over the financial systems by regulatory agencies, the need for information systems interoperability and data integration has increased, which strengthened initiatives related to finance on the Semantic Web; these initiatives, allied with the ontologies’ semantic formalism, have gained their place and importance in this specific industry.
As an example, the Suggested Upper Merged Ontology
Other relevant initiative is the Financial Industry Business Ontology2 (FIBO), a series of standards being developed by the Enterprise Data Management Council (EDMC) and published following the technical governance process of the Object Management Group (OMG). FIBO currently provides a framework of conceptual definitions concerning the wide spectrum of financial applications, currently available for use in two modules.
The first module, FIBO foundations, defines high-level financial concepts such as currency or contracts, and even non-financial concepts such as autonomous agent or country, that are need for the definition of more specific financial concepts. The second module, FIBO Business Entities, defines concepts such as legal persons and corporations, entities that could incur legal obligations such as establishing business contracts with other entities.
There are also ontological initiatives concerning financial
regulations, where lies the scope of this work. Abi-Lahoud
et al. (2013) developed an ontology concerning the
compliance with American anti-money-laundering regulations;
later, Abi-Lahoud, OBrien, and Butler (2013) presented an
experimental discussion about the adopted approach, an
iterative process based on subject-matter expertise and on the
use of structured natural language, more precisely based
on SBVR
1See: http://xbrl.squarespace.com/financial-report-ontology/. 2See: http://www.omgwiki.org/OMG-FDTF/doku.php.
These initiatives are being conducted with the support of the Governance, Risk and Compliance Technology Centre3 (GRCTC), also responsible for the development of the Financial Industry Regulatory Ontology (FIRO) and the Financial Governance, Risk and Compliance Ontology (FIGO).
The final and main goal of this work is to create an ontology to represent the Brazilian financial system, by means of its risk management concepts, and to be implemented in the Web Ontology Language (OWL). In this sense, it is related to some of the ontologies mentioned in the previous section, while considering BACEN’s governance policies, as published in its norms.
A Brazilian financial jargon says that BACEN’s regulations are the “tropicalization of Basel”. To exemplify this statement, when comparing BACEN and Basel standardized approaches to evaluate market risks, one can conclude that the BACEN approach has an additional component of risk for fixed interest rates denominated in the local currency (real), making it a conservative adaptation of the Basel approach (BIS 2013b).
The specification of OntoBacen, by means of its
requirements, is given by a set of competence questions
The definition of capital component used in this paper is that of a grouping of assets or liabilities, possibly weighted by some factor and represented by an amount of money.
Aditionally, for the development of the proposed ontology, a methodology partially based on the GRCTC methodology (adopted by FIRO and FIGO) will be used, as shown in the Construction and Usage section.
The BACEN’s prudential regulation is the starting point for the definition of OntoBacen. It was analyzed in a top-down approach, beginning with the most high-level view, represented by the notions related to the methodology for calculation of the Reference Capital, later reaching the lowerlevel related concepts. In this sense, by the interpretation of a series of BACEN documents, the lower level concepts were identified, introducing definitions related to several approaches for the measurement of different types of risk.
After this domain analysis, some core modules were identified for the development process, as shown in Figure 1.
Foundations
RWA MaRrkWet ARisk
Credit Risk Operational Risk
Banking Book Risk
Primarily, the FIBO Foundations and FIBO Business Entities ontologies were chosen to provide the highest level of semantics, such as the has part property, a whole-part relationship frequently used by OntoBacen, or even concepts common in finance, such as currency.
Some additional concepts not present in FIBO were defined to provide mid-level semantics, constituting the module Foundations, that is supposed to be used by other modules and ontologies of OntoBacen; it is composed by a set of ontologies described later in this section.
The lower level ontologies are then separated in two major disjoint groups: Capital and RWA. The first group addresses the definition of capital, that is represented in an accounting perspective by shareholder’s equity, savings and other kinds of liabilities. The second group name is an acronym for Risk Weighted Assets, that also in an accounting perspective consists of the values of assets weighted by distinct types of risks according to the degree of risk exposure; these two groups encompass the concepts that must be defined for addressing CQ1.
To exemplify how RWA captures the notion of risk, one could think, for instance, in a market risk perspective, if you have a given amount of resources applied in the stock market and the same amount of resources applied in treasury bonds, it is expected that the weighting factor of the first group is higher than the second one’s weighting factor, and consequently its RWA, because of the probability that the company which some stocks was acquired enter bankruptcy is higher than that of the government defaulting.
Each one of these groups were then divided in minor (and also disjoint) modules. Capital group takes into account BACEN major definitions to do these separation, being decomposed in Tier 1 Core, Tier 1 Complementary and Tier 2 ontologies. The same group also encompasses a Permanent Limit ontology, that is used to reduce the amount of capital used for requirements checking, in cases that permanent assets exceed a certain limit.
The RWA group considered the division for risk management mentioned in the first section, resulting in different ontologies for Market Risk, Credit Risk and Operational Risk. An additional ontology Banking Book Risk was added to treat the risk related to interest rates of banking book assets, i.e. those acquired and meant to be held until their maturity, because the risk exposure calculation method for these cases is different from the standard market risk for interest rates approach.
An additional reason to adopt such modularization is that these subdomains are commonly subject of distinct business areas in financial institutions (specially the big ones). In this sense, the compliance area is more willing to treat issues addressed by the Capital ontologies, the market risk management area to those of the Market Risk ontology, and so forth, in such a way that those areas could consult specific ontologies as semantics repositories or even use its inference capabilities to address their own issues.
Finally, an additional ontology, Capital Requirements, deals with the capital adequacy questions mentioned in the proposal section. It is related to concepts defined in both Capital and RWA ontologies, and contains the definitions of business rules necessary for addressing CQ2.
Currently, the Foundations, Market Risk and Capital Requirements ontologies are ready to be used, as detailed in the sequence. Consequently, the capital adequacy competence questions address only market risk exposure.
This module is composed of four foundational ontologies, described as follows: Common Relations Ontology that defines a set of data and object properties required by other ontologies, such as: 1. mathematical properties, to define product, minimum, maximum, and other derivation relationships; 2. time constraints properties, such as initial and ending date (xsd:dateTime), minimum and maximum duration (xsd:duration), needed for time intervals definition; 3. the has reference date property, needed for the definition of financial system governance contexts; 4. the has decimal value property, used to define factors; BACEN Factors Ontology for the definition of constant or time dependant factors present in BACEN regulations. Time dependancy is defined by fixed xsd:dateTime intervals or fixed xsd:duration intervals relative to a specific date; Financial Institutions Ontology encompassing concepts that define the Brazilian financial system agents, such as: 1. The financial institutions classification, specializing the concept for legal person from FIBO Business Entities. Examples are commercial banks, investiment banks, securities brokerages, etc.; 2. The concept of monetary authority, that also is a legal person, and used to define BACEN; 3. The concepts for classification of institutions into compliant or not-compliant to specific regulatory norms; Contextualized Monetary Amount Ontology for the definition of a generic context concept, and also: 1. The contextualized monetary amount concept is a specialization of FIBO Foundations monetary amount concept, something that has a currency and an amount, and that additionally has a context (uses FIBO Foundations has currency, has amount and has context properties); 2. The financial system governance context concept, that specializes context, and also involves a monetary authority governing and constraining the behavior of a financial institution at a specific moment in time (uses FIBO Foundations is governed by and constrains properties).
The contextualized monetary amount concept is used to represent amounts of cash related someway to a financial system governance context, thus it is the major definition of OntoBacen for addressing CQ3.
The main goal of this ontology is to provide a way to evaluate the market risk exposure by using at least one of the approaches available. Its semantics translates the business rules needed to obtain the market risk RWA (risk weighted assets by market risk exposure).
Figure 2 shows its main concepts and their relationships
using a notation similar to VOWL
The first important thing to note is that there are two possible appoaches to evaluate the market risk RWA, the standardized approach (called RWAMPAD) and the internal model approach (called RWAMINT). Both of these approaches have more specific concepts that are omitted here for a matter of simplicity.
In both cases, financial institutions must verify their market risk exposure by the standardized approach, because even the internal model approach depends on the standardized. In addition, they are not required to have (or to use) an internal model, but in the cases that both approaches are implemented, one of them must be chosen.
To opt for the internal approach, the institution must show to BACEN that the proposed model actually maps the market risk efficiently and that it is consistent with the regulations and norms. When opting for this model, things get a bit messy, because in this case, some conservative constraints for the evaluation of the RWA must be considered.
Firstly, a market risk model transition factor (defined as Sm) must be considered. This factor assumes the value of 90% in the first year of the transition, and 80% after that. This weighting factor is then applied to the standardized approach, producing an intermediate result, the standardized approach considering Sm factor. From the results obtained by both the application of the internal model approach and the standardized approach considering Sm factor, the greater of these is defined as the internal model RWA.
Independently of the values for the market risk RWA obtained by different approaches, institutions must choose one of them to report BACEN. OntoBacen’s current implementation chooses, in cases where the two models are evaluated, RWAMINT (int. model has part approach)
RWAMPAD is derived from considering product of Sm factor RWAMINT components (omitted)
is derived from is derived from ismdaexriivmeudmfroofm maximum of product of market risk RWA component
RWAMINT considering Sm factor
RWAMPAD (standard approach) relative time dependant factor OB Market Risk OB Foundations generalization custom relationship the smallest (by comparing the has amount data property); in the other cases, where there is only the standardized approach, this latter is the one to be reported.
The market risk ontology defines the concepts mentioned before as specializations of contextualized monetary amount. A general market risk RWA concept is defined, so that it encompasses any market risk evaluation approach, being naturally specialized by the two approaches previously mentioned, and by an additional concept for the approach that was chosen to be reported to BACEN.
The intermediate results used in the evaluation of the market risk RWA are conceptualized as specializations of an additional concept market risk RWA component. Finally, the Sm factor concept is classified as a specialization of relative time dependant factor, defined by Factors ontology and whose semantics define that its value is dependant of the amount of time elapsed from a specific date (in this case, the market risk model transition date).
There are different capital requirements specified by the BACEN regulations, such as minimum requirements for tier 1 capital and reference capital. The latter is the most general (and relevant) definition of capital, so that this requirements rules was chosen as the first to be implemented by the Capital Requirements ontology. For the implementation of capital requirements rules related to more specific concepts, such as tier 1 capital, some efforts will be needed in the construction of ontologies for the Capital module, described in the beginning of this section, and working in progress at the moment of writing.
The main idea of this ontology is to compare the risk weighted assets with some liabilities composition, defined in this case as reference capital, and that is mainly composed by reserves and shareholder’s equity. To define the concept of risk weighted assets, it is necessary to consider all types of risk (such as the market risk mentioned before), aggregating these multiple risk types as a general and single concept. For that, all ontologies of the RWA module must be available; as already mentioned before, at this moment the capital requirements ontology is considering only market risk as a risk type.
The minimum required reference capital can be determinimum required reference capital mined from the risk weighted assets, as depicted by the dependency relationship between these concepts in Figure 3. This minimum requirement amount is given by applying a numerical factor (reference capital requirement factor) to the RWA, whose value decreases yearly (11% before 2016, 9.875% at 2016, 9.25% at 2017, 8.625% at 2018 and 8% after 2018). This fixed time interval dependancy is represented as an specialization of the concept time interval dependant factor of the Factors ontology.
Before this comparison between the reference capital and its minimum requirement could be done, the excess of permanent assets must be discounted from the capital, resulting in an additional concept for comparison between capital and RWA: reference capital for rwa comparation. This excess is determined by additional business rules, omitted here, because they are in the scope of the Permanent Limit ontology, not yet constructed.
Another important concept definition is that of margin over required reference capital, which is given by the difference between the capital component, considering any necessary deductions such as the excess of permanent assets, and the minimum required capital. From the margin over required reference capital, one can determine if a financial institution is compliant with the capital requirements verifying if its value is non-negative, analogous analysis could be made to determine if the institution is non-compliant (negative margin).
Given these final considerations, concepts like reference capital requirement compliant and reference capital requirement non-compliant can be defined (shown as part of an external ontology in Figure 3), which indicate the compliance (or not) of some Brazilian financial institution to BACEN’s prudential regulation at a specific time.
The nine steps for developing and using OntoBacen are shown in Figure 4. The six first steps are for the ontology construction, while the last three are for its usage. BACEN’s prudential regulation is the input to this methodology, and is available as a set of .pdf files written in Portuguese, that are copied to an easily editable format, such as text files.
Input: Bacen norms 1.Follow references ref.
X
X 6.Manipulate namespaces,
imports, cardinalities, labels, etc.
Enrich semantics
by adding SWRL rules.
.owl +SWRL TBox ABox
.txt (NL) 2.Self-contained, complete sentences 3.Extract terms and rules to SBVR .sbvr (SNL) for each module
(steps 6-9) 7.Generate individuals with custom application (Jena + SPARQL) .rdf .s.sb.sbvbrvrvr .o.wo.owlwl l 5.Convert SBVR
to OWL (formal logic)
Input: Operational capital limit report file
.xml 9.Get answers with new knowledge ? 8.Infer new axioms by using an OWL and SWRL compatible inference engine new axioms In the first step, it is needed to follow reference chains present in such norms, to construct, in a second step, semantically complete and self-contained sentences in natural language (Portuguese), by cutting and pasting portions of the original text.
After that, in the third step, the self-contained sentences are interpreted in order to achieve a first level of formality, identifying and representing its terms and rules with SBVR (structured natural language). Note that there isn’t a SBVR structured vocabulary for Portuguese; in this sense, relationships and rules are translated to English so they can be based on SBVR-SE (SBVR Structured English), but terms (concepts) are kept in their original form.
Marinos, Gazzard, and Krause 2011 proposed the creation of a tool for the manipulation of SBVR vocabularies with auto-completion and highlighting features, work that later evoluted to SBVR Lab 2.04, a tool freely available on the Web; this tool was used to help achieving the goals of the third step.
The fourth step begins with the possession of the SBVR vocabulary; its terms and rules are distributed in a set of distinct vocabularies, mainly by considering their subject matter, what inevitably demands interpretation and expertise of the domain; secondly, we take into account technical considerations, in order to achieve, for instance, a higher degree of disjointness between vocabularies, and thus minimizing the number of relationships between terms of distinct sets. Other important issue involves the detection of core terms,
those that are extensively related to other terms, and should be organized in such a manner that could be easily shared between multiple modules.
All these initial steps involves human interpretation and manual activities to be accomplished; they demand familiarity with Brazilian legal writing, as the BACEN’s norms are written similarly to any other Brazilian law document (legalese), and also require prior knowledge about its subject matter, since these norms aren’t designed to be educational.
The fifth step is the conversion of these multiple SBVR vocabularies to OWL 2.0, generating the ontology modules. Some works in the literature address the conversion between these two languages without semantics loss, however a more detailed description is beyond the scope of this paper. Karpovic and Nemuraite 2011 worked in the field, resulting in the creation of a conversion tool freely available on the Web, called s2o5. The initial step for the creation of OntoBacen OWL files used this tool6.
In the sixth step, the initial OWL files obtained from s2o are subjected to manipulations in order to complement and enrich their semantics. For that, the Prote´ge´7 software was used to: • Add or update namepaces and ontology imports; • Include some cardinality restrictions not captured in the
SBVR vocabularies phase; • Add labels and other annotation properties useable for documenting the ontology (in Portuguese and English); • Create SWRL rules to allow the inference of additional axioms, including the use of its built-in functions for math and date operations.
At this point, each OWL file is the final version of an ontology, concluding the terminological component (TBox) of the system.
The main reason to adopt such approach is because manipulating a large vocabulary such as the BACEN’s prudential regulation, is made quickly by just listing its terms and rules in text files than formalizing all them in ontology development tools. In this sense, for OntoBacen’s initial development phase, described in this paper, only small subsets of the identified concepts were subjected to the formal ontology engineering process (step 6).
For the construction of the assertion component (ABox), the input artifact for the definition of instances of the ontology classes (individuals) is the DLO8, a XML report file that Brazilian financial institutions must submit to BACEN, briefly depicted in Figure 5.
This file, containing the data required for the possible assertions which one can infer by the use of OntoBacen, is available in accordance with a XML Schema similar to accounting, where each structure is composed basically of 5See: http://s2o.isd.ktu.lt/about.php.
6It was necessary to apply a simple syntax transformation algorithm in this step, whose details are beyond the scope of this paper. 7See: http://protege.stanford.edu.
8DLO is an acronym for Demonstrativo de Limites Operacionais in Portuguese, and stands for operational limit statement. <documentoDLO cnpj="12345678" dataBase="2012-05"> <limitesInformados> Reference Date </..l.imitesLIisntfoofrRmeapdoortse>d Limits Legal Person Identifier <parametros> Reference Capital ... List of Parameters (Account Code = 100) Account </parametros> Value <contas> s <conta codigoConta="100" valorConta="2139.00" /> tn <conta codigoConta="101" valorConta="2129.00" /> cuo <conta codigoConta="102" valorConta="2049.00" /> cA ... fo <conta codigoConta="900" valorConta="1067.00" /> itsL <<ccoonnttaa ccooddiiggooCCoonnttaa==""995600"" vvaalloorrCCoonnttaa==""160645.9.0000""//>> </contas> </documentoDLO> a numerical identification code, and an amount of money (Brazilian reais).
A Java application was developed to do the XML deserialization, that also used Apache Jena framework (with some help of SPARQL queries), for the automatic instantiation of the individuals to be later used in conjunction with OntoBacen. The final result is a set of RDF files, following the same modularization approach used in the ontology creation phase.
From now on, all components required for the reasoning
phase are ready. The reasoning can be done through a
specific module, subsets of modules, or even all of them. In
this phase, an inference engine compatible with SWRL rules
must be used; for the test cases presented in this paper, Pellet
Finally, by using the set of inferred axioms, one can get the answers to the proposed competence questions, for instance: a Brazilian financial institution complies to BACEN’s prudential regulation in a determined context, if it is classified as capital requirement compliant in that context.
Notice that each module can answer some limited and specific questions, for instance: the Market Risk ontology can only determine the degree of exposure to market risk, and that isn’t sufficient to verify the compliance or not to BACEN’s prudential regulation; the presented competence questions have a higher level of complexity, and need some reasoning over all modules of the ontology so that they can be answered.
For testing the proposed knowledge system capabilities, a standard example of the DLO was used, as provided by BACEN. From there, three additional test cases were created by altering elements of the XML file, so that their instantiation could be automatically done by the custom application mentioned in the construction and usage section.
Table 1 shows the relevant input data of the four test cases, in millions of Brazilian reais, and for a matter of simplicity, the market risk RWA models were consolidated by its components, as it was shown in Figure 2.
According to the information shown in Table 1, OntoBacen can apply business rules by using an inference engine compliant with OWL and SWRL rules, in order to answer if the institutions in each case are compliant or not with BACEN’s capital requirements regulations, considering their exposure to market risk.
Case 1 is the default example provided by BACEN9. In this case, only the standardized market risk approach is used, so that it is necessarily the reported one, and the reference capital is more than five times higher than the reported RWA, with a highly positive margin over the required reference capital, resulting in the inference of such institution as compliant to the capital requirements.
In case number 2, both models are implemented, but the standardized model indicates a lower risk exposure than the internal model, and as OntoBacen is configured to choose the minimum exposure approach (this isn’t obligatory), the standardized approach is chosen to be reported. This institution has a high amount of permanent assets, so that the reference capital is halved when reduced by the excess of permanent assets, making the minimum required reference capital higher in comparison with this amount, resulting in a nega9The operational limit statement XML files are available at: http://www.bcb.gov.br/fis/pstaw10/leiaute limitesDLO.asp. tive margin over the required reference capital and therefore the conclusion that it is not adherent to the norms.
Case 3 has both models implemented too, but the internal approach indicates the lower risk exposure (being reported), not sufficiently low to break the barrier of the standardized approach weighted by the Sm factor (90% in this case because the model transition was done in less than a year). Additionally, the reference date is now at the year of 2016, when the reference capital requirement decreases from 11% to 9.875% of the RWA, and finally results in a handily positive margin over the required capital, concluding that this case is compliant.
In the last case, number 4, the market risk approaches differ greatly from one another, in such a manner that even the Sm factor being of 80% (since the model transition happened more than a year before the reference date), the internal model broke the barrier of the standardized approach weighted by Sm, so that the final RWA value by the internal model will be the same of the barrier. As in this case the internal model will assume 80% the value of the standardized approach, OntoBacen will choose it for being the lower one. The minimum required reference capital is then evaluated from the resulting RWA and compared with a minor value, which brings to a negative margin and the conclusion of non-compliance to BACEN’s capital requirements regulations.
All test cases executed the mentioned inferences in few seconds, by using Pellet reasoner within Prote´ge´, so that computational performance was adequate, since this isn’t a real time problem. The time for loading required ontologies from the Web was approximately thirty seconds.
OntoBacen currently deals with very general and aggregated concepts, so that performance was not a great concern yet. However, as the level of detail (and data) increases, to deal with all data at once could be a performance issue, given the exponential nature of reasoning systems; this is another reason to consider modularity, alongside with distributed reasoning, as a primary design requirement for modeling this domain.
This paper presented an alternative technical approach for dealing with risk management: instead of the standard specialized systems, we propose to use ontology-based technologies together with a knowledge-based system.
Our proposal provides an open knowledge reference to address issues of this domain, freely available in the Semantic Web10; its semantics provides a formal representation of rules established by BACEN’s prudential regulation, and also a computational artifact that along with automated reasoning can provide answers to the user.
By the use of such approach, any Brazilian financial institution that needs to report accounting and risk indicators to BACEN by using an XML operational limit statement (which has only syntactical and structural constraints, without formal semantics), could verify its semantic consistency before submission, or even generate semantically consistent 10URI: http://lti.pcs.usp.br/⇠ filipe.polizel/OntoBacen/. content, avoiding mistakes and delays that can bring eventual penalties and losses.
Finally, for the effective success of such solution, modularity must play a central role in its design from the beginning to the end, allowing financial institutions to take advantage of computational features such as distributed computing and avoiding to handle massive amounts of knowledge at once, given the exponential computational complexity of logical reasoning algorithms.
This work intends to further explore the BACEN regulations in order to define business rules for other risk types, such as credit and operational risk. Besides, the ontologies for capital definition will be created so that the reference capital concept can be decomposed in more detailed definitions. Therefore, the Capital Requirements ontology could be enriched in order to consider all possible types of risk, and capital requirements rules could be evaluated in additional levels, such as tier 1 capital requirements.
Other issue concerns the integration capabilities of the proposed ontology. In order to address that, additional semantic alignments can be done between OntoBacen and other ontologies, while the work on financial ontologies (FIBO, FIRO, etc) progresses. Another possible approach for this question would be consider additional ontologies as possible semantic foundations, such as a mathematics ontology to express some of the relations identified in OntoBacen (derivation of concepts by differences, maximums, etc).
As these goals are achieved, additional efforts can be done in such a way to deepen the concepts definition for each subdomain that composes the governance of a financial system risk management, increasing the proposed system granularity and thus allowing it to treat additional risk management questions (or even accounting). To this end, a lot of work in the interpretation of an extensive set of BACEN regulation documents should be done, and as the ontology evolve in depth of details, new modular considerations must be taken into account, such as those discussed in this paper.
After the construction of the modules proposed in the specification section, this work also aims to evaluate the approach using a more realistic case study, by applying OntoBacen rules with the data of a real Brazilian financial institution, that is publicly available via balance sheets and risk reports, or even by collecting more detailed data using the operational limit statement XML sent to BACEN by some institutions.
Jaime Sichman partially financed by CNPq, Brazil, proc. 303950/2013-7.
Retrieved from last access on [BIS 2013a] BIS. 2013a. Principles for effective risk data aggregation and risk reporting. [BIS 2013b] BIS. 2013b. Regulatory consistency assessment programme (rcap) assessment of basel iii regulations in brazil. [Engel et al. 2013] Engel, P.; Hamscher, W.; Shuetrim, G.; vun Kannon, D.; and Wallis, H. 2013. Extensible business reporting language (xbrl) 2.1.