A Short Introduction to the Regorous Compliance by Design Methodology

Abstract

We provide a short outline of the compliance by design methodology proposed by Sadiq and Governatori to ensure compliance of business processes and its implementation in Regorous.

Introduction

Many de nitions of compliance have been proposed. However, regulatory compliance is generally understood as the set of activities in place in an organisation to ensure that the procedures, policies, processes and operations of the organisation comply with the normative frameworks governing the business and environment where the organisation operates. Sadiq, Governatori, and Naimiri [26] proposed a de nition of regulatory compliance as a relation between two sets of speci cations, more precisely, between the (formal) speci cations of a set of regulations and the (formal) speci cations of a system. The de nition is further operationalised by focusing on formal models of business processes for the speci cations of a system, and the relationship is that activities performed to execute a business process do not violate the (relevant) set of norms.

In the past decade a plethora of compliance frameworks have been proposed; we refer to [17, 25] for introductory material to general ideas about compliance, [ 7, 4, 2 ] for surveys and evaluations from the functionalities and business point of view, and to [20, 19] for classi cations of the underlying approaches and their suitability to properly represent normative requirements. The compliance-by-design methodology and techniques advanced by [26], extended in [ 15, 17 ] and then implemented as Regorous [ 18, 10 ] emerged as a strong ICT based solution for handling the regulatory compliance of business processes [20, 19]; Regorous combines a conceptually sound logical representation of norms with mathematical models of business processes and, at the same time, it o ers a practical solution to determine whether business processes comply with relevant normative frameworks.

In the next section we give a very brief overview of business processes and we argue that they can be used to represent a large class of systems. Then in Section 3 we discuss how to model norms in FCL, the rule language used in Regorous, then in Section 4 we outline the compliance architecture for Regorous. 2

Business Processes

A business process model is a self-contained, temporal and logical order in which a set of activities are expected to be executed to achieve a business goal. Typically, a process model describes what needs to be done and when (control ow), who is going to do what (resources), and on what it is working on (data). Many di erent formalisms (Petri-Nets, Process algebras, . . . ) and notations (BPMN, YAWL, EPC, . . . ) have been proposed to represent business process models (we refer to [ 6 ] for an extensive presentation of business processes languages and modelling techniques, and [ 1 ] for the technical foundations). Besides the di erence in notation, purposes, and expressive power, business process languages typically contain the following minimal set of elements: tasks, connectors (control ow gateways) and events. A task corresponds to a (complex) business activity, and connectors (e.g., sequence, and-join, and-split, (x)or-join, (x)or-split) de ne the relationships among tasks to be executed; for the events we restrict ourselves to the start and end event. The combination of tasks and connectors de nes the possible ways in which a process can be executed. Where a possible execution, called process trace or simply trace, is a sequence of tasks and events respecting the order given by the connectors. We will use TP to refer to the set of traces of a process P . In other terms, TP represents all possible ways in which the process can be executed.

Compliance is not only about the tasks that an organisation has to perform to achieve its business goals, but it is concerned also on their e ects (i.e., how the activities in the tasks change the environment in which they operate), and the artifacts produced by the tasks (for example, the data resulting from executing a task or modi ed by the task) [21]. To capture this aspect [26] proposed to enrich process models with semantic annotations. Each task in a process model can have attached to it a set of semantic annotations. An annotation is just a set of formulas giving a (partial) description of the environment in which a process operates. Then, it is possible to associate to each task in a trace a set of formulas corresponding to the state of the environment after the task has been executed in the particular trace. Notice, that di erent traces can results in di erent states, even if the tasks in the traces are the same. In addition, even if the end states are the same, the intermediate states can be di erent. Accordingly, we extend the notion of trace. First of all, we introduce the function

State : TP

N 7! 2L; where N is the set of natural numbers and L is the set of formulas of the language used to model the annotations. 3

Modelling and Reasoning with Norms

As we have already discussed to check whether a business process is compliant with a relevant regulation, we need an annotated business process model and the formal representation of the regulation. The annotations are attached to the tasks of the process, and it can be used to record the data, resources and other information related to the single tasks in a process.

For the formal representation of the regulation we use FCL [ 9, 15 ]. FCL is a simple, e cient, exible rule based logic. FCL has been obtained from the combination of defeasible logic (for the e cient and natural treatment of exceptions, which are a common feature in normative reasoning) [ 3 ] and a deontic logic of violations [ 16 ]. In FCL a norm is represented by a rule

a1; : : : ; an ) c Where a1; : : : ; an are the conditions of applicability of the norm/rule and c is the normative e ect of the norm/rule. FCL distinguishes two normative e ects: the rst is that of introducing a de nition for a new term; the second is

The second normative e ect is that of triggering obligations and other deontic notions. FCL supports all deontic notions (normative requirements) proposed and classi ed for compliance purposes in [ 8, 22 ], see Figure 1. In addition it has mechanisms to terminate and remove obligations (see [ 15 ] for full details). For obligations and permission we use the following notation: • »P¼p: p is permitted; • »OM¼p: there is a maintenance obligation for p; • »OAPP¼p: there is an achievement preemptive and perdurant obligation for p; • »OAPNP¼p: there is an achievement preemptive and non-perdurant obligation for p; • »OANPP¼p: there is an achievement non preemptive and perdurant obligation for p; • »OANPNP¼p: there is an achievement non preemptive and non-perdurant obligation for p.

Compensations are implemented based on the notion of ‘reparation chain’ [ 16 ]. A

Compliance

Legalese Formalisation 4

Compliance Rule Base Rule1 Rule2 Rule3 Rule4 Rule5 Rule6 Rule7 Rule8 Rule9 ...

Recommendation Sub-system

recommendations as implemented in Regorous. Given an annotated process and the formalisation of the relevant regulation, we can use the algorithm initially proposed in [ 15 ] to determine whether the annotated process model is compliant. The procedure runs as follows: 1FCL is agnostic about the nature of the literals it uses. They can represent tasks (activities executed in a process), or propositions representing state variables and the happening of events. reparation chair is an expression

O1c1

O2c

Oncn; where each Oi is an obligation, and each ci is the content of the obligation (modelled by a literal). The meaning of a reparation chain is that we have that c1 is obligatory, but if the obligation of c1 is violated, i.e., we have :c1, then the violation is compensated by c2 (which is then obligatory). But if even O2c2 is violated, then this violation is compensated by c3 which, after the violation of c2, becomes obligatory, and so on.

The reasoning behind FCL is the standard mechanism of defeasible logic [ 3 ] extend to handle the deontic notions. We refer the interested readers to [ 14 ] for a full description and all technical details.

Each task in a process model can have attached to it a set of semantic annotations. In our approach the semantic annotations are literals in the language of FCL1, representing the e ects of the tasks. Figure 2 depicts the architecture of the compliance methodology Compliance Checker

Annotated Business Process

Input Obligations if sis at ly wh ana

Logical State Representation

State(t,1) State(t,2) State(t,3) State(t,4)

A process is (fully) compliant if and only if all traces are compliant (all obligations have been ful lled or if violated they have been compensated). A process is partially compliant if there is at least one trace that is compliant.

Regorous proved to be conceptually sound for the modelling of norms [ 10 ] against underlying semantics advanced in [ 8, 22 ] It does not su er from the problem of wrong representation of norms a ecting formalism based on possible world semantics [ 11 ] and temporal logic based compliance frameworks [ 13 ].

Notice that the Regorous’s strategy to examine all traces (with the proviso that all loops are unfolded once) is optimal, in the sense that [ 5 ] proved that the problem of determining whether a process is weakly compliant is NP-complete and CoNPcomplete for the case of full compliance.

It is worth noting that the core notion we require is that of a trace, which is can be simply understood as a sequence of relevant event. Thus, the idea presented in this section and used in Section 4 can be adopted for a large variety systems (all we need is a sequence of events, each with a set of semantic annotations attached to each event). Also, it can be used at di erent stages of the life-cycle of a business processes design-time, run-time and auditing. At design time, we have to simulate all possible execution of the process with abstract data, at run time, we use the data generated by an instance (case) of the process, and we can evaluate if up to the current task the process is compliant, determine what obligations are currently in force and predict if the instance is going to be compliant. Finally, it is possible to replay the entire log (split in cases) for auditing purposes, eventually retrieving the data from log of from the databases related to the processes [21, 23]. 4.1

Implementation and Evaluation As we have already alluded to our compliance-by-design methodology has been implemented in Regorous which has been implemented on top of Eclipse. For the representation of process models, it uses the Eclipse Activiti BPMN 2.0 plugin, extended with features to allow users to add semantic annotations to the tasks in the process model. Regorous is process model agnostic, this means that while the current implementation is based on BPMN all Regorous needs is to have a description of the process and the annotations for each task. A module of Regorous take the description of the process and generates the execution traces corresponding to the process. After the traces are generated, it implements the algorithm outlined above, where it uses the SPINdle rule engine [24] for the evaluation of the FCL rules. In case a process is not compliant (or if it is only weakly compliant) Regorous reports the traces, tasks, rules and obligations involved in the non compliance issues.

Regorous was successfully tested in a number of pilot project with industry partners in banking, insurance, telecommunications and building sectors. See [25, 18] for the results of the evaluation in the telecommunication sector for compliance against the Australian Customers Protection Code (C628-2012). As we noted above, in general, the problem of determine whether a business process is compliant is computationally intractable. However, Regorous adopts a series of strategies to reduce the number of computations [ 12 ]. Furthermore, experience with the pilot project seem to indicate the theoretical computational limits, do not really a ect practical applications. 17. Governatori, G., Sadiq, S.: The Journey to Business Process Compliance. In: Cardoso, J., van der Aalst,

W. (eds.) Handbook of Research on BPM, pp. 426–454. IGI Global (2009) 18. Governatori, G., Shek, S.: Regorous: A Business Process Compliance Checker. In: Francesconi, E., Verheij,

B. (eds.) ICAIL 2013, pp. 245–246. ACM, New York (2013) 19. Hashmi, M., Governatori, G.: Norms Modeling Constructs of Business Process Compliance Management

Frameworks: A Conceptual Evaluation. Arti cial Intelligence and Law (2017) 20. Hashmi, M., Governatori, G., Lam, H.-P., Wynn, M.T.: Are We Done with Business Process Compliance:

State-of-the-Art and Challenges Ahead. Knowledge and Information Systems (2018) 21. Hashmi, M., Governatori, G., Wynn, M.T.: Business Process Data Compliance. In: Bikakis, A., Giurca, A.

(eds.) RuleML 2012, LNCS, vol. 7438, pp. 32–46. Springer, Heidelberg (2012) 22. Hashmi, M., Governatori, G., Wynn, M.T.: Normative Requirements for Regulatory Compliance: An

Abstract Formal Framework. Information Systems Frontiers 18(3), 429–455 (2016) 23. Islam, M.B., Governatori, G.: Exposing the RuleRS: a rule-based architecture for decision support systems.

Arti cial Intelligence and Law (forthcoming) 24. Lam, H.-P., Governatori, G.: The Making of SPINdle. In: Governatori, G., Hall, J., Paschke, A. (eds.)

RuleML 2009, LNCS, vol. 5858, pp. 315–322. Springer, Heidelberg (2009) 25. Sadiq, S., Governatori, G.: Managing Regulatory Compliance in Business Processes. In: vom Brocke, J., Rosemann, M. (eds.) Handbook of Business Process Management 2nd edition, International Handbooks on Information Systems, vol. 2, pp. 265–288. Springer, Berlin-Heidelberg (2015) 26. Sadiq, S., Governatori, G., Naimiri, K.: Modelling of Control Objectives for Business Process Compliance.

In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007, LNCS, vol. 4714, pp. 149–164. Springer, Heidelberg (2007)

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