An Agent-Based Framework for Financial Transactions Monique Calisti
Daniel Deluca and Andrew Ladd
Laboratoire d’Intelligence Artificielle Swiss Federal Institute of Technology CH-1015 Lausanne, Switzerland Phone: +41 21 6936677 Fax: +41 21 6935252
S1 Technology Center 705 Westech Dr. Norcross GA, 30092, USA Phone: +1 678 421 4842 Fax: +1 877 359 5506
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[email protected] [email protected]
ABSTRACT
Ever-changing Internet technologies are creating revolutions in the way people interact with each other. In particular, business interactions are rapidly transforming and evolving toward more dynamic and automated solutions. Among various on-line commercial activities, nancial services represent a fundamental component for developing and supplying many other e-businesses. The main idea behind e nance is to provide support by deploying software instruments that enable to automate many of B2B and B2C transactions. The current degree of automation and personalisation of on-line nancial services is still very limited: Web interfaces or ad hoc tools still require a lots of human interactions. Agent technology seems to be one of the most promising approaches for evolving toward more exible and dynamic solutions. Autonomous, intelligent, social and selfinterested software entities would act on behalf of nal endusers and/or business operators without the need for direct human involvement. This paper describes an agent-based system supporting automated business transactions. The aim is to evaluate the main potential and the major limits of supplying nancial services by deploying agents in a software environment. Keywords
agent-based interactions, e- nance, electronic payments, ontology. 1. INTRODUCTION
Internet technologies are rapidly evolving and radically modifying the way people interact with each other. The increasing number of virtual market-places facilitates transactions by bringing together a vast number of potential buyers and sellers [2]. In particular, business interactions (either business to customer (B2C) or business to business (B2B)) are rapidly transforming toward more dynamic and automated
solutions. Among various on-line businesses, nancial services represent the fundamental basis for developing many other electronic commercial activities. The main idea behind e- nance is to provide nancial support by deploying software instruments that enable many of the B2B and B2C tasks to be automated and improved. This also allows a broader set of personalised services to be o ered to the endusers. E-banking is probably one of the most common examples of automated end-users services that may rely upon a combination of B2B interactions, for instance between banking, credit card institutions, insurances, etc. Nowadays, despite the growing deployment of electronic nancial systems that allow some degree of automation1 , Web interfaces or ad hoc tools still require a large degree of human interactions. Transactions and payment orders, for instance, can be performed electronically, but only if a human is entering the right code or is pressing the right button in a speci c graphical interface. Moreover, the various back-end nancial services o ered to nal end-customers often do not combine information and facilities coming from di erentiated service providers (i.e., B2B integration is not supported). This kind of approach is evolving from customer self-service channels to more automated and fully integrated business applications that drive products and services to the consumer. Analysts predict that in the near future people will not physically go to their nancial institution branches nor log on to the Internet to deal with their banking tasks2 . Instead, humans will delegate the management of their bank accounts, paycheck, investments, insurances, mortgages, loans and credits to their personal electronic nancial assistant. The important concept is that self-interested software entities acting on behalf of humans and/or service providers can automate several electronic business and commercial activities such as services' advertisement, market trend monitoring, services' pricing and negotiations. This scenario facilitates nancial services to be increasingly incorporated as part of larger packages and organised around a primary product (e.g., credit or insurance 1 S1 Corporation, for example, developed some speci c e nancing tools such as S1 Financial Planning, S1 Bill Payment and Presentments, etc. More details can be found at www.s1.com 2 `Bots' will transform Retail banking, R. Ramulla, Andersen Consulting Financial Industry Segment, Internal Publication.
in conjunction with a house or a car purchase). Agent technology seems to be one of the most promising approaches for designing and implementing autonomous, intelligent and social electronic self-interested assistants [1], [5]. Software agents can evaluate and optimise the utility of speci c actions (such as bidding, o ering, selling, etc.), gather and process huge amounts of information and follow speci c strategies more eciently and more rapidly than humans or traditional mechanisms can. It could be argued that an agent future for Internet-based business transactions will be possible only if agents will be able to properly implement nancial services in software environments. However, it is also true that the current increasing deployment of agent technology in several elds has the opportunity of in uencing how nancial services will be supplied. In order to better evaluate the main potential and the major limits of an agent-based e- nancing framework, the Financial Agentbased Transaction (FAT) system has been developed. In the FAT system several entities can interact: personal assistant agents acting on behalf of nal end-users, agents representing banks, nancial institutions and all kind of existing online businesses. Speci c connections, contracts, agreements or other forms of relationships can exist among those business entities. Dynamic interactions enable agents to modify those relationships, contact each other, ask for services, o er services, cancel previous agreements, plan activities, etc. This paper concentrates on the basic mechanisms that are needed for supporting nancial services in an agent-based environment. By describing the FAT system and showing how agents could support and even replace humans or traditional business interactions, the aim is to evaluate the potential of autonomous agents for evolving on-line transactions that require nancial support. This evaluation is a preliminary step in proving that it is not only possible, but also desirable to integrate agent technology within existing electronic markets. Section 2 gives a more detailed overview of the trends in nancial service provisioning development. The central part of the paper focuses on the FAT system description, Section 3, and on depicting speci c agent-based transactions, Section 4. Section 5 discusses our approach and hopes to stimulate and contribute to a productive discussion about the main challenges for the success of automated e- nance. Section 6 summarises the current achievements of this work and comments about future developments in this area. 2. TRENDS IN ON-LINE BUSINESS
E-business can be de ned as the entire set of processes and mechanisms that support business activities in an electronic environment, or network, and involve information processing. In particular, this includes:
Electronic advertisement of services, products (e.g., access to product brochures and price lists), providers, advertisers, etc. Automated transactions (exchanges, contracts, service level agreements, etc.) between businesses and/or between businesses and customers. On-line ordering, direct selling (i.e., selling products),
End User
E-business world E-finance
B2C interactions B2B interactions
Figure 1: E- nance can be considered as a nal service
to be o ered to end-users or as a fundamental component service for many other e-business activities.
content selling (i.e., selling information), auctioning, on-line negotiation, marketing, etc. e-Finance as a set of access and management operations such as: { Banking: account management, transactions, credit card services. { Investment: on-line trading stock market and funds management. { Insurances: properties and life insurance management. { Mortgage and Loans. { Wealth management as a set of integrated nancial services including personalised nancial planning facilities.
E- nance can be considered as a nal service to be o ered to end-users (B2C) or as a fundamental component service for many other e-business (B2B) activities deploying mechanisms such as electronic payments, funds transfers, etc. (see Figure 1). For this reason, the evolution of e- nancial services plays an important key role for the future of all on-line transactions. Traditional approaches need to be evolved toward more automated solutions, since a human-based control becomes more and more unable to cope with: (1) the increasing end-users service demand, (2) the growing needs of exibility, and (3) the more urgent needs of dynamic service aggregation, i.e., B2B interactions. Agents seem to be one of the most promising approaches for supporting this evolution. 2.1 Business Drivers
The main factors behind the increasing interest in agent technology can be divided in application pull or business oriented (the need for innovative solutions to increasingly cope with e-commerce needs) and technology push or technological (the development of new techniques which make agent deployment a real possibility). In the rst place we have:
Market growth: The rapid growth of electronic markets and Internet-based commerce have forced major
changes to the roles, business models, and operational practices of service providers, including nancial service providers. Competition is erce and has kick started an industry wide drive for eciency.
Increasing exibility in usage requirements: With market di erentiation and increasing customer demand comes a need for exible service deployment. Today, nancial service providers o er several online services that allow end-users to apply for mortgages, investments, bank accounts management, etc. While these online services o er a good degree of exibility for nal end customers, they still do not allow full automation nor advanced personalisation. Services Integration: The number and the diversity of available services, i.e., distinct on-line businesses, is continually growing. This diversi cation is creating a complex heterogeneous network infrastructure and serious technological challenges in providing uniform and coherent services. Often, integration among various on-line services is limited, forcing end-users to move toward di erent virtual places. The lack of integration among nancial services contributes to further complicate this scenario.
These three drivers together are combining to produce very complex electronic market architectures and requirements. A major consideration is that when end-users' pro les change (new baby, new insurance, salary increment, etc.), the corresponding nancial picture should also change (modi cation in life insurance, mortgage re-computation, new car insurance, etc.) in order to optimise end-users' nances. All related nancial providers should therefore be informed about these changes in order to propose accurate and up to date solutions. In general, issues of scalability, reliability, security and interactions between services are increasingly replacing any other concerns business provider may have had. While complexity and integration have been partly addressed in the next generation of electronic applications, such as wealth management and customer relationship management3, there is still the need of meeting the challenges listed above and mapping end-users requirements in nancial planning in a more exible, dynamic and personalised way. 2.2 Technology Push Factors
Until recently, many agent applications have remained nothing more than small pilot projects in the research laboratories. One key reason behind this is that the necessary network architecture for agent deployment was just not available. Today, this is currently changing. There are now a large number of toolkits available which enable developers to quickly build multi-agent systems. Some of the most productive initiatives include FIPA-OS (http:// pa-os.sourceforge.net) and Jade (http://sharon.cselt.it/projects/jade/), open source 3 Several companies do o er such services. Some examples can be found at: www.adviceamerica.com, www.assetplanner.com, www.directdvice.com, www. nacenter.com
implementations of the FIPA standard speci cations4 , JATLite (http://java.stanford.edu/), Retsina, OAA, AgentBuilder (www.agentbuilder.com), JACK (www.agent-software.com.au/jack.html) and mobile agent systems such as Grassopher (www.ikv.de), Aglets (www.aglets.org) and D'Agents (agents.cs.dartmouth.edu). On top of that, increasingly, toolkits are also including reasoning capabilities and GUI management tools for deployed agents. More and more virtual markets do deploy agents. Gibney et al. are exploring the use of a two-levels auctioning mechanism for routing service demands in Telecom networks managed by software agents [4]. Kubawara, et al. developed a market model for multi-agent resource allocation [3]. Semret et al. deployed an auctionbased pricing approach for di erentiated Internet services o ered by agents and they identi ed the best strategies for end-users and brokers [6]. Ygge et. al as modelled power load management as a computational agent-based market [8]. 35 organisations are currently collaborating within the AgentCities framework ( see also www.agentcities.org). AgentCities is a worldwide initiative designed to help realize the commercial and research potential of agentbased applications. The objective is to construct a worldwide network of agent platforms based on the FIPA standard. Each platform will be supported by di erent institutions and host diverse populations of agents able to access each other's services. The resulting test-bed is designed to experiment agent technology, verify the impact of this technology on a quite large population of potential customers and act as a uni ed system facilitating the development of on-line services, ontologies, interaction protocols, etc. In this way, AgentCities has the potential of providing an inter-operable market where several services can be o ered and integrated including B2B and e- nancing services.
To summarise, agent technology is maturing as a software development paradigm. Development environments and standards are becoming available, which will likely build con dence in agent techniques and allow more wide-spread experimentation. Furthermore, several companies are investing in agent technology for agent-based tools providing nal endusers applications. Many current European IST Projects are investigating the supposed bene ts of agent technology in several elds including business integration. More information is available at: www.cordis.lu/ist/. Two other important e-commerce initiatives involving agents technology initiated by the MIT's MediaLab are the Development E-commerce Workshop 5 and E-Markets SIG 6 . 2.3 An Agent-Based Vision
Agent technology will play a fundamental role in changing the relationship between the consumer and the enterprise 4 FIPA (www. pa.org) is a non-pro t standardisation group that aims to promote inter-operability of emerging agentbased applications, services and equipments. 5 www.media.mit.edu/~mikeb/dev-ec/main.html 6 e-markets.www.media.mit.edu/projects/e-markets/
as well as the relationship between online business services provided by distinct partners. Customers will have more control and better access to a wider range of services (provided by various entities). Service providers will be able to dynamically interact between each other for aggregating existing services, adding new facilities, and generating completely new service packages. Currently, enterprises rely too heavily on a `self-service' customer model. For instance, today, a speci c end-user may apply for an insurance policy on-line, basically having access to an electronic interface. Tomorrow, electronic nancial assistants will interact with insurance providers to create a tailored solution based on speci c consumer's requirements and preferences. Moreover, software agents would be able to provide a wide range of investment possibilities dynamically managing end-users' portfolios. New nancial services will appear and more sophisticated facilities could be available. Agent-based negotiations and coordination will make it possible to handle more complex and heterogeneous situations. Within this vision, agents will o er a broader range of services due to greater dynamicity in combining services from di erent nancial partners. The availability of more detailed knowledge about customers' pro le dynamically supplied by personal assistants will allow service provider agents to o er more completely tailored packages that match customers' requirements. 2.3.1 Challenges
On-line businesses, and in particular e- nance, require complex interactions between diverse systems owned by di erent organisations or individuals. Despite the development of more robust information and reasoning systems and the evolution of agent infrastructures, major challenges lie ahead, as various visions of exible and automated integration between agent-based business systems rise to the fore.
Integration of agent infrastructures with existing nonagent based environments such as databases, legacy systems, various tools, etc. This task is even more complex when considering diversi ed access channels from Internet-only to to embrace mobile (PDAs, wireless, etc.), IVR and ATMs. Development of more usable and simple agent communication frameworks. This includes less complex formal semantics and logic models for agent communication languages, content expressions and ontologies so that dynamic and exible agent coordination and service aggregation can be more easily implemented. Security of agent-based interactions. When building nancial and business systems relying on electronic platforms and components, such as agents, the notion of trust has to be rede ned so that the main characteristics of electronic environment and emerging technologies are taken into account for building an appropriately secure framework.
3. AN ELECTRONIC AGENT-BASED MARKET
The FAT framework represents an electronic market where economic transactions rely upon nancial mechanisms supplied by software agents. This requires to modeling the type
of `goods' that are traded (or services o ered), to specify which entities can access the market and how this is possible, given a speci c market's infrastructure. In particular, this means to:
De ne intra-agents infrastructures that make software entities capable of participating in nancial transactions (e.g., reasoning capabilities in business and nancial terms). Implement technical facilities for enabling speci c agentto-agent interactions (e.g., ad hoc interaction protocols, negotiation strategies, etc.). De ne common knowledge representations and ontologies including fundamental notions, such as bank account, payment, credit, etc., so that agents are able to communicate with each other in a suciently abstract manner. De ne security policies regulating all agent-based transactions. The combination of di erent authentication, non-repudiation and data encryption mechanisms allows the implementation of several possible policies.
The development tools that have been deployed to implement the FAT system are:
Jade 2.01 (http://sharon.cselt.it/projects/jade/). The Java Development Kit of Sun Microsystem (version 1.3, http://www.javasoft.com). Together, tool facilitating UML-based modelling (http://www.togethersoft.com)
Jade is a software development framework aimed at developing multi-agent systems and applications conforming to FIPA standards for intelligent agents. Jade supplies two main sub-modules: a FIPA-compliant agent platform and a package to develop Java agents. 3.1 Modelling Goods and Services
At a very abstract and generic level, di erent types of goods/services can be o ered in the FAT market. However, in order to enable automated transactions between electronic entities representing di erent businesses and/or individuals, a formal and common interpretation of the good/service that is traded is needed. Although distinct entities in the market can have di erent internal representations of goods/services, for a common global understanding, a minimal agreement on common terms, de nitions, and expressions is needed. This agreement corresponds to the adoption of a common ontology to refer to when speaking about similar concepts. 3.1.1 Ontology Definition
An ontology represents a common vocabulary and agreed upon meanings, including de nitions to describe a speci c domain. All systems that communicate, inter-operate, and work together must share an ontology. Shared ontologies can be implicit or explicit. Implicit ontologies are typically represented only by conventions and procedures. Explicit
ontologies are (ideally) characterised by an explicit declarative representation in a well de ned knowledge representation language. To de ne an ontology it is necessary to design an underlying model of the domain in terms of objects, attributes, relations, and possible actions. Then, token or symbols or terms that refer to these elements have to be assigned. Finally, encoding rules and constraints which capture important aspects of the domain model are xed. In the FAT framework, two ontologies have been de ned: a bank-ontology modelling banking services and an insuranceontology modelling sickness insurances services7 . Considering the extreme complexity of the Swiss sickness insurance system, a simpli ed model has been implemented. This also allows the representation of a larger number of other existing sickness insurances. The vocabulary and the actions which from the ontologies are de ned using frames. A frame is a table divided into four columns: Slot, Description, Type and Reserved Values. Each frame de nes a concept used by an agent. The rst column of each frame contains the slot name. A slot is an attribute which de nes a frame. A short explanation of each slot is given in the second column. The data type is displayed in the third column. Only three data types are primitive: String, which represents a list of characters, Long (integer numbers) and Float ( oating points numbers). The description of other complex types is de ned in sub-frames. Some slots can take only speci c values. This reserved values are displayed in the last column. Given the extensive e ort to provide more machine accessible descriptions of data by adopting XML based solutions, particularly in a business context8 , future work includes an XML version of both the bank-ontology and the insuranceontology. 3.2 Interaction Protocols
Ongoing conversations between agents often fall into typical patterns. In such cases, certain message sequences are expected and, at any point in the conversation, other messages are expected to follow. These typical patterns of messages are called interaction protocols. In the FAT system, in order to facilitate the e ective inter-operation of agents that can be developed in di erent contexts and by di erent developers, standard FIPA interaction protocols (IPs) are adopted. The three most used IPs are:
FIPA-request : this protocol allows one agent to re-
FIPA-query : the receiving agent is requested to perform some kind of inform action.
FIPA-contract-net : an agent (the manager) solicits
quest another agent to perform some action, and the receiving agent to perform the action or reply, in some way, that it cannot.
proposals from another agent (the contractor) by issuing a call for proposals, which speci es the task and 7 A formal representation of the two ontologies can be recovered from the http://liawww.ep .ch/~calisti/FAT/ page. 8 For instance, ebXML, BizTalk, eCo and RosettaNet all use XML as a basis for de ning frameworks for business interactions.
any conditions the manager is placing upon the execution of the task. The contractor's proposal includes the preconditions that the contractor is setting out for the task, which may be the price, time when the task will be done, etc. 3.3 Market Actors
In the FAT system, distinct software entities mainly differ because of the di erent roles they can cover and/or services they can o er during nancial transactions. A software agent can play di erent roles considering di erent goods or services. Therefore, a generic agent can be both buyer and seller depending on the speci c transaction. However, in order to facilitate the tasks' decomposition and the agents' implementation, we distinguish between Personal Assistant Agents acting mainly as buyers and Service Provider Agents acting essentially as sellers. More precisely, when considering B2B transactions service provider agents can become buyers of each other's services. Three main types of agents have been implemented.
Personal Assistant Agent (PAA): every nal end user
is considered as a potential `consumer' of the services/goods o ered in the FAT market. First of all, PAAs access banking services in order to:
Open and/or close accounts (saving, checking or credit card accounts),
Get information about accounts' status, discounts, special rates etc.
Order payments and money or funds transfers.
Furthermore, PAAs, as `shoppers', can interact with all other provider agents in the FAT market in order to purchase goods and/or access services. A PAA can be considered as a global personal assistant that can act on behalf of nal end users in several di erent situations such as meeting scheduler, travelling organiser, etc. However, in this paper the focus is primarily on the negotiation with potential sellers of insurance policies and the interactions with bank agents.
Service Provider Agent (SPA): every service provider
(or good seller) is represented by an agent which is capable of negotiating with all other agents in the market. Negotiations with potential customers or peer providers take place to nd an agreement about service properties (or goods' characteristics), sales tax, prices, delivery and handling fees, form of payment, etc. The choice of payment options every SPA is o ering depends on which kind of relationships have been established with acquiring banks and card companies. In this framework, since the focus is on the provisioning of insurance services, we have Insurance Provider Agents (IPAs) that o er the following main services:
Information retrieval about policy terms and conditions, insured, billing, coverage, etc.
Creation and closure of policies,
Policies management (change of content, coverage amount, etc.).
3. electronic notification
In addition, every IPA is able to interact with banking and nancial institutions with which B2B relationships have been established. A Bank Agent (BA) is acting on behalf of a banking or a nancial institution. Banks that do business with providers who wish to accept credit cards are also called acquiring banks (B2B relationships). Providers are given an account to deposit the value of batches' card sales. The banks acquire batches of sales slips and credits their value to the provider's account. Banks then submit the other banks' charges to the interchange network either directly or through third-parties. Banks that extend credit to their customers through bank card accounts are also called issuer banks (B2C relationships). In this framework, every BA can act as an acquiring and an issuer bank. The three main kinds of services o ered by a BA are:
Information retrieval about accounts, funds, nancial and banking services information. Creation or closure of bank (checking and saving) and credit card accounts, Dynamic management of information and services.
More in details, every BA supports the main following operations:
Checking balances - both current and available - on accounts such as checking and savings, Transfer funds: customers who have multiple bank accounts can initiate funds transfers between their accounts. Account holders can also transfer money from their personal bank account to external nancial institutions, View transactions, Electronic Bill: a PAA can ask to view the bills to pay, request to pay them using a checking account (only checking account can be used, a transfer of money from savings to checking may be necessary to be able to pay a bill, for example), Credit card services.
4. FAT FOR INSURANCE SERVICES PROVISIONING
As mentioned earlier, in order to show how automated nancial and banking services can be deployed not only as `standalone' services, but also as the basis of many other business transactions, insurance service provisioning has been integrated within the FAT system. On one hand, the kind of relationships established between PAAs and BAs and between PAAs and IPAs can be considered as B2C interactions. On the other hand, B2B transactions take place between distinct BAs and between BAs and IPAs.
UBS-BA
2. payment order
5. verification
4. electronic notification
PAA
IPA 1. electronic bill
Figure 2: The main phases of the intra-bank payment scenario: money's transfer. In the following, a description of every simulated scenario is given. The decomposition of di erent interactions in basic steps helps in de ning speci c services and capabilities that every di erent software agent in the market has to support. 4.1 Insurance Service Provisioning
An insurance agent provides information to all customers about the health insurance o ers (e.g., access to policies brochures and price lists) and o ers on-line sales channels and support-lines. For this purpose, a major task is to describe the characteristics of di erent types of insurance and their attributes. There are two main types of health insurance in Switzerland:
A basic compulsory insurance that covers the risks of illness, accident and maternity. Complementary insurances which o er other services like ophthalmology cares, preventive health, home visits, etc.
Based on this general di erentiation, a simpli ed model of the Swiss sickness insurance system has been implemented (e.g., insurance-ontology). The idea of providing insurance services as an orthogonal market to the e- nance framework is based upon what future generations of nancial service providers are expected to provide. There is now a movement toward providing wealth management services to nal end-users: nancial planning tools allowing aggregation of di erent content, including insurance services, in a single integrated view. Given this framework, di erent scenarios have been implemented with the main purpose of evaluating the feasibility and the e ectiveness of automated agent-based transactions. 4.2 Intra-Bank Payment Order scenario
Figure 2: Marie's PAA stipulates an insurance policy with the IPA-X for 500 $. Marie's PAA orders the bank agent UBS-BA to transfer 500 $ from Marie's bank account to IPA-X's account. Both Marie's PAA and IPA-X have accounts with the UBS bank (i.e., the same BA is managing both accounts).
1. PAA-to-IPA negotiation. The negotiation is successful if the two agents nd a common agreement about the
insurance policy and its price. Depending on the speci c policy that agents have been negotiating about, the nal agreement can include di erent information and speci cations (i.e., di erent kind of contracts can be stipulated). In this kind of bilateral negotiation, one agent plays the role of buyer (i.e., the PAA) and the other agent plays the role of seller (i.e., the IPA). If the negotiation terminates with an agreement, the PAA has to pay the IPA and the seller has to supply the service to the buyer. Depending on the type of payment method that has been negotiated, explicit interactions with the BA can be required. 2. The PAA makes the payment. The PAA gets the necessary IPA's bank account information and asks its BA to transfer the right amount of money to the speci ed IPA's account. The BA knows from the account money transfer information provided by the PAA if the transfer will be an intra- or inter-bank transfer. 3. The BA veri es if on Marie's account there is enough money to make the payment. If this is the case, the BA transfers the speci ed amount of money from the buyer's account to the seller's account. In case there is not enough money in Marie's checking account, the BA noti es the Marie's PAA, which could decide autonomously to transfer money from a saving account to the checking account. The PAA should notify the end-user about this (eventually asking for an authorisation). If there is no other possible way to transfer money to the checking account, the PAA should notify the IPA, as well as the end-user, about the fact that the payment cannot be done and the service negotiation should fail. 4. The IPA delivers the good/service to the PAA. The service delivery can be subordinated to the payment completion or not depending on which agreement the PAA and the IPA have reached in the negotiation. 5. The IPA nally interacts with the BA in order to verify that the money have been transferred on its account. If not, a further interaction with the PAA is initiated. 4.2.1 Inter-Bank Payment Order
Marie's PAA stipulates an insurance policy with ISPA-X for 500 $. Marie's PAA orders UBS bank (UBS-BA) to transfer 500 $ from Marie's bank account to the IPA-X's account. IPA-X's account is managed by a di erent bank agent (CS Bank Agent, CS-BA).
Up to step 2, this latter case is equivalent to the previous scenario. What makes the di erence is the BA-UBS and the BA-CS interaction. Either the transfer of money happens independently on the service delivery or the service delivery is done only after the money have been transferred from UBS to CS. In this scenario, the focus is on developing techniques and mechanisms to support inter-bank agents relationships. 4.3 Credit Card Based Payment scenario
Figure 3: Marie's PAA stipulates an insurance policy with IPA-X for 500 $. Marie's PAA pays the speci ed amount of money via Marie's credit card account.
acquirer bank
UBS-BA
3. electronic receipt
issuer bank
2. payment order 1. payment order
PAA
IPA 4. electronic receipt
Figure 3: The main phases of the credit card payment scenario. The same bank agent can act as acquirer and/or issuer. 1. Marie's PAA to IPA-X negotiation: a successful negotiation terminates with an agreement about a speci c insurance policy and its price. Marie's PAA asks to pay by using Marie's credit card account (in this example UBS bank is the issuer bank of Marie). The PAA and the IPA rst negotiate on the type of credit card that is accepted as payment (VISA, MasterCard, American Express, etc.). Depending on the kind of existing payment infrastructure already installed at the service provider premises, the IPA will be able to accept speci c cards (e.g., the existing electronic infrastructure of the IPA-X only accepts Visa credit card). Finally, Marie's PAA securely submits the credit card information to the IPA-X. 2. IPA to UBS-BA interaction. The payment can be done in di erent ways in relation to what kind of agreement IPA-X and UBS-BA (the acquiring bank) had previously stipulated. In general, the IPA submits customer's payment data (i.e., amount of money to be paid, credit card number, cardholder's name, etc.) to the UBS-BA. This one does the credit card veri cation and provides an electronic receipt back, which is forwarded by the IPA to the PAA. If the credit card information is invalid, the message that is sent back to the PAA is a failure message explaining failures reasons and the purchases is interrupted. 3. The BA reports the completion of the transaction to its customers. The PAA also receives an electronic receipt from the IPA (see previous step). This enables Marie to eventually ask her PAA for printing out the receipt for later references. 5. DISCUSSION
The FAT system implementation allows a rough estimation of several aspects concerning the feasibility and the e ectiveness of automated nancial transactions. The current trend towards aggregating services including nancial mechanisms is perhaps one of the most challenging problems future online business will have to face. In this area the concept of agent middle-ware that es the technological and architectural gaps in current e- nance systems seems to have great potential. Agents provide a means of:
Abstracting from the technological idiosyncrasies of di erent technologies to improve their inter-operation.
Enabling richer and more exible interaction between both user and providers (B2C) and provider and provider (B2B interactions automatically exchanging tasks between di erent agents to customise service delivery).
Despite the potential of agents, it is important to consider some main challenges for their e ective deployment. The more traditional issues of using and building software agents, such as for instance addressing schemes, communication aspects, interaction protocols, etc., are furtherly complicated by the introduction of business mechanisms. Producing ` nancial' agents implies (1) the addition of speci c timing rules and policies that can be dicult to implement in a virtual environment, (2) an important communication overhead that increases as the number of agents scales up, (3) the capability of reasoning quickly and adapting to dynamically changing environment, and (4) the introduction of a more important computation support in order to behave strategically. In addition, the inherent problem with doing business and nancial transactions over the Internet is that data travelling over public networks can be easily compromised. This can a ect both the customers as well as the business owners. Companies have to nd ways to ensure the security of transactions, sensitive information, applications and on-line communications. The deployment of agents brings up new questions and research issues. In particular, it is fundamental to understand the dynamics of agent-based mechanisms in order to converge to a new notion of trust. For instance, an increasing number of business and nancial transactions rely upon the use of credit cards, charge cards, bank cards or other speci c payment mechanisms that involve relationships rooted in trust and good faith. A nal end user (or consumer) trusts the nancial institution that issued his/her credit card to pay the merchant for the purchased goods and services. Merchants trust that the card issuers will pay them reasonably fast, and the card issuers trust that the end users will pay their bills on time each month to reimburse the money they are advancing on behalf of them. When building nancial and business systems relying on electronic platforms and components, such as agents, the notion of trust has to be rede ned so that the main characteristics of electronic environment and emerging technologies are taken into account for building an appropriate trust model [7]. The fact that the new computational paradigm creates an open and evolving world and relies on partially autonomous entities, makes risks even more unpredictable and therefore trust even more crucial. More work on security is needed within the FAT system. In particular, the aim is to provide security mechanisms protecting and regulating all agent transactions. Starting from this concrete framework, the aim is to nally converge to a trust model that could have a more general validity. 6. CONCLUSION
The use of software agents in the nancial industry will certainly changes have a fundamental impact in the future development of nancial services and on-line businesses. Traditional banking activities will still play an important role, but current trends suggest that more and more automated and personalised solutions will be preferred. Electronic nancial advisors will be will automate the cross-selling and up-selling of nancial products and services. This will bring
bene ts for both customers and nancial institutions in terms of exibility, service integration, service personalisation, etc. A signi cant number of intelligent agents oriented projects using FIPA standards have been run during the last years. AgentCities is a new initiative, which aims to build a worldwide, publicly accessible, test-bed for the deployment of FIPA agent based services. One of the main ideas behind FAT is the possibility to integrate banking and insurance services into this test-bed. In this way, it will be possible to evaluate in a more realistic way (1) what kind of impact these services will have on a larger population of users, (2) how and at which level service integration will be possible, (3) how security mechanisms should work, and (4) how nancial services will evolve in such a vast and di erentiated electronic environment.
Acknowledgements
Many thanks to Frederic Deleze for his fundamental work in implementing the FAT system and Steven Willmott for his precious suggestions. 7. REFERENCES
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