What is Incident Management?

Incident management (IM) is the process to recover a service that does not function properly or is unavailable. A service disruption can be an employee not being able to print, but also payment transactions no longer being processed or an entire company no longer being able to log into their systems. An incident is a major incident if service recovery is critical to the performance of an organisation.

IM protects the ability to do business and avoids costs of non-productivity. Certain services, such as internet banking or iDEAL, have  such importance for society that there are legal uptime requirements (and penalties for non-compliance). Issues with these services often escalate to major incidents.

Improving system availability

The new AI application improves the availability of systems by:

1. Ensuring uniform process execution by experts
2. Reducing major incident handling time
3. Preventing incidents from escalating to major incidents

The new application will contribute to a critical business process for the entire bank.

‘Model = Application’ using advanced AI

The structuring methodology of Knowledge Values helped to create a goal-oriented model of the (major) incident process. The advanced Match™ AI and Data Enterprise Platform facilitates the paradigmatic principle that model = application which allows the model to be immediately used by Major Incident Managers (MIMs) to guide them through the process. By consistently using the application within the IM process, uniform process execution is now guaranteed. 

Servicenow integration reduces handling time

Once an incident has escalated to a major incident, the responsibility for service recovery is transferred to a MIM. To support the MIM, the application is integrated with the incident administration system ServiceNow. Information about the incident — the service, its importance to the organisation and the potentially involved IT architecture — is automatically retrieved and presented to the MIM. An employee can also enter other essential incident information. The result is an overview of the incident that the MIM can use to kick-start the service recovery.

Automatic progress reporting to stakeholders

The application automatically generates reports during the major incident process (see figure). Benefits:

1. Siloed information becomes common knowledge. This reduces the chance of costly inappropriate actions based on misinformation or misunderstandings. Also, less time has to be spent distributing information.
2. Management is always up-to-date on the progress of service recovery. The MIM can focus on service recovery and spend less time informing stakeholders.
3. The step-wise service recovery progress is automatically saved in a retrospective document. With this document, the incident can be easily analysed afterwards. Without such a feature, reconstructing what happened is difficult, as documenting with precision is difficult during a major incident.

Preventing major incidents

The application should contribute to the goal of preventing incidents from escalating to major incidents, or even prevent incidents from occurring at all. The retrospective document helps identifying structural improvements based on lessons learned during the incident.

A possible future step is the implementation of the application in the normal incident process. The expectation is information gathering functionality will empower employees in the incident proces to solve incidents themselves. The consequence would be that less incidents escalate to major incidents. This is the ideal situation as the best way to handle a major incident is to prevent it.

What’s next?

The disruptive flexibility of The Match™ Technology Platform allows feedback of the MIMs to be quickly integrated into the model. This means that MIM knowledge can be continuously integrated in the application and directly applied during major incidents. The automatically generated documentation during the proces will prove to stakeholders that there is an unprecedented level of control that will contribute strongly to system and service availability.

Data and compliance challenges

In the knowledge economy, banks need to automate their processes and ensure quality data services. Customers and regulatory authorities are becoming more demanding and the life cycles of regulatory schemes are getting shorter. The increasing rates of change of requirements on data transparency, regulatory reporting and access to liquidity sources are putting enormous pressure on European financial institutions. Banks allocate vast amounts of resources for automation and compliance and at the same time face legacy systems that do not have the flexibility to smoothly automate processes or produce “ready-to-consume” data. There is an urgent need for advanced data transformations to conciliate these dynamic data requests.

The Match™ AI and data platform

To flawlessly automate the private banking process, one of the largest Dutch banks is now investing in the Match™ Platform. Recently, the communication with risk profiling services was automated using Match™. Through smart connections, the bank managed to eliminate a two-phased, manual, error-prone process. What used to be an integral part of the daily work of a few hundred employees, is now replaced by transparent, well-specified instructions that are automatically executable.

Amongst the results are reduction of request handling time, improved accuracy, better risk mitigation, and an overall cost decrease. The Match™ AI and Data Platform supports the bank to control the complexity of automation and data transactions. Without coding, the technology suite makes it possible to build business fluid applications and perform advanced data transformations.

The Match™ Platform enables easy development and maintenance of domain-specific knowledge bases in a user-friendly way. With this accomplishment, the innovative bank team expects further excelling customer and employee satisfaction rates.

“The bank will move forward to the next levels of digital transformation and compliance. It will continue to manage its intellectual capital and control its enterprise logic and data through the Match™ Platform.” – Product owner bank

Investment advice Wft compliant

By specifying the regulations of the Wft (Law financial supervision), the bank created a robust, intelligent application without programming (!) that transforms investment data into a visually appealing dashboard.

Main functions of this Know Your Customer (KYC) application:

1. Determine income, assets and investing capabilities;
2. Formulate a detailed investor profile based on the client’s input;
3. Assess investment objectives and level of risk appetite of the client;
4. Create an overview of investment scenarios based on different predictions of future market performance.

Successful bank implementation

The KYC application is seamlessly connected to the system responsible for the selection of appropriate risk profiles. Manual, error-prone steps are removed. The result is a transparent process that is compliant with the Wft. Users are happy to have the flexibility to cope with current and future regulations.

Future-proof solutions today

The adaptability of the Match™ Platform – powered by a smart AI inference machine – allows for quick, accurate and controlled transformation of data. Analysis and reporting processes benefit from consumable data yielded by sophisticated transformations. Match™ offers a complete data solution that covers every step of digitising complex processes up to transforming big data chunks into valuable insights.

The AI solution is operational in the bank. Using the Match™ platform of the Amsterdam-based company Knowledge Values, the bank manages complex automation and smoothly integrates regulations with access-controlled distribution through the enterprise. The bank will continue to manage relevant business logic and capitalise the business value and its intellectual capital using Match™.

Knowledge Values congratulates our newly certified Enterprise Logic Engineers (Enterprise Logic Engineering I – Foundations):

ABN AMRO Bank N.V.:

• Danielle Détant
• Patricia van Helden 
• Yesim Özmuk
• Karen Verhoeven
• Edith Van Wijngaarden

Hoogheemraadschap de Stichtse Rijnlanden:

• Marijn Sleeuwenhoek

Knowledge Values:

• Robin Goudeketting

Bedankt voor jullie inzet, energie en enthousiasme! Het is een plezier om met jullie te mogen samenwerken.

Knowledge Values heeft haar privacyverklaring geüpdatet. Deze update is doorgevoerd om te voldoen aan de eisen van de wet van Algemene Verordening Gegevensbescherming (AVG) die op 25 mei is ingegaan. Bij Knowledge Values hechten we veel waarde aan het vertrouwen die de gebruikers ons schenken. Daarom is het erg belangrijk voor Knowledge Values om alle rechten van de gebruiker in kaart te brengen. Op de Privacy Policy pagina kunt u de wijzigingen bekijken. In dit privacybeleid leest u welke gegevens wij verzamelen en hoe wij deze gegevens gebruiken. Tevens geven wij aan hoe u gebruik kunt maken van het recht om de gegevens aan te passen of te verwijderen.

Mocht u nog vragen hebben dan kunt u contact opnemen met contact@knowledge-values.com.

Het Knowledge Expert Team van Knowledge Values heeft het afgelopen jaar hard gewerkt aan een innovatieve manier om grote hoeveelheden data te kunnen analyseren en te kunnen verwerken. Hiermee is een grote stap gezet in het slim verbeteren en uniformeren van batch georiënteerde, complexe, data verwerkende processen. Inmiddels zijn de eerste succesvolle resultaten al geboekt bij launching customers Achmea en PON.

Toepassingsdomeinen zijn onder meer regulary reporting (MiFIDII, Basel II, Solvency II, GDPR, EMIR), compliancy (Anti Money Laundering, Know Your Customer/Customer onboarding) fraude detectie en data reconciliatie.
Maar ook bijv algehele validatie, (her)classificatie en verwerking van complexe data-sets zoals klant-profielen, product-portfolio, billing-transacties, product-info en prijs-segmentatie. Zelfs het compleet vervangen van legacy maatwerk-applicaties (Cobol, Clipper, Progress etc.) in dit domein levert nu een aantrekkelijke business case op door inzet van de Match Data Processor.

Tijdens een 1e info-sessie op donderdag 26 oktober heeft Knowledge Values met trots de details van de Match Data Processor gedeeld middels een presentatie en een demo.
Wegens zeer grote belangstelling plant Knowledge Values nu een 2e info-sessie in op woensdag 17 januari van 14:00 tot 16:00 uur.
Locatie is het kantoor van Knowledge Values  aan de Herikerbergweg 242 in Amsterdam Zuidoost. Onder het kantoor is een ruime parkeergarage voor gasten.

Interesse om deze sessie bij te wonen? Vul dan hieronder uw email-adres in, dan nemen wij contact met u op.
Laat het ons uiteindelijk vòòr 15 januari weten want we sturen op een select gezelschap.

Waterschappen willen over naar gedigitaliseerde regels

De 22 Waterschappen in Nederland hebben de uitdagende taak om hun regels duidelijk te maken aan burgers, aan ondernemingen en aan andere overheden. Voor werkzaamheden bij waterwegen bepaalt het Waterschap of en hoe dat gebeurt. Dat vraagt om heldere en vlot toepasbare regels, voorzien van begrijpelijke uitleg. En digitaal natuurlijk, passend in deze tijd.  

Onlangs kwamen vertegenwoordigers van de Waterschappen bijeen in Amersfoort om te brainstormen over de beste aanpak. Op uitnodiging presenteerde Knowledge Values haar unieke visie op het structureren en vastleggen van regels, gebaseerd op principes uit de wetenschap.

Aanpak van Knowledge Values

Knowledge Values benadrukt dat goed gespecificeerde regels een voorwaarde zijn voor succesvolle digitalisatie: ontwerp de regels doelgericht, integraal en transparant. De Match™ Software van Knowledge Values ondersteunt de vastlegging van de regels in een kennismodel en zorgt tevens voor de representatie: de diverse visuele weergaven maken het lezen en valideren van de regels gemakkelijk. Tevens worden de regels automatisch gecontroleerd op compleetheid en consistentie. Het kennismodel kan ook direct als applicatie worden gebruikt (zonder programmeren!), zowel door mensen als door andere computersystemen. 

Toepassing voor de Waterschappen

Vervolgens kwam de uitwerking op het scherm van een deel van de regelgeving. Deze pilot was in enkele dagen door WDODelta met Knowledge Values opgezet. De aanwezigen waren onder de indruk van de transformatie van ‘hun’ complexe regels in een makkelijk te begrijpen kennismodel. Een schermdialoog demonstreerde de werking, inclusief de geautomatiseerde generatie van de bijbehorende documenten.

Na de beantwoording van verschillende vragen deelden de aanwezigen hun enthousiasme over de presentatie. Toepassing van de aanpak van Knowledge Values op grotere schaal is de komende periode onderwerp van nader onderzoek.

Update

Op 7 september 2017 is afgesproken, dat de aanpak van Knowledge Values voor de Waterschappen de voorkeur heeft gekregen voor het specificeren van regels. 

In 2016 the first version of WIS*kit, a web application that simplifies the allocation process and carries out complex income calculations, has been released.
We are proud to present release 2.3 now.

The current release has been extensively tested by Eigen Haard and fellow corporations Stadgenoot and Rochdale.
The application is collectively developed based on input of various housing corporations. That way, housing corporations will follow a more uniform method, which creates clarity for the customer.

The following functionalities have been introduced in WIS*kit release 2.3:

• The possibility to work with an annual report has been added. Advice is to only use an annual report of the previous year. This is also mentioned under the “i” icon in the WIS*kit application itself.
  Calculation for Box 3 has been adjusted for 2017.
• You can now see with which contract partner or other co-resident you are working on. This makes usage easier.
• In case of (a deviation from) a rejection, names of children and date of birth will be asked for.
• Self-employed entrepreneurs are now being asked for the net annual profit and what the deduction items (self-deduction, start-up deduction, VAT exemption) are in order to reach the taxable income of the entrepreneur.
• Added is the ability to use data of the benefit participation act (formerly the assistance).

Read more about WIS*kit on the website www.inkomenstoets.nl 

Disclosing the economic value of knowledge. A functional paradigm.

During the 9th European Conference on Intellectual Capital in Lisbon in April 2017, Dr. Larry Lucardie gave a few scientific insights that initiates advanced thinking and a new generation of ICT.

The value of knowledge is not in line with its economic valuation. Due to how economic value is perceived in the industrial systems of the 19th and 20th century, corporate bookkeeping systems do not explicitly account for knowledge. In centrally guided systems economic value was linked with material commodities created by physical labour, whereas in capitalist countries the value of immaterial assets was denied by accountancy foundations. While industrial systems have transformed into knowledge economies, bookkeeping systems still rely on concepts of industrial economies.

Knowledge economies being complex systems and enterprises, as a consequence, struggle when processing service requests. Knowledge management activities are not targeted to mastering complexity, but instead are focused on representing it. Representation of knowledge is often human-based suffering from randomness and limiting scalability in time and space. IT approaches focus on representation of logic in legacy systems that are closed and rigid and not very adequate to convey and maintain knowledge. Enterprise logic is represented in text documents, calculation sheets, flow charts and similar techniques that do no justness to the characteristics of complexity.

So, our views of knowledge and knowledge management do not seem to be in a satisfactory shape and need revision. Old fashioned concepts underlying bookkeeping systems need to be synchronised with the knowledge economy. At the same time, the value of knowledge needs to be capitalised. The current accumulation of inefficiencies offers an expected but much needed and excellent opportunity to induce a paradigm change to accomplish this. The paradigm of functional object-types delivers a broader and deeper view of knowledge relating it to complexity. It provides a theory how to characterise and structure complex logic and render knowledge usable and adaptable for the transformation function of an enterprise. In addition to scientific advances, the first practical results reveal that the paradigm, including its Match™ Technology instruments, yields unprecedented achievements that are unthinkable with classical business improvement approaches. It showcases formidable time reductions in the transformation model, lower development and maintenance costs and higher quality of enterprise logic. Its 7th generation application-by-specification development is revolutionary short and elastic.

Processing million of records in minutes

Previously it was already possible to correctly and consistently specify business logic using the Match™ Specification Developer, allowing for flexibility, transparency, zero defects and a incredibly short time-to-market in your knowledge models. With the Match™ Data Processor it is now possible to enjoy the same benefits, while automatically deploying the model to analyse and transform millions of records in minutes. 

In 2016, when authorities changed the regulations on reporting for life insurance companies (renseigneren), amazing results were achieved with a project at Achmea. Read more about renseigneren.

Knowledge Values can help control MiFID II complexity

In early 2018, a revision of the Markets in Financial Instruments Directive (MiFID) and new Regulation on Markets in Financial Instruments (MiFIR) will be implemented by the European Union (EU). While these directives and regulations are aimed at making the European financial market more efficient, resilient and transparent, they bring a great deal of change and extra work for financial companies in the EU. Among others, more reporting requirements are introduced, assessments will need to be conducted, and trading obligations will be imposed. 

Applying our Advanced Knowledge Services™ methodology, Knowledge Values can help your company to introduce intelligent regulations management solutions in reply to these new regulations. Using the Match™ Specification Developer helps your organization structure processes transparently and with zero defects. And with our newly developed Match™ Data Processor you can automatically process millions of transactions in a matter of minutes. Additionally it can simultaneously produce output that complies to the MiFID II reporting requirements or other regulations. 

Client

Achmea is legally obliged to share information regarding life insurance policies with the Tax Authority, a process called renseigneren. It involves sharing value- and premium information, ~ 300.000 messages once a year, and information regarding extraordinary events (passing, expiration, surrender, donation, and violation of tax rules), ~2500 messages every month. This information is reflected in pre-filled tax declaration forms. Until recently, this process demanded a lot of knowledge and effort from employees, as rules were only partially automated.

Challenge

As per January 1st 2017, new regulations for renseigneren came into force, tremendously effecting large life insurance providers such as Achmea. The new regulations have an impact on multiple IT systems in the chain: administration, workflow, database registration, forwarding to the Tax Authority, informing the customer, and archiving. In addition, the process adds no commercial benefit: no new life insurance will be sold by proper renseigneren. However, not complying with these obligations may lead to considerable fines from the Tax Authority.

Solution

With the expertise and principles of Knowledge Values, the rules for renseigneren were first structured in Match Developer, creating a goal-oriented and transparent, directly executable renseignerings application for all life insurance policies of Achmea. Subsequently, connections with other systems in the chain have been realised, tested, and put into production. As a result, employee effort is limited, and a correct and traceable process is guaranteed.

Benefits

Last but not least, future modifications in the rules for renseigneren will be accomplished easily. In conclusion: business improvement according to the principles of Knowledge Values is a foundation for Achmea’s ambition.