Operational risk turns out to be risks a company undertakes when it attempts to operate within a given field or industry. Operational risk is the risk not inherent in financial, systematic or market-wide risk. On the contrary, it is the risk remaining after determining financing and systematic risk, and includes risks resulting from breakdowns in internal procedures, people and systems.

When it comes to financial industry, the Basel II Committee defines operational risk as: “The risk of loss resulting from inadequate or failed internal processes, people and systems or from external events.”

However, the Basel Committee recognizes that operational risk is a term that has a variety of meanings and therefore, for internal purposes, banks are permitted to adopt their own definitions of operational risk, provided that the minimum elements in the Committee’s definition are included.

1 Breaking down Operational Risk

The following lists the seven official Basel II event types with some examples for each category:

  • Internal Fraud – misappropriation of assets, tax evasion, intentional mismarking of positions, bribery

  • External Fraud – theft of information, hacking damage, third-party theft and forgery

  • Employment Practices and Workplace Safety – discrimination, workers compensation, employee health and safety

  • Clients, Products, and Business Practice – market manipulation, antitrust, improper trade, product defects, fiduciary breaches, account churning

  • Damage to Physical Assets – natural disasters, terrorism, vandalism

  • Business Disruption and Systems Failures – utility disruptions, software failures, hardware failures

  • Execution, Delivery, and Process Management – data entry errors, accounting errors, failed mandatory reporting, negligent loss of client assets

1.1 Operational Risks in Bank Industry

Alan Greenspan, Chairman of the Federal Reserve American Bankers Association, during Annual Convention on October 5, 2004 held, “It would be a mistake to conclude that the only way to succeed in banking is through ever-greater size and diversity. Indeed, better risk management may be the only truly necessary element of success in banking.”

Operational risk losses have often led to the downfall of financial institutions, with more than 100 reported losses exceeding US$100 million in the recent years.

1.2 No data means No IA

When you walk through the Web, there is no report or Open Data base when it comes to previous event which occured short while ago.

1.3 Ideation regarding the perfect financial report

1.4 SNCF OpenData

Open Data SNCF - https://data.sncf.com/explore/?sort=modified SNCF offers the possibility to have a look at their Incident report and investigation

1.5 Other OpenData Bases

2 A graph database to tackle Operational Risk

Provides a real-time library of Incident report and investigation

kable(incident_report, "html") %>%
  kable_styling(bootstrap_options = c("striped", "hover"))
DATE TYPE.DE.RAPPORT URL
2016-07 Rapport externe http://medias.sncf.com/sncfcom/open-data/rapport-securite/Reflexions-securite-essais-ferroviaires-grande-vitesse.pdf
2015-04 Rapport annuel sécurité http://medias.sncf.com/sncfcom/open-data/rapport-securite/ftp://rlalanne@voyagessncf.upload.akamai.com/17512/sncf.com/medias/sncfcom/open-data/rapport-securite/Rapport_annuel_Securite_2014-Elements_generaux.pdf
2015-04 Rapport interne sécurité http://medias.sncf.com/sncfcom/open-data/rapport-securite/Rapport_annuel_Securite_2014-Elements_EF.pdf
2016-08 Rapport interne sécurité http://medias.sncf.com/sncfcom/open-data/rapport-securite/Incident-Saint-Aunes-site-transparence-VDEF.pdf
2015-10 Rapport externe http://medias.sncf.com/sncfcom/open-data/Pour_une_nouvelle_etape_dans_le_management_de_la_securite_de_SNCF-09oct2015.pdf

2.1 Graph database

Graph database aims at bringing to light all links between all events occured to provide unthinkable answers to concrete issues such as :

  • A very specific kind of event, did used to happen at a very specific period of time?

  • Is there a given hour or specific day when an event occurs ?

  • …

 visNetwork(nodes, edges, width = "100%") %>%
   visGroups(groupname = "Incident", shape = "icon",
             icon = list(code = "f071", size = 75)) %>%
   visGroups(groupname = "Date", shape = "icon",
            icon = list(code = "f017", color = "black")) %>%
   visGroups(groupname = "Commentaires", shape = "icon",
            icon = list(code = "f044", color = "red")) %>%
  visGroups(groupname = "Ville", shape = "icon",
            icon = list(code = "f19c", color = "green")) %>%
   visGroups(groupname = "Agent", shape = "icon",
            icon = list(code = "f007", color = "gold")) %>%
  addFontAwesome()

  • In blue, warning logo accounts for an unplanned disruption or degradation of service which gives birth to some problems. Here is the incident event. Answer to question : “What?”

  • In black, clock logo brings light to when accident occured - i.e. time regarding the issue. Answer to question “when?”

  • In red, report logo provides up-to-date and in-depth information when it comes to issue occured.

  • In green, city logo highlights the place where took place issue.

  • In yellow, person logo brings agent out who is written the incident report.

DT::datatable(incidents_securite)
## Warning in instance$preRenderHook(instance): It seems your data is too
## big for client-side DataTables. You may consider server-side processing:
## http://rstudio.github.io/DT/server.html
DT::datatable(trafic_incident_report)
## Warning in instance$preRenderHook(instance): It seems your data is too
## big for client-side DataTables. You may consider server-side processing:
## http://rstudio.github.io/DT/server.html
library(leaflet)
## Warning: package 'leaflet' was built under R version 3.4.3
trafic_incident_report<-trafic_incident_report[c(1:500),]
m <- leaflet(trafic_incident_report) %>% addTiles() %>%
  addMarkers(lng = ~Longitude, lat = ~Latitude)
## Warning in validateCoords(lng, lat, funcName): Data contains 5 rows with
## either missing or invalid lat/lon values and will be ignored
m

See where events occur

aaaa

bbb

ccc

## Warning: package 'sunburstR' was built under R version 3.4.3
Legend