Who are the MIBI?

The Motor Insurer’s Bureau of Ireland (MIBI) protect victims of road traffic accidents caused by uninsured or unidentified vehicles, in the Republic of Ireland and within the Green Card System of countries including the UK.

The MIBI is an interesting i2 use case for many reasons. In some ways, there is an element of fraud in almost all of their cases. If someone is hit by an uninsured driver, then someone in that story is defrauding someone or even worse committing a crime in some way.

A lot of the time the MIBI only gets one side of the story, this means they rely on their skilled fraud team and i2 deployment to assist them with their investigations.

Suspicious Cases

The MIBI offers a vital service to victims of accidents involving uninsured vehicles. They are also unfortunately the target of fraud.

Remember, there is an element of fraud to all MIBI cases really. So, the MIBI likes to refer to these cases as suspicious cases. Again, the MIBI relies on its skilled team and i2 deployment to help identify these suspicious cases.

It seems the MIBI is good at this, as a number of their suspicions have ultimately led to cases being withdrawn or dismissed in court.

Why i2?

The lead driver behind the i2 deployment is Fraud Manager, Ken McKinlay. Ken has been working with i2 since 2011. He’d been introduced to i2 by the Gardai in a previous role, where he was working on a ring of fraudulent cases. Before i2 he was using flip charts to capture data which was obviously time-consuming.

Ken had some very clear requirements for the system:

• Needed to get up to speed quickly
• It needed to visualise both policy and claim data together as there will definitely be hidden connections there
• The system needed to be pro-active and let the analyst know when an item of interest came up

The MIBI i2 deployment

The MIBI i2 deployment relies on automated feeds from 2 main source systems: An internal case management system called PRESTO and InsuranceLink. InsuranceLink is an external source that insurers use to check the claims history for claimants. The IFB in the UK has something similar.

Automated feeds into i2 are nothing new. Why the MIBI i2 deployment is so special is their use of the i2 suite. The MIBI have really utilised every tool and feature available to them. In some cases, S-branch even developed enhancements so they could utilise the products further

Alerting

The MIBI have around 100 + alerts in their system. This emails them everyday with a list of claims that require looking at. These alerts evolve with the system and are created by the MIBI fraud team

Geospatial Analysis

The i2 deployment is integrated with the MIBI’s GIS mapping solution Esri. This allows the MIBI to Identify hotspots in their iBase data, easily create alerts from repetitive areas of claims or accidents and overlay routes of uninsured Irish cars involved in accidents so that they can be more easily visualised on the maps.

Queries

Queries are a standard feature of i2 iBase, MIBI has really embraced them. Previously queries were being made of the MIBI’s data using tools like crystal reports; making the task far more complex. The ability of the team to ask complex questions easily, ensures the i2 system is fluid and moves with the MIBI’s needs.

Weeding

In order to comply with GRPR deleting or weeding data from i2 in an automated fashion was a necessity. Although i2 iBase didn’t do this out of the box, S-branch assisted in automating this process saving valuable time and preventing mistakes.

Smart Matching

S-branch also implemented some enhanced matching functionality to identify potentially matching claims. Again, i2 iBase didn’t do this out of the box but S-branch assisted in automating this process.

Searching

The MIBI makes use of all the searching tools available in i2. While this is standard usage the team feedback that searching their data has never been easier

Visualisation

i2’s strong point has always been visualisation. The ability to query a particular policy or claim and see all related information instantly in an easy to understand format is invaluable. i2’s ability to draw attention to potentially unseen connections has also proved useful.

The Outcome

Ken uses the word ‘enjoyed’ when he talks about the i2 deployment. The initial deployment was made in around 11 days. Although the initial implementation didn’t include all the features mentioned above, it met the core requirements detailed by Ken.

The beauty of i2 is that the iBase database schema is completely tailored to their needs. MIBI made the decision to keep their schema simple to assist quick analysis. This decision was a good one and it has lead to the MIBI having a very clean, clear i2 deployment that evolves with their needs.

If any of the above could benefit your i2 deployment, you’re looking into i2 or you’re looking into data analysis tools in general; please feel free to contact us.

It’s no secret that i2® is a popular choice for visualising and analysing data. That’s why in 2011 IBM paid a rumoured $500 million to acquire the small British software company. Its flagship product: Analyst’s Notebook has now become the standard for charting data and is used in nearly all of the UK police forces. If you have a sporadic flow of data in formats that vary greatly, IBM i2 is still one of the most compelling tools on the market.

IBM i2® products have always worked well with structured data. This has given its users the ability to ‘bring to life’ data hidden in columns and rows. There are many other places that data can hide though and one of those places is in unstructured text.

Unstructured Data

Unstructured text can pose a challenge to analyse and understand, and we keep generating more of it every day. This text can be anywhere from documents, emails or social media posts. In March 2018 we wrote a blog detailing how data hidden in unstructured text can be utilised. It focussed on the use of Natural Language Processing and particularly Entity Extraction. You can read it here. That blog post concentrated on what could be done using freely available tools.

At the time we stated that there are many commercial offerings that offer that functionality but in a much slicker and easy to access interface. One of those tools is Rosoka Text Analytics. Rosoka is an industry leader of text analytics solutions. Their enterprise solution Rosoka Server is great for large scale analysis of unstructured data. This blog is about their standalone solution which is a plug-in for i2.

So, why is it a ‘no-brainer’?

Well, to start off with its fully integrated with IBM i2 Analyst’s Notebook. It’s a plug-in that has been created in close collaboration with IBM and you can tell. We tested the plug-in against several datasets, including the case study we used in the previous blog post. This data can be found here.

Here are the reasons why we think it’s a ‘no-brainer’ plug-in:

• It extracts entities and links from unstructured files such as PDF’s, Word documents and txt files. It then allows users to generate Analyst’s Notebook charts based on the content
• Processing time is quick compared to reading the documents manually and quicker than the free extraction engines used in our previous blog
• During testing we found the entity extraction to be very accurate. What was more impressive was the relationship extraction. In our previous blog we inferred links based on how many times two entities are mentioned in the same document. What Rosoka do is far more sophisticated and is based on the language around the two entities
• Entity extraction is good but it can create a lot of noise. Rosoka’ s use of Salience (relevance) means we could always find the most relevant extracted entities and ignore the others
• Rosoka applies entity resolution to its extraction. This meant that if Theresa May is mentioned as ‘Theresa’, ‘Mrs May’ or even ‘She’ in a document, Rosoka will be able to resolve these different texts as one entity.
• It’s easy to reclassify an extracted entity from say a person to a company (for example Robert Dyas the UK hardware store). Rosoka can also learn from your decisions so it doesn’t make the same mistake again
• Rosoka is truly multilingual. We tested this by running several news articles about Islamic State through Rosoka in different languages. The organisation Islamic State was mentioned in both the Russian and the Arabic news articles. On the chart they were resolved into one entity, despite them originating from two different languages. That meant that when we expanded Islamic state we got linked items from both the Russian and the Arabic articles.
• The most surprising reason Rosoka is a no-brainer though is the price. For a fraction of the cost of IBM i2 Analyst’s Notebook the plug-in delivers accurate, multilingual, unstructured data analysis. We’ve looked at costs for this type of technology for clients before and often the requirements were dropped, due to budget restrictions; well not with Rosoka!

In conclusion, we believe Rosoka is a ‘no-brainer’ plug-in for i2 Analyst’s Notebook. The functionality, ease of use and price will just make any analysts life easier!

For more information on Rosoka visit their website or contact S-branch. If you’d like to find out more about unstructured data analysis, then feel free to call.

S-branch offers independent advice, meaning if Rosoka is not for you at this time, we can help you find the solution that is.