The Internet of Things (IoT) has been defined as a global infrastructure for the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies (ITU, sd). It is a network of devices, home appliances, vehicles and other things, that are embedded with electronics, software, sensors, and connectivity which enables those things to connect, collect and exchange data (Wikipedia, sd). What does IoT mean for industries and companies. What kind of opportunities offers IoT and are there any challenges?

A lot of industries can benefit from the IoT. Think for example of machines used in the fabrication industry that need to be lubricated once in a while. If a machine is not lubricated on time, the machine could jam which results in a lot of costs. Nowadays, the machines are checked manually if they already need to be lubricated. It could save a lot of time and money if the machines automatically send a signal whenever they need to be lubricated. Another example is a municipality’s streetlights, once is a while a lamp stops functioning. It would again, save a lot of time and cost if the streetlight would send a signal that its lamp needs to be replaced instead of someone who needs to check all the streetlights (Smeets, 2018).

Next to opportunities and benefits, challenges exist. First, a lot of different data is generated by the use of IoT and a lot of different platforms exist which all generate data in a different way. How to connect these data and platforms? This can be very challenging and time-consuming. Next to this, IoT will mean for a lot of companies that they need to change their business model. To take full advantage of IoT, a lot of companies will in the future need to offer more service level agreements (Smeets, 2018).

To conclude, IoT can save a company a lot of time and cost, but also comes with some challenges.

References

ITU. (sd). Internet of Things Global Standards Initiative. Opgeroepen op Octobre 09, 2018, van ITU: https://www.itu.int/en/ITU-T/gsi/iot/Pages/default.aspx

Smeets, P. (2018, Octobre 9). De staat van het Internet of Things: belofte of realiteit? Opgehaald van Dutch Cowboys: https://www.dutchcowboys.nl/technology/de-staat-van-het-internet-of-things-belofte-of-realiteit

Wikipedia. (sd). Internet of things. Opgeroepen op Octobre 9, 2018, van WIkipedia: https://en.wikipedia.org/wiki/Internet_of_things

While searching for some blog inspiration, I found a recent article in the Journal of Management Information Systems that caught my eye. The article is about a study on how data from financial social media can be used to detect the early signs of corporate fraud.

I already knew that social media can be used to collect information about people’s opinions, habits, etc. Also I knew that it is possible to detect fraud by machine learning analyzing financial data. Still it surprises me that by using financial social media data, corporate fraud can be detected. How is this possible?

Well, financial social media like SeekingAlpha or Yahoo Finance contain all kind of information, just like standard social media, such as Facebook.  Only on financial social media you can find user-generated content (UGC) like return on investment, product announcements, etc. The authors of the article I found, show that from UGC, latent features can be derived that are leading for fraud detection.

The authors have developed an algorithm that uses social media features together with traditional data as financial ratios and language-based features. To make this algorithm, systemic functional linguistics (SFL) theory has been used.

After evaluating the performance of the algorithm, the authors found out that their development leads to an 80 percent prediction accuracy, which is higher than the prediction accuracy of currently used procedures. Corporate fraud is a big problem and detecting it using traditional methods can be very challenging and time-consuming. For these reasons, the authors claim that a similar framework system as they invented, should be developed. It could be used by the government, security agencies, research institutes, and others. Several stakeholders would benefit from such a system.

If you want to know more about using financial social media to detect corporate fraud or how the authors have used SFL, I would recommend you to read the article.

Feel free to let me know how you think about my post and if you have any questions, please ask. ?

References:

Dong, W., Liao, S., & Zhang, Z. (2018). Leveraging Financial Social Media Data for. Journal of Management Information Systems, 461-487.