News 25/06/2018 Liscor on AziendaBanca – Leasing Technology Evolution Azienda Banca interviewed Andrea Villa Luraschi, CEO at Liscor, Vertical Software Vendor of Lutech Group, which provides its end-to-end software platform for the management lifecycle of contracts to financial companies. “In 2017, after the economic recovery that encouraged the revival of investments, there has been an increase of the stipulated leasing, also thanks to a series of facilitating and incentive measures, says Andrea Villa Luraschi. The continuous calls for implementation of our systems from the financial companies was an index of the resumption of the leasing market resumption.” Liscor sees the leasing trend not just like a form of financing, but also as a tool to simplify goods management. This is why Liscor promotes continuous functional evolutions of its software platforms, as well as the use of state-of-the-art technologies. Research & Development is a top priority at Liscor, especially in new fileds such as blockchain and IoT. “FORWARD3000 is our software: web 2.0 responsive, platform independent, developed according to a SOA logic, with an integrated process management engine. It presents unique characteristics - continues Villa Luraschi. From a functional point of view, it is a multi-product and multi-company software. This means that with a single installation it is possible to manage different financial services that can be provided either by a single company or by autonomous legal entities. Click here to read the full interview.
News 12/06/2018 Lutech Group @Job Fair UniMi Lutech awaits you next June 20th, 2018 for La Statale to Jobs at Università degli Studi di Milano. This event is a job fair dedicated to students and graduates at the university headquarters in Milan. Come and meet Lutech at our stand, you will find our professionals that will introduce you your job and career opportunities in a continuously growing Italian company. The meeting between companies and young talents is important to understand each other’s goals, expectations and targets. Sharing the points of strength means sharing growth and success! Your PassiON. Your Career. #joinLutech June 20, 2018, from 10.00AM to 5.00PM Università degli Studi di Milano – HQs – via Festa del Perdono 7, Milano. FREE entrance with online registration for students and graduates of Università degli Studi di Milano.
News 11/06/2018 Cyber Threat Intelligence for understanding threats [kc_row use_container="yes" force="no" column_align="middle" video_mute="no" _id="143334"][kc_column width="12/12" video_mute="no" _id="298733"][kc_column_text _id="390091"] THE SCENERY The data presented in the latest Clusit Report show that the first half of 2017 was the worst ever for cyber security, confirming an inexorable upward trend from 2011 to today: any organization, regardless of size or sector of activity, is concrete risk of suffering a significant cyber attack within the next 12 months. This in the face of ICT security investments still quite insufficient compared to the market value of ICT goods and services. Cybercrime, today, is characterized by attacks aimed at extorting data and money. The media hype that has been created on the subject of security helps companies to become more aware of the risks to which they are subject. Very often, however, attacks are perceived as actions by international criminal organizations, forgetting that sometimes a company's security flaws arise from design errors and security management that can not be resolved by simply identifying the appropriate technology. We need governance, skills and strategy, even more so today that digitalization extends the attack and risk surface. Almost everyone has thought about the protection of PCs and laptops, but only a few companies have installed advanced security systems on their employees' smartphones that represent a very large attack surface. It is therefore necessary to develop a new model of investments in cyber security, adapted to real threats. The answer can be found in the Security by Design approach, that is to think about security already in the design phases of an application or a digital service. Therefore, we must not abandon Digital Transformation or, on the contrary, renounce security in order to have more advanced or innovative features: the real challenge is to integrate security into systems, applications and digital services without precluding usability and experience from users. To be safe and protected, a company must follow a series of rules and processes that are not limited to the implementation of technological solutions but enter into the personal sphere of the behaviors and habits of employees and collaborators. Therefore, we need to think in terms of prevention that declining methods and technologies tailored to the different needs of each company that depend on its nature, the business model, the organizational structure, the awareness of people. [/kc_column_text][kc_column_text _id="379397"] THE LUTECH APPROACH The heart of Lutech's value proposition is based on some pillars: "solid" Security Engineering based on knowledge and the ability to integrate the best technologies in the field of Cyber Intelligence, Breach Monitoring, Incident Response. Lutech's Cyber Threat Intelligence offering provides customers with the support needed to understand consolidated and emerging cyber threats, offering cyber threat detection, analysis and monitoring services. The activities of Intelligence, performed outside the Customer's infrastructure, on the information channels in the visible, deep and dark web, are aimed at collecting the data necessary for the development of information, in some cases even preventive, relating to Cyber Crime. and Fraud Activity, able to support our clients in strategic decision-making and management processes. Also the service of Breach Detection & Incident Response of Lutech (L-BDIR) realizes the monitoring of infrastructure security through the detection and analysis of anomalies in network traffic and execution of application processes, in order to identify, evaluate and responding to external and internal threats to servers, endpoints, mobile devices, applications. Through the use of cloud-based and on-premise technological and service components, L-BDIR collects data and information from the various technologies present in the Customer context and / or offered by Lutech. The detection and response to threats are structured on the model of the "Cyber Kill Chain", with a view to modeling and keeping under control risk scenarios; and to mitigate or remedy the compromise of systems, applications and data, thus reducing the impact on the customer's business. Furthermore, the integration with the Cyber Threat Intelligence services makes the most up-to-date information to the controls and the platforms that can actively use them immediately be activated. Lutech CSIRT Team [/kc_column_text][/kc_column][/kc_row]
News 11/06/2018 Social Analytics: The importance of opinions We are in the age of data, we hear it repeated continuously; the mantra that resounds everywhere, from the press to the generalist sector, is always the same: BIG DATA. Where does this large amount of data come from? And why do we talk about it so much today? The answer is quite simple: we talk about it so much because the data have enormous economic value, especially if they concern people and their behavior. "Data is the new oil", Clive Humby, Mathematician We are talking about "dynamic" data, that is, of those data that change over time, precisely because they are the digital fingerprint of our life in the world, such as passing through a place, our tastes and our opinions, our behavior and relationships with friends and brands. And here is the answer to the first question, most of the data comes from people and devices used by them, such as smartphones, computers, wearable devices, but also from the "things" used by humans such as home automation, smart devices (washing machines) , air conditioners, automobiles, etc.) up to industrial tools, ie from the famous IoT devices (Internet of Things) Summing up then, the huge increase in data is due to the following factors: Today it is no longer just computers and mobile devices that are connected, but everything, even the signals of our body Data transport networks have reached high speeds even on the mobile Users have switched from one-use-to-use-based consumption model (As A Service On Demand) Let's go back to the initial statement: we are in the data age. This statement is so true, that for the first time in modern history, it is technology that is chasing data, not data searching for a technology that supports and generates them. This has, in fact, traced the path of technological macro-trends in the coming years Big Data: understood as the ability to attract, collect, analyze and above all represent a large amount of unstructured data Artificial intelligence: the ability to process data with processes and performances similar to those of human intelligence Blockchain: the technology created to guarantee decentralization, transparency, security and immutability of data. It is precisely on these themes that TEIA Technologies, a company belonging to the Lutech group, focuses precisely on the data age, with the awareness that the value of the data does not lie in the data itself, but in the knowledge we can derive from it. In TEIA we work on the data and with the data to extract, in fact, knowledge. Knowing your customers and prospects is no longer just a competitive advantage, but a necessity that companies can no longer ignore, and that's what we do for our customers and partners: collect and process data using the technologies we've talked about above: Big Data, Artificial Intelligence and Semantic Analysis. The data on which we work are mainly divided into two macro categories: Open data: all data available on public socio-digital channels, such as Social Networks, Forums and Blogs Custom Data: the data that are present in the company, and that almost always are a mine of information not carried to value. Since its foundation in 2013, TEIA has developed and put various products and services in a portfolio, thanks to continuous technological research and collaboration with major universities and research institutions: AI: proprietary artificial intelligence platform, based on machine learning, neural networks and cognitive computing Topic Catcher: semantic clustering ( Custom Data Analyzer: platform dedicated to the analysis, also in real time, o customer custom data, also based on the technological core of Opinion Platform: proprietary opinion analysis platform based on The Opinion Analysis platform is, in fact, the central cornerstone of the company's proposal in the context of Social Analytics. Its main strength is expressed in the ability, enabled by the synergistic use of different AI technologies and semantic analysis, to distinguish between sentiment and opinion, a substantial difference when we want to extract granular and quality information from the analysis of data " Increasingly, Sentiment and Opinion Analysis are used as synonyms to such an extent that even on Wikipedia the definition of Sentiment Analysis reads: "Sentiment analysis (also known as opinion mining) refers to the use [...]". The differences, however, are substantial because identifying the mood of a text is a very different operation than deriving its opinion. Let's try to think of the following sentence: "These cookies are delicious". It is quite simple to attribute the correct mood that, in this case, is "POSITIVE" but if the sentence to be analyzed was the following, what would be its mood? "This brand makes delicious cookies, but they are full of fat and cost too much." Most of the Sentiment Analysis tools would force the attribution of a label through an algorithm based on generic rules of semantic interpretation and, at best, to a text like that of the example would attribute a "NEUTRAL" mood (it could, however, happen that the label assigned is that of "POSITIVE"). It is evident that the result not only does not perfectly reflect reality but provides indications that are potentially the opposite of the real expressed sentiment. The forcing in attributing a mood "at all costs" is one of the main reasons why in the majority of sentiment analysis the percentage of neutrality is very high (above 60-70%), this type of result should be an alarm for those who receive it: on social networks people write to express their opinions or to share information, it is therefore strange to conclude an analysis of this type stating that most of the posts are labeled as "NEUTRAL". The fault of this result is not (only) to be attributed to the tool or the algorithms used in the analysis: try to attribute a sentiment to the offending sentence. I am convinced that most people, at the question "What mood would you attribute to the above sentence?" Would answer “It depends". Here, this is the problem: an analysis tool can not answer "DEPENDS", and without precise instructions can not help but force an answer, even if clearly wrong. Let's try to analyze the previous sentence by placing a well-defined condition: what we would answer if the question were asked as follows: "What is the opinion about the price of cookies?" or "What is the opinion about the taste of cookies?"; in this case, I am sure, the answer would not be “IT DEPENDS" but a very precise label or category. Well, the accuracy of the answers is one of the substantial differences between Sentiment Analysis and Opinion Analysis, but it is obviously not the only one. When we ask someone's opinion, we expect a reasoned answer or otherwise the precise expression of a personal thought. I try to explain once again with an example, to the question "Why do you like these cookies?" What do you expect to be answered? Something like "positive perception" or a structured comment as it could be: "These cookies I like because they know about butter"? Here is another difference between Sentiment Analysis and Opinion Analysis: in the first case, the maximum we can get is a more or less precise representation of the mood around a single and well-defined topic, while in the second case we can get the answers to our questions. As an example, below we show a possible representation of an opinion analysis. In this case, the analysis refers to the user's perception of the assistance services of a manufacturing company operating in consumer electronics: As you can see, regardless of the specific case, the Opinion Analysis allows us not only to determine the mood but also, and above all, to understand the motivations behind it. One of the greatest difficulties in listening to the network is to be able to separate what is an opinion, from what is instead a simple news, ie a post or article that does not express opinion, but that simply shares information, or from communications of the same brand that you want to derive the perceived. Also in this case the simple Sentiment Analysis is not enough, to understand what opinion the people have of our brand, product or service, but it is necessary to rely on the Analysis. The image below shows the graphic effect of the approach described above applied to a survey conducted during the launch of a consumer product: The first thing that is evident is how the volumes at stake are drastically different and how, above all, the number of posts in which users express a real opinion about a particular topic is very less than the number of posts that report generic information but that do not represent the expression of end users, but that is what every brand wants to know when analyzing the opinion of its customers and prospects. The next steps: customers are people, who leave a footprint when they interact with the digital and physical world: they give, sometimes unconsciously, enormous information about their behavior and habits, which can tell us a lot about their personality. It is with this awareness that we are developing a proprietary platform for the analysis of psychometric personality traits. Soon we will be able to tell you that the psychological profile has a person who interacts with certain contents, so as to better calibrate the communication addressed to it. Teia is also very attentive to the security of the data it deals with, so we could not even start working on the blockchain, studying and developing systems for decentralization and information security. Mauro Ferri Co-Founder TEIA, Lutech Group