Forward-looking real time intelligence and Predictive Analysis

AI creates intelligent data


RiskNET [Editor-in-chief]
Forward-looking real time intelligence and Predictive Analysis: AI creates intelligent dataInterview

There is a lot of talk about AI or artificial intelligence. But where are we currently with the forward-looking technology and how can it make a real breakthrough? FIRM spoke to Heiner Pollert, CEO of the Patentpool Group. He is also the first Chair of the German Institute of Invention and an economic senator in Germany's largest business association, the BVMW (Bundesverband mittelständische Wirtschaft, Unternehmerverband Deutschlands e.V. [The German Association for Small and Medium-sized Businesses]).

Where do you think we currently are in terms of data analysis and evaluation here in Germany?

Heiner Pollert: The huge potential of data analysis and evaluation has already been widely recognised. However, what is often still lacking is implementation. At present, only very few companies conduct an advanced analysis of data from different sources and with different structures to identify interrelationships and come up with corresponding findings. This is because it involves much more than just an analysis of information. Classic AI solutions operate in a binary world, in which programs – mainly based on intelligent algorithms – analyse data. This information is normally stored in databases. This kind of classic AI setup inevitably leads to performance problems. The higher the data volume, the more computing power is required. As a result, many people are faced with what seems to be an unresolvable problem. Our new AI solution breaks away from this old paradigm by creating intelligent data. The key is that we don't actually use technology to analyse large volumes of data. What we call our Quantum Relations Machine (QRM) – a big data analysis technology with AI function – reads the data and then breaks it down into individual data atoms. These tiny particles are then linked to all their dependencies and saved in the C+8 data model. This process is similar to how our brains work. It does not differentiate between 'databases' on the one hand and 'programs' on the other. Instead, it uses intelligent data – broken down and saved in billions of neurons – that independently responds, learns, calculates, thinks and changes. Based on this model, our AI creates intelligent data that no longer has to be analysed by a program as it already contains the answers to our questions itself.

Up and down the country, artificial intelligence (AI) is being described and fêted as the technology of the future. But, as the old saying goes, the journey is as important as the goal. So what will it take to help AI make the big breakthrough.

Heiner Pollert: That old cliché may sometimes be true, but certainly not when it comes to the development of future technologies in the private sector. The goal is a finished and functioning product that is accepted in the market and can recoup the huge development costs.

Although we can see that a new era is beginning – with the issue of AI attracting much greater attention in society as a whole – Germany tends to be lagging behind when it comes to AI development and market placement. A lot of things need to happen. AI is the future for many industries and sealing yourself off from it or rejecting it will come back to bite you sooner or later. Competitors will simply overtake you. The technology we have developed has already made the breakthrough from a technical perspective. What we lack now is appropriate applications that make our truly ground breaking basic technology usable for customers. The first of these applications are currently in development.

In Germany, we have a situation where some of the established banks are looking around for new business models. Meanwhile, start-ups are making rapid progress with digital ideas and solutions. How can banks benefit from the latest digital business models and what do they have to do in return?

Heiner Pollert: In some cases, the major banks are still behaving very conservatively when it comes to digital transformation – with no sign of adaptation and realignment. German banks in particular have slept through the chance to help shape the digitalisation of their industry and as a result are lagging behind developments. Taking an international comparison, in terms of innovativeness and transaction costs our German banks are way behind their American counterparts.

I think that banks should try to rethink their existing business models, break up their rigid structures and start using new technologies. I would urgently advise institutions to actually buy up and integrate those Fintechs that do things better than they do themselves.

Let's turn to the banking environment. Have we really slept through the digital revolution in the financial services environment?

Heiner Pollert: Yes, definitely, and with potentially fatal long-term consequences – anyone who closes themselves off from the digital revolution will lose out economically down the road. But that's the case in plenty of industries. Innovations are initially ignored and companies view their own business models as sacrosanct – only to be overtaken by competitors from all sides. Many traditional banks still have no clear digitalisation strategy and see the primary use of digital processes as redesigning their communication channels to the customer, for example through apps or online banking. There is clearly a need to catch up here.

What do you think it will take to help new analysis methods and AI to make a bigger breakthrough in the banking sector?

Heiner Pollert: There needs to be a mind change. In the future it will be increasingly important to be able to predict international trade flows, political and social trends, and changes. Referring to all available variables, for investment considerations for example, will increasingly become an almost unresolvable challenge. This is where the new methods and technologies come in.

But it is important to remember that only those who recognise the benefits of AI will be able to play at the top level in the future.

You are working with Prisma Analytics on new data analysis and AI solutions. What does that involve specifically?

Heiner Pollert: Now that the development of the revolutionary C+8 data model has been completed, the team of developers has started programming the first solution that will monetise that technology: the flagship application "Decision Point". The first product from Prisma Analytics GmbH is a research app featuring intelligent research tools, which completely replaces the previous complex and costly process of analysing large volumes of unstructured data. This application will be offered through the EIKON platform by Refinitiv – formerly Thomson Reuters – and will shortly be providing exactly the kind of new analysis methods you asked about.

And if we break down everything to the banking sector, how can decision makers in this sector benefit from Prisma Analytics and its solutions?

Heiner Pollert: Every month, thousands of terabytes of information are imported, broken down, and immediately stored in Prisma Analytics' proprietary C+8 data model. This results in a constantly growing volume of natively arranged dynamic data records that reflects the real world exactly as it behaves in reality. The C+8 parsing engines create a constantly developing network of primarily objects discretely connected to one another, which all associate with one another autonomously through shared connections based on quantifiable dependencies. In this way, Prisma Analytics is creating an organically growing, connected database with native forecasting functions – a kind of machine-based intuition. Our analysis application provides access to all of this inconceivably huge intelligent mass of data. 'Decision Point' uses dependencies rather than correlations for its predictions, enabling extremely complex, multi-stage queries to be calculated, and a previously unachieved quality of predictive analysis to be created. It is an extremely useful tool for decision makers.

Can you give us a specific example?

Heiner Pollert: We are already able to explain medium and long-term market trends with a level of accuracy that has never before been possible. We will be delighted to provide you with more details after the official launch of our "Decision Point" application.

Dr. Heiner Pollert

As CEO of the Patentpool Group, Dr. Heiner Pollert manages and markets patentable innovative technologies. He is also the first Chair of the German Institute of Invention and  an  economic senator  in  Germany's largest business association, the BVMW.

Heiner Pollert: As CEO of the Patentpool Group, Dr. Heiner Pollert manages and markets patentable innovative technologies
Since Prisma Analytics was established in 2016, the Patentpool Group has supported and guided the company as an independent major project. At locations in Munich, Bucharest, Barcelona and Dubai, the core team along with industry experts developed a data evaluation system that combines big data analysis with artificial intelligence and human expertise. The flagship product "Decision Point" is an interactive environment that delivers forward-looking real time intelligence and predictive analysis. "Decision Point" enables banks, governments and non-governmental organisations to acquire advantageous real time information to support complex decisions such as investment strategies, risk management or crisis prevention. Even on the most complex issues, the tool provides sound decision recommendations – linked to forecasts and associated probabilities.

[ Source of images: Adobe Stock | Bildquelle Pollert: Patentpool Group/Sabine Finger ]
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