One could easily think that IT and digitization are somehow the same thing – or at least support one other. The corporate reality is that it is sometimes the opposite. It is often the legacy IT and the IT department that are the obstacle to new digital models. Is there any way to get traditional IT and digitization to work together or do we need total disruption to change things?

Legacy IT systems have been built to support processes and operating models that were dominant when the original systems or architectures were designed. It generally happened before truly digital companies began to emerge. By digital companies I mean companies that are built on digital data, data-oriented processes and models built on digital customer experience. We can see that companies such as Google, Uber and Amazon are examples of really digital companies.

A former bank executive said to me recently that “he hasn’t invested in bank shares for years and at the bank he felt like he was sitting on a time bomb with core legacy IT systems.” He said that everyone knows they cannot continue like that for long, but it is scary to start to replace systems where most people have their money. New systems might offer better services for lower costs but he is not brave enough to take those steps, because something might go wrong.

New regulation, for example GDPR and PSD2 in Europe, have demonstrated how hard it is to live in the digital era with legacy IT systems. For example, banks should be able to provide data to their customers, but how they do it is not very modern. An executive from another bank told me how they employ someone to manually collect data on an Excel sheet, when someone asks to get his or her data, and then email it to the client.

This is very different from the big public talks about open API banking.

In practice we have also seen that IT departments are typically very skeptical about accepting any new systems, even though top management and business leaders would like them to. Someone could say they are conservative and against change but there are also very practical reasons for this. They have a hard time managing the existing systems and typically it has been hard to get the legacy systems to talk to each other. Each new system has meant expensive system integration projects.

Generally, it is hard for incumbent companies to change and change their operating models. That’s why disruption has happened in many industries and new companies have emerged to kill the old companies. In some cases, the old companies have survived, but most of the new business has gone to the new players (for example media companies, telco carriers and bricks and mortar retailers).

But are there some ways to make the transition. There are no simple solutions, certainly no miracles, but we can suggest some things that can help:

1. The top management must understand technology, digital business models and be brave enough to make mandatory changes early enough,
2. The starting point for new services and processes must be the customer value and customer experience, not technology or internal processes,
3. There are technology solutions, e.g. RPA (robotic process automation) that help to make the transition and enable digital processes on the top of legacy systems, thus getting old and new systems to talk each other and at the same time enable significant information work automatization.
4. Everyone in the organization must be ready and open minded to look for better solutions to serve the customers and offer them value. It means people must go outside their comfort zone and admit their old routines don’t always make sense. It is better to proactive than reactive.
5. Find real facts and not just trust beliefs you like. For example, cloud, automation tools and Machine Learning are not security risks compared to the old in-house system. All systems have risks, and it is important to implement and manage them right. The devil is in the detail.

We will see more significant digitization in most industries. It will kill many big companies and create new significant companies. We will definitely see significant changes in the models to manage and use customer data, build digital processes on that customer data and make all operations be based on that data. Management must have the courage to drive those changes, including a complete transition from legacy IT to totally new systems and models.

That said, there are some softer ways to handle the technological change, but even with those models it is fundamental to keep the focus on customer value, not on internal development.

Your focus must not be to develop IT, but your customer value and experience.

The articles first appeared on Disruptive.Asia.

Over the past year, Robocorp has been quietly building open-source tools and a cloud-native platform with the vision of making Robotic Process Automation (RPA) more easily accessible to any company and not just the giant corporations on the Fortune 1000 who benefit from it today.

Today, Robocorp announced it has raised $5.6 million in our first round of institutional funding, led by Benchmark, with participation from Slow Ventures, firstminute Capital, Bret Taylor, President and Chief Product Officer of Salesforce and co-creator of Google Maps, and Rob Bearden, CEO of Docker. Additionally, Benchmark’s Peter Fenton – who has backed numerous successful open source companies from JBoss (acquired by Red Hat), to SpringSource & Zimbra (both acquired by VMware), to Elastic (IPO'd last year) – is joining the board of directors.

With the new funding, Robocorp is now ready to accelerate its growth and take the next step toward democratizing RPA. The RPA industry has seen incredible growth in just the past 2-3 years, with large corporations already benefiting from the automation of millions of routine business tasks, ranging from onboarding new employees to processing insurance claims. But for all the benefits RPA has brought to businesses, it has only been able to help a sliver of the market due to the prohibitively high costs associated with these proprietary tools and the lack of a proper developer ecosystem. 

Ultimately, Robocorp's goal isn’t to just disrupt the RPA tool market, but instead it wants to create a whole new industry that they call robosourcing. Currently, companies looking to gain efficiency and cut costs outsource functions to low-cost regions around the world. In the near future, what will happen is that instead of transferring this work to remote regions, companies will employ robot developers who will automate the work in-house instead. Outsourcing work to robots, or robosourcing, will be a driving force to increase efficiency, reduce errors, improve employee satisfaction, and deliver better customer experience.

Looking ahead to what’s next, with this new funding the company is expanding its operations by tripling its workforce to scale the vision of an open-source RPA ecosystem by creating tools that developers across the world will use to automate tasks. This is a great opportunity to participate in one of the most interesting and fastest-growing enterprise software market at the moment. Robocorp is also hiring people to help it grow the developer ecosystem and create content around the open-source RPA ecosystem.

Read more at Robocorp web site.

See open positions at Robocorp.

Robocorp is set out to change Robotic Process Automation. RPA has the potential to change how millions of people work every day and Robocorp is making it accessible to everyone through open-source technologies, delivered through a cloud platform.

RPA is the fastest-growing segment of the global enterprise software market and we are disrupting it in technology, business model, and ecosystem.

Robocorp is based in San Francisco and Finland. We are actively hiring top software engineering talent to work with us on remote-first basis.

Read more on Robocorp career site.

San Francisco, October 15 2019 – Difitek has appointed Ronald J. Buschur as Chief Executive Officer of the company. Mr. Buschur will work directly with Jouko Ahvenainen, Chairman of the Board and other senior management of the company. Mr. Buschur is an experienced leader, having lead Powerwave Technologies (Nasdaq) global operations and thousands of employees around the world and an experienced entrepreneur, having taken companies from initial stages to the public markets. Mr. Buschur has been an executive advisor to Difitek Inc. since 2016 in its growth in digital finance.

Mr. Buschur comments the new position: “Having seen the growth and working with the company in the digital finance market since an early stage, I’m honored to lead the company to its next phase. The market demand is strong and the company has significant, technology and expertise in the global fintech market and as the industry matures and customers expect better digital finance services, we’re looking forward to offering cloud based finance back office and engine to the market.” 

Mr. Ahvenainen comments: “I’ve worked with Ron in different roles and have seen firsthand his expertise and business acumen. Global fintech adoption is at a key moment, where solutions to drive customer value are being taken to market. Finance institutions are looking for more cost-effective solutions to offer better services to customers. We’re excited about supporting our customers and partners seize these opportunities in the financial markets.”


About Difitek Inc. 

Difitek provides the leading finance engine for digital finance services. It has powered many financial marketplaces in real estate in the US and Europe, in access to capital for individuals and small businesses in South East Asia and new forms of financing in South America. 

More information is available at the company website: www.difitek.com 

For further information, please contact:
Ronald Buschur, CEO 
ron.buschur@difitek.com  
+1 714 414 9820

Photo (from left): Markus Lampinen, Co-founder & Board Member, Jouko Ahvenainen, Chairman, Ron Buschur, CEO.

I​t was maybe two years ago when I was first in discussions about data becoming a liability to companies. Until that time it had only been seen as an asset. This thinking is becoming mainstream and is really changing the behavior of companies. The masterminds that were devising models to get more data five years ago are now concentrating on how to make services that come without ‘data liability’ or are simply creating entirely new data models.

A Google search now reveals several articles about data as a liability and I have raised the subject with many significant tech and consumer companies in Silicon Valley. One very significant company has even told me how they are systematically deleting information that is not directly linked to their core business. Some other companies have mentioned how they had earlier offered data as a bargaining chip to get good deals with other companies. But they have now seen this no longer working for them and many are avoiding collecting data because of the potential liability attached to it.

We are still in a watershed moment; some businesses and business leaders are still in the old paradigm that they want to get more data and believe it is key to their business. But the most advanced companies are finding new ways to get value and new customer relationship models so that they can minimize their liability yet still get value from customer knowledge and also find a fair data relationship with their customers.

These changes and new models are not always easy to explain to the old paradigm people. They might think that the only way to use the data is to have it in their own hands. Of course, new data regulations first in the EU and later, for example, in California or New York will also accelerate this change and understanding. However, it is not easy to understand different models that utilize data if you don’t have the basic knowledge of data science and an understanding of software business models and how software is written, used and distributed nowadays.

Data traders and brokers are the first ones to really suffer from this change. It is not only that companies have become less willing to buy data generally, but the reputation and image of the data trading business has suffered significantly. There are many good reasons for this and we can say that not all of those companies have been ethical or transparent in their business – sometimes with operations in a ‘grey’ area.

There are at least three models to handle data in a new way:

1. Consumers and customers own their own data and it can be utilized in the customer relationship with customer’s consent;
2. Data is kept in distributed solutions (e.g. distributed ledgers) and it can be public or semi-public, depending on its implementation;
3. Relevant data is collected and requested only when needed and it is not stored and specifically not distributed to 3rd parties.

Many new solutions can also combine components of models #1 and #2. Model #3 can also utilize the model #1 approach to get data from the customer. We are still in the early phases of these models, but it is clear there are significant development resources in place to get these to happen with forward-looking businesses actively looking for new solutions.

Some ICO companies have introduced models where people could own their data and then sell it in return for some tokens. This model’s most relevant point is that people could get value from their own data, but in reality, it is very hard to get this kind of market to actually work. The idea of data exchanges and markets is looking quite dead. During the 25-year history of Internet services, we have seen many market place ideas that have not worked in real life. The personal data exchange model is probably one of those.

It is relevant that people get fair value from their own data, but it most probably comes in other formats not necessarily suited for sale in an open market place. And how do you price your data? Can you sell it for one-time use only? Some have compared it to selling one’s own organs, and I can see the point in the comparison.

The key for new data models is to find new customer relationship models. How people can get value from their data in daily situations. The value can be better experiences, better prices and more relevant services. The company must be able to serve the customer better, if the customer shares data in the transactions. Technology, including AI, offers many new ways to achieve this.

Changes take time. Most automobile companies are still making combustion engine cars that are driven by human beings, although everyone knows the future belongs to self-driving electric cars. No serious carmaker can ignore this future and they must also invest in these future cars. It is the same in the data business, many companies must still manage their old model data, but they must prepare for the future of the data business that is much more distributed and customer driven.

The article first appeared on Disruptive.Asia.

Read more about new user-centric data models at Prifina.

Fintech has made quite a lot of headlines, at least in startup publications this decade. But we can still say that actual changes in the finance industry have been quite insignificant and even the new technology, or fintech, has only played a small role – so far. Most changes have happened on the outer peripheries rather than the core. When and how should we expect the big changes to happen?

A new research report Fintech 50 lists the top 50 fintech companies and fintech growth during the last five years. We can see there are some success stories, but if we look at those numbers and companies, we can conclude, fintech hasn’t yet been a threat to traditional finance institutions. Square and Stripe are the top companies on the list, they exist mainly to handle payments. They represent new technology and make payment solutions more cost effective. They are also services for processing transactions rather than actual finance services.

Other companies on the list include also new credit scoring, trading and money transfer services. They are also very transaction-oriented. We still have quite limited changes, e.g. in saving accounts, wealth management, real estate finance, lending and investing services. Robo-advisors is a category that has seen much more talk than real business.

We have heard many reasons why it is so hard to change the finance sector, from regulation to a need for a strong balance sheet, risks and conservative customers who guard their money. But as we know, in many industries big disruption often takes more time than visionary early-adopters expect, but it then comes and maybe in a bigger way than expected. We have seen, how long it has taken the big disruption in retail to really happen.

If we try to think what has been successful in fintech and new finance services, it has been services that are very simple and straightforward to ordinary people. Services to make payments easy, services to transfer money or get small loans when you need them. We can never underestimate, how important convenience is to consumers. It is more important than price, which is also very important.

We have also seen that some new exciting things get traction, but it can be for a short time only. If the value, usability and comprehensibility are not in place, people abandon the services quickly. We have seen equity crowdfunding, ICOs, robo-advisors and P2P lending getting a lot of attention, but the services haven’t been able to offer enough value or they have been too complex to understand or use. There are many reasons for this such as being too complex to understand the real value; difficult to evaluate the services themselves; even bad services and complex finance products or asset classes.

One very significant problem with new finance services is when too many compromises are made, when the services haven’t been disruptive enough. Some finance professionals can challenge this argument, and say you can make new finance services, only if you know the old services well enough and build new products based on that knowledge and experience. But if you do in that way, you just add new stickers on old services, or maybe add some web and mobile functions, but you don’t go to change the fundamentals of the services. The successful online retailers or media services haven’t only added a web services to order items or watch content, but they have build the whole company and operation on moderns digital operations, logistics and models.

If we simplify this real disruption point, we should not expect real new disruptive finance services from London, New York or Singapore, but from San Francisco, Berlin and Shenzhen. They are not built by former bankers, but by software-oriented risk-taking entrepreneurs that are ready to challenge old models, take risks and convince risk taking venture capitalists. 

Many technology solutions in fintech have been based on traditional fundamentals, like centralized solutions that also utilize many old finance world concepts and systems. Although blockchain has suffered from the ICO bubble, it is a model and technology that can offer tools to really change the finance world. Blockchain and distributed ledger solutions generally are also developing behind the scene rapidly. It will be to find the balance between totally wild distributed models and how fast the regulation can develop.

What can we expect in fintech during the next few years? Here are some predictions:

1. Most real disruptive services that produce game changers will come from outside the finance services and former finance industry people;
2. Successful new finance services will not only offer a web or mobile cover to old types of services, but they will also be services and instruments that are fully designed to digital elements and operations;
3. The successful services will be easy to understand and easy to use;
4. Software for new services will be built on the latest models and principles, including open source components, GitHub libraries and open APIs;
5. The services will be very scalable, and should not be compromises of old traditional manual processes, new technology or limited to geographical areas.

We will see much more change in the finance sector, but the timing is always hard to predict and in the finance sector it is even more complex with regulatory constraints. But when we get services that offer significant value to people and attract enough investor money, no regulator or politician will be able to stop them for long. It might sound like a cliché, but we need finance services that really disrupt the industry and not simply cutting corners.

The article was first published on Disruptive.Asia.

Read more about technology solutions for fintech services at Difitek.

Fake news has been a popular topic for a few years, especially how it impacts politics and elections. Fake videos are becoming more relevant too, especially when technology enables the creation of videos where faces and voices can be seamlessly implanted. The most recent Mark Zuckerberg fake video was a reminder that this is really happening. 

However, a potentially more dangerous threat comes from fake data in all formats and why it is also a bigger personal risk than data leakages. 

The idea of fake news, videos or data more generally is to have something that people believe to be authentic or valid, even though it is not. The fake material is then used to change people’s opinion, sway decisions or cast a slur on someone. They are used frequently in politics but can also be used in business, for example, to cause trouble for a company, manipulate stock prices or create support for competitive businesses or companies.

At both business and personal levels, stolen data and misuse of confidential data have been the main issues, e.g. someone uses a company’s business secrets, steals an identity, or reveals personally sensitive information. As we know, this can cause all kind of business and personal issues, but it is not always the worst option – what if data was fake?

Someone can create fake rumors about a person, or a company and they are a kind of fake news. Fake rumors are probably a very old model to cause harm to someone and it is very hard to fight against them, if they are good stories. How about going deeper into your data. What if someone could create a new credit history for you, new family details, a criminal record or health records. Basically, many parties have a lot of data about us and it has a lot of impact on our lives, but if that data was modified, it could really cause trouble.

Let’s imagine a storyline for a thriller where a person’s entire historical information is changed. He doesn’t work in his workplace anymore, he doesn’t live in his house, he isn’t married to his partner, isn’t the parent of his children, doesn’t have access to his bank account and isn’t the person in his passport. Basically, the person would longer be the person in his or her life. The scary part is that this is no longer a fictional plot for a TV series – it could actually happen to someone.

You might say this fake data was easier to create before the digital era with paper documents. While it may be true, with digital information the impact of fake data can be much greater, and it can be generated at a much larger scale. The fake data can be distributed to many places quickly. There are already examples, how a simple error in one master system changed the name of a person, the new name is distributed to all relevant places, including the passport office, health care service and banks. Suddenly the person cannot use any services with his real name and his ID is no longer valid. If your fingerprints and face don’t match the government’s passport and ID database, which is considered to be the real one?

Fighting against fake data needs other means than just protection of data from leaks and theft. We can say there should be enough safe places where the information is hard enough to change. There should also be models on how to handle information that seems to be incorrect. In practice, this requires complex models, with no system totally safe it is hard to know what information is really correct, or if some information has been modified. 

This requires planning on how to handle this risk. Some organizations and people might still say it is enough to have safe authority, bank and health care organization databases that have the master copies of the data, but this is naïve thinking. We have seen enough cases that prove no system is totally safe. 

An important aspect is also the legal protection of individuals. If your digital data is only stored and managed by the government, banks, health care organizations and big companies, how can you prove that your data is correct or even know if it is correct in those systems. Individuals should be able to protect against criminals but also against government, authorities and big businesses. But how do you do it if they manage all your data?

We are starting to see possible solutions to prevent this threat. For example, solutions to control personal data, blockchain type solutions to track all transactions and history of changes and models to check data from reliable sources and verify its integrity. But we are still in the very early stages. The first step is really to recognize the risk and include it in the design and regulation of data systems. Data already plays a central role to drive our daily life. We must be able to guarantee that our data is correct, and that it is me who defines my data and not that the data makes me someone else.

The article first appeared at Disruptive.Asia.

Read more about new data models and virtual assistant at Prifina.

Data has been referred as the oil, blood vessel or cornerstone of business nowadays. But it is a very unequally distributed asset. Some giants, like Facebook, Google and Amazon, have much more than others. Once upon a time the Rockefeller oil company was split under the antirust act. Should the regulators do the same to data giants, or can the market handle them?

​We have many big companies around the world, like telco carriers, retail chains, TV and publishing companies and banks. They have millions of customers in their home and foreign markets. What do they all have in common? They want to utilize customer data in their operations. But suddenly they have found themselves in a situation, where they cannot compete in data with the Internet giants.

Even the biggest publishing companies do not have better or even enough data to compete with Facebook to target advertising. Retail chains cannot compete in data with Amazon. There are also rumors that if these companies were to launch finance services, banks would have a tough time to compete with them. Telcos basically were the source of data, but nowadays Google and Facebook know their customers better.

This situation has especially led the EU to investigate these companies and how they utilize their strong positions in the market. There are, at least, speculations, how Facebook, Google (Alphabet) and Amazon could be split. Amazon’s position, in particular, has created political pressure in the US, when many retailers are in big trouble.

Although we often hear speculation about antitrust laws especially in the US and the EU, it is not so typical to split companies. It is often also said that technology and markets are changing so rapidly today that it is not necessary to split companies anymore. The market will take care of them. A typical example in this context is Microsoft. In the late 1990’s it dominated the PC operating system and software markets. But mobile, Internet and cloud services have changed the market and no one sees Microsoft as dominating the market anymore.

If we think data, is it realistic to think, the market could handle this. There are companies that are data aggregators, collect data from many sources and sell it. In that way companies can buy more data. But probably this is not enough to compete with those that are really in touch (or in the mobiles) of each individual. And privacy requirements have even more impact on data trading than on collecting it.

So, could anyone have more data on you than Facebook, Google or Amazon? There is one party that has even more of your data. But the question is, if this party can really operate on the data market and change the market and competition situation. Or if this party technically can really make it easy to control and use the data?

Who is this party that knows more about you and collects more of your data? Government, bank or your local Internet provider? No, it is you, yourself. You can still know more about yourself than any Internet company and also collect more of your own data. But you would need better tools to do it and to really control your data.

If you can carry your data or purchasing profile to your supermarket, or use your profile to select the best offers for you or to have your financial profile to find loans and wealth management products for you, it would be impossible for Google, Facebook or Amazon to compete with your data. It would be a real disruption for the data market.

Data defines your life and what you can get nowadays. It is a threat that a few gigantic companies in the world control your data. It doesn’t stop with these companies, if governments start to collect all these data points and force companies to hand them over, it can mean many new risks. Data doesn’t only impact your human rights, but it starts to be your human right. 

If the solution for data control is not to split some companies and hope to have governments that respect human rights, but to enable people to own and control their own data. Then it would change the whole data business, how centralized Internet has worked and how people can control their own data. The good news is that distributed data models, blockchain and the changing urgency and discussion about privacy are going to enable this soon.

Once the Internet was expected to make the world more open and equal. It has happened in some areas, but data and some services has become very centralized. Now we see signs, that we can go to more distributed models, where human beings can control their own roles and even get a personal AI to help them.

The article first appeared at Disruptive.Asia.

Read more about personal data and virtual assistant at Prifina.

 ​AI and robots are going to take work from human beings, there is no question about it. The much more complex question, as usual, with new technology, is how exactly it will happen and what is the timetable. We know robots have already taken over some factory work and self-driving cars are coming, but robots are also coming to the office and information work, for example, at JP Morgan, software takes standard legal work from lawyers. But maybe Robot Processing Automation (RPA) and outsourcing office robots is the next big wave to start some real disruption.

RPA is already a two-billion-dollar plus global market and is expected to double in three years. RPA is the technology that allows us to build computer software (“robot”) to emulate the actions of a human interacting with computer systems. RPA robots utilize the user interface to capture data and manipulate applications just like humans do. Basically, it means software uses systems as a human being and can also process data between systems. In practice, it can be simple data transfer from legacy systems to some new system, or from Excel to SAP, but it can be also handle much more complex processes such as insurance claims. 

At the moment the RPA market is dominated by a few big software companies and system integrators that manage implementations. To get to the next level, it needs lower license fees for robots, but also making the actual implementation easier. Easier implementation doesn’t mean only easier tools to make simple tasks, but also more powerful tools to make much more advanced robots that can handle much more demanding jobs, even including AI. A potential business model is to start to offer outsourcing services done by software robots. Business Process Outsourcing market is expected to be a $343 billion market by 2025. We can say it is almost 100 times the current RPA market.

Nowadays RPA is mainly used in larger corporations that want to cut routine work. They make their internal calculations; how much human work must be replaced that they have a business case. Then they approach a larger IT consulting or System Integrator firms and buy an implementation project from them on RPA software. Then they pay license fees to RPA software vendors. The license fees are quite high, so it must be significant savings in the human work that this implementation project and software fees are really justified.

At the same time some companies have hundreds of other tasks that could be automated. And there are also thousands or hundreds of thousands of smaller companies that also must perform a lot of routine work. Let’s think, for example, smaller accounting firms. Their employees use a lot of time copy-pasting information between invoicing, payroll, reporting and accounting systems. Sometimes they build some of their own ‘macros’, but in the most cases it is too complex and they have no time to optimize existing systems and processes. They probably can’t really justify a business case to use the current RPA software solutions.

Let’s then think, if they could easily take a cloud-based robot that starts to handle routine tasks between an invoicing and accounting system. A small company could order a robot online for its specific needs and we had cloud-based solutions where hundreds of thousands of developers could develop and offer their robots to companies of any size. It would be easy and safe to start to use those robots for daily office routines. This would really change the office work and the role of robots in information work. Then it would be easy to build more complex functionality, including AI, into those robots and to get them to execute more and more complex tasks.

We are already seeing all kinds of physical robots. There are industrial robots for manufacturing, waste-processing and transporting items. We also have cleaning robots in homes and self-driving cars. It’s somehow surprising that software robots for office work are still so complex to build and so expensive. It is clear, however, that this is going to change.

Today the RPA market is like any boring B2B software market. As we know, big changes are not really implemented by selling software in a traditional way to companies, especially when the targets are mainly larger companies that are conservative, procurement channels are ultra-conservative and both are influenced by opportunistic IT consulting firms.

It is very evident that software robots will, at some point, be found each and every office. The question is now, how and when it will happen. A strong candidate is to have platforms that easily build and enable robots and offer them for outsourcing work. When it starts to happen in a big way, no office will stay the same. Maybe this is one new area where Silicon Valley and China could start to put money to work?

The article first appeared on Disruptive.Asia. Read more about Robocorp, the leading cloud-based open source software robotics company.

Prifina has been taken position 21 on AngelList's 32 Fastest Growing Startups In San Francisco - Hiring Now - List. AngelList looked through their data to find which companies have added the most employees in 2019, and we selected the leading startups that also have open jobs. They removed any company that didn't include salary/equity data for its jobs. The list includes also companies like Roblox, BlackBird, Truly, and Looker. 

​Prifina offers tools, including personal concierge and AI, and services to manage private data in the digital world. Prifina believes that people must be able to own their own data and have solutions to manage, control and utilize their data. Personal data is fundamental a part of personal wealth. Personal data is a part of personal life. Personal data influences personal life and personal data can have an eternal life. Prifina believes it should be in your personal control and your personal AI will serve you.