Interview with Mario Farris, founder of K Linx: automated payment matching for enterprise organizations

Today we present an interview with Mario Farris, founder and managing director of K Linx, an innovative fintech startup in the world of money collection.

Hello Mario, tell us a little about yourself and your professional experience.

I have been working in IT for about 25 years, full of enthusiasm and passion. Before this, I spent a few years in the Italian Navy, a life-changing experience of great professional training.

Since 2000 I have set up with two partners an IT services company, Workgroup Consulting, focusing on the banking and insurance world; we deal in software development, design consultancy, and the resale of third-party solutions in the fraud detection business. For some years now, following a successful project that has consolidated our skills in the areas of ​​payments, master data management and credit risk, we decided to invest in creating a market solution dedicated to the specific purpose of ​​automatic reconciliation of money collection.

From this decision K Linx took shape, first as a flagship solution for the Workgroup products, and since last year as an innovative startup of the same name.

What is K Linx and how does it work?

K Linx is essentially a software system that links entities belonging to two different sets. If we imagine that the incoming financial flows constitute the first set, and the credit instruments the second set, creating links between these entities is the same as to reconcile the receipts.

The credit titles, as generically indicated in K Linx, can be composed of any entity for which we expect future payment: invoices, bills, taxes, penalties etc. The heart of the system is a series of algorithms whose task is to answer, automatically, to two simple questions: Who is paying? What is he/she paying? 

From these two answers, the system then determines, from a qualitative point of view, whether it is a full or partial payment, within a specific tolerance.

K Linx was born as a traditional computing software based on Microsoft technologies; the main task of the startup is to migrate the core components of the system towards cognitive computing technologies. We are already deep in this project, as we have designed an artificial neural network able of answering, with definitely better performances than the traditional algorithm, to the first of the two questions mentioned above. Let’s not forget, in fact, that no matter how sophisticated an algorithm may be, there are cases that cannot be entirely managed by it: the so-called doubtful cases that require the supervision of a human operator. With artificial intelligence our ambition is to minimize these cases, to further increase the level of automation and efficiency.

Who is your target?

Unlike from what we thought at the beginning of this adventure, our main customers consist of realities from the financial world: Banks and Financial Companies.

Banks use K Linx in the area of ​​business credit, in particular on the invoice advances. The banks have an interest in monitoring the payments of the invoices with a liquidity advance, both for the refund and for the management of the credit risk.

The financial companies have an interest in the automatic reconciliation of the payments from the loan instalments, in particular those that come in unstructured form.

Generally speaking, our targets include all the realities that have credit consisting of incoming payments. For example, one of the fields in which we are certain there is a need for automation and in which we are eager to propose our platform is that of utilities companies, that consists of large invoices by definition.

What are the benefits in using your solution?

The realities that carry out manual or semi-automatic reconciliation, must face significant costs, since they must form dedicated teams for this purpose. These costs persist even if one relies on companies that perform this kind of administrative services.

With the adoption of our platform, instead, the additional value we offer is that of making an otherwise time- and cost-consuming process more efficient. Another important benefit is the complete governance of receipts, in order to be able to completely manage the dynamics, costs and drawbacks of this crucial component of a company's life cycle.

How many members currently compose your team?

Currently the team consists of 5 technicians coordinated by 1 research and development manager, 1 delivery manager and 1 sales manager for the market proposition. We are looking for new resources, in the field of both Microsoft technologies and artificial intelligence. The main characteristic of the people we are looking for, in addition to an adequate basic technical skill, is their passion, the desire to accept challenges and to be architects in creating something fintastic.

What are unstructured payments? 

I have made reference several times to unstructured payments: we are talking about those forms of payment that are not based around specific positional references, but rather have text fields that can be freely filled. The SEPA or SWIFT transfers are an example of unstructured payments, or better yet, the infamous handwritten bulletins.

Now put yourself in the shoes of the companies that receive daily cash flows: if it is MAV, RIBA, SDD, the reconciliation is carried out by consolidated processes, based on unique identifiers that directly lead to the credit title. Think instead of wire transfers or handwritten bulletins: you need human intervention to correctly interpret them, i.e. repetitive and manual operations. Our platform automatically resolves these operations, thus freeing the resources working on these repetitive and low-value activities.

What are your figures currently?

Although we are still a small reality, we have relevant references in the sectors I mentioned, finance in particular. Last year we have processed about 5 million bank transfers, achieving remarkable matching performances, in some cases equal to 90% of perfect reconciliation.

Which actors or realities would you like to build a partnership with, and why?

There are two areas in which we are very likely to form partnerships:

• the technological field, for a reciprocal exchange of expertise and already implemented components, to be mutually “time to market” on certain aspects; we have recently joined the Fintech District, in which we trust we can develop this kind of synergies.
• the commercial environment, if the potential partner creates an acceleration effect on the market. In this regard we have just concluded an agreement with a foreign company for the development of our offer on a European level, in particular in the Fintech capital cities.

What are the developments in your pipeline? What are you planning to launch, and with what timing?

Our roadmap is very tight; in fact, this year we will be launching several components redesigned with artificial neural networks, as well as developing APIs that will allow us to expand our offer, making it more granular and therefore better suited to the needs of companies, especially those in the financial world. We will be in the “Salone dei Pagamenti” in November for the second time. Stay Tuned! 😊