What is K Linx and how does it work?

K Linx is the A.I. based platform for automated, efficient and simplified reconciliation management.

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 titles the second set, creating links between these entities is the same as to reconcile the payment received.

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 our 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 received credit transfer as SCT or SWIFT. 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 our 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 the collection process, in order to be able to completely manage the dynamics, costs and drawbacks of this crucial component of a company’s life cycle.

What are 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 theserepetitive and low-value activities.

K Linx in the market

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 we 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 fild, with potential partners that can create an acceleration effect on the market, also in other countries.