With the goal of industrializing the credit management industry, Dignisia is a Swedish software company helping European banks and servicers maximize the performance of debt collections and NPL portfolio transactions through the actionable use of data.
In this brief interview, Dignisia’s CEO, Jonny Lingvall answers a few key questions posed by members of SmithNovak, Europe’s leading organizer of events for the Non-Performing Loans market.
How do you see the development of the European NPL market over the next twelve months in terms of stocks, trades and servicing performance? Do you see activity outside the core markets of south Europe?
I think the NPL market will increase in terms of volume and price due to increased demand and quality in the portfolios, but I do not think the increase will be as strong as many others believe. First, we will see an increase in UTPs and then NPLs will follow. The demands from the market on those who handle transactions (buyers and sellers) will increase, which will lead to greater industrialization and digitalization to handle large and numerous transactions. In general, we see great interest from foreign investors in the Italian, and other south European markets.
Can you briefly explain the solutions Dignisia is currently marketing to companies operating in the Non-Performing Loans market?
We're delivering software as a service specifically tailored to credit professionals in over 11 European markets with +50 integrations between creditors and debt collection agencies. The software helps optimize collections performance and NPL sales prices. We've seen uplifts in collection performance of 10+% and similar numbers for NPL-sales prices when utilizing our data format and ready built functionality for analysis/management.
In which parts of the credit management process do you see room for improvement?
The part of a credit’s lifecycle that is most neglected is without doubt at the handover phase to debt collection. Here we see that many creditors and servicers need to improve the conclusions they are drawing from their clients’ payment patterns. With better information, they would be able to improve the performance of their existing collection strategies, basing them on facts rather than gut feeling.
What are the main advantages of your solution to each of the three pillars of the NPL market; the Banks, Funds and Servicers?
A standardized data format that is accepted and implemented on the European market. We’ve developed a unified, granular, and most importantly, light-weight and easily implementable data format. It is currently in use in over 11 European markets with over +50 integrations to both internal and external debt collection units. With this as a foundation, it is easy to apply modern technology for credit optimization.
In your experience, are you seeing an increased willingness on the part of the banks and servicers, in particular, to embrace new technology in the NPL process? Where can technology really make a difference?
Yes, definitely. However, there are concerns from the market about how to transfer to a more data-driven way of working. It is easy to take the easy way out instead of investing the time and money needed for digitalization of the chosen credit management strategy. At the same time, we see that the market has challenges in finding the right expertise and competence, which drives the market to invest in smart technology.
Besides traditional data points (such as age, type of debt, etc), which new variables can unlock relevant insights? How do these help in choosing the best recovery strategy?
Standardized activity-based data, i.e. analyze and follow up which collection activity gives which effect, regardless of whether they are performed internally or via one or several external partners. We are often asked what the optimal collection process for specific industries is. The optimal process is the one you continuously challenge with digitized A/B testing and champion challenger.
How can technology help shorten the bid-ask spread in the NPL market? Is it a useful tool for investors to help them specialize in more profitable niches?
By giving everyone involved a clear and transparent picture of the portfolio's quality and historical workout. We also add the possibility to conduct many sell-side valuations to understand quality differences and optimize sales price. In this same way the software could be useful for investors to quickly analyze larger portfolios to find the one most suitable for them. In cases where the selling party works with our software, a portfolio with high data quality is presented containing both open and closed cases, which creates value for buyers who can keep the risk buffer down and which in turn will lead to minimized bid-ask spread and reduce the threshold for investors to enter new markets and new asset classes.
How does Dignisia software help to deal with challenges around data harmonization? Do you see new standards emerging?
We have only seen the beginning of the requirement for detailed and structured data to optimize chosen credit strategies. This is a trend Dignisia welcomes and supports through our own data format. Then you have the ongoing initiative from the European Banking Authority, which also drives towards a standard on data in the NPL transactions.