Sura Bogotá (Prosear) is a Colombian company with 23 years of experience in rental insurance, which provides protection to landlords and real estate agents through rental policies, covering the fee, administration and public services in case of default by tenants.
At KBA, we have been working with Prosear for almost a year now. We started with a simple proof of concept of our product that was successfully completed. Since then, we have been progressively incorporating more functionalities to add value to Prosear. Specifically, we have automated everything related to integration with the credit bureau. Both to collect financial information and the validation and estimation of income.
Likewise, we have contributed to the improvement of risk policies by automating Prosear’s risk policy and jointly developing a decision engine that combines said policy with our SRS artificial intelligence algorithm.
Prosear is a very important client for us and it is an honor to be able to work with them given their long history in the Colombian market and their magnificent reputation. Since we started working with them, we have been impressed by their knowledge of the business, their strategic and future vision, and their agility on a day-to-day basis.
Prosear has had the deference to invest his time in responding to a brief interview to evaluate his impressions and satisfaction with KBA through his manager, Hernando Narváez Rico, and with the collaboration of Óscar Zapata Sandoval, the company’s director of technologies and processes.
We hope that this short interview with Prosear gives you a better and clearer approach to how we work and how we can help in the Colombian leasing market, trying to add value by combining automation and artificial intelligence.
To what extent do you see that technology and digitization are affecting your market?
Hernando Narváez Rico, manager of Prosear, gives us an answer that makes clear the enormous need for process automation in the Colombian leasing market:
“Every time we have much more empowered and informed customers who require an immediate, clear and easy response about our service. They hope that their request will be dealt with online, and that the process will flow in a very agile way. Likewise, if at any time they require assistance or a solution to a concern, they look for an advisor to attend them in a personalized way. If we do not have the capacity to digitally address these needs, they will seek that option with our competition.”
What are your main challenges at a technological and digital level?
“At a technological level, our main challenge is to achieve the automation of processes. In this way, we will be able to deliver an immediate and online response to our clients. From digitization, our main challenge is to be able to align our collaborators to this new way of doing business and get them to transform their operational activities to ones that add greater value.”
In recent months you have been working with KBA. What have been the main factors that have made you work with them?
We have to be honest and confess that Hernando Narváez Rico’s response has made us very happy, since we do our best to offer the most professional results possible:
“We have found in KBA a team of highly trained and professional people, with great ability in developing technology and understanding the business. This has allowed us to optimize the risk analysis process and generate a decision engine that substantially speeds up decision making.”
How do you think KBA can add value to your business?
Through our Machine Learning algorithm we try to respond to the needs of our clients as quickly as possible. This is how the manager of Prosear explains it:
“I believe that KBA adds value by having the ability to bring our business vision closer to the immediacy needs of the market, using technology as a vehicle to reach our customers and solve their requirements.”
What advantages do you see in using a Machine Learning algorithm in risk assessment? Is it useful to have the explanatory variables on the risk prediction, in addition to the probability of default?
The main feature of our algorithm is being able to predict the risk of default with all the information available and quickly adapting to changes in the market. Hernando explains how important it is for Prosear:
“In such a dynamic and changing market, being able to use a Machine Learning algorithm allows us to have a greater degree of certainty in risk analysis. The probability of default that the algorithm adjusts is a valuable input for our decision-making in an agile and controlled manner. “
How do you see the combination of your traditional risk policies with Machine Learning algorithms? Do you see them complementary or substitutes?
At KBA we believe that traditional policies are still of enormous importance today. But, in turn, combined with our algorithm, a tremendously powerful symbiosis can be achieved, and Hernando also thinks so:
“We find power in the combination of traditional policies and the Machine Learning algorithm, since the former help us define a framework of action within which the client can move, and in turn the algorithm helps us identify key variables that they allow an automatic way to deliver a decision that is better adjusted to the level of risk. They are definitely complementary.”
From a technical point of view, how easy has the integration of the algorithm and the software been? What is the opinion of your technology team on this?
Hernando Narváez Rico, manager of Prosear, answers the following: “From a technical point of view, I consider that the process has been quick and easy to adopt. Our technology team has managed to visualize and operate the variables in our system. In addition, we have always had the support and timely accompaniment of KBA.”
And according to the company’s director of technologies and processes, Óscar Zapata Sandoval: “the integration process at a technological level has been quite easy to carry out. We have had the support of the KBA development area at all times. And that, added to an easy-to-understand integration manual, has allowed us to overcome this stage in a short time and with the expected result.”
In addition, Óscar adds that: “the API developed by KBA has a very fast response time, errors and updates are well documented and the language used is very versatile to carry out this type of implementation.”
Lastly, Prosear’s director of technologies and processes wanted to highlight: “KBA has developed and adjusted its solution to the specific needs of our business and they have been in charge of carrying out the most complicated tasks of the process with the aim of making it easier for us to use. At all times we feel the commitment to deliver a solution that from a technical point of view responds to the need raised.”
Would you recommend KBA and its team?
We are happy to share with you the final question from Prosear’s manager, Hernando Narváez Rico, about whether he would recommend us, to which he replied: “I would definitely recommend KBA and his team.”