credit decision

All posts tagged credit decision

We are hiring – Machine Learning Engineer


Evispot provides the financial industry with the decisions they need in the future – today. We do it by exploring artificial intelligence – because no human, neither configured software can handle the complexity of data that must be evaluated.


With 15 years of experience in the credit industry and a strong domain technology interest, we realized the opportunities AI entails in credit decisions. Traditional decisions models are based on a defined amount of parameters. A defined amount of parameters entail limited answers. The possibility to identify patterns, anomalies and multidimensional relationship has not been possible before – until now. The era of traditional credit models is over. New, constantly optimizing, models are the future.


Evispot is looking for a machine learning engineer to join the team, to take part in the product- and technology development and creating excellent products for the financial industry. You will be a part of disrupting the financial industry and creating next generation credit decisions.

– Take part of Evispot current technology- and product development.
– Develop solutions for real world, large scale problems.
– Hands-on prototyping new algorithms, evaluate with experiments.
– Also, productionize solutions at scale or/and plan for scaling.
– Help drive optimization, testing and tooling to improve data quality.
– Take part of an active start-up who constantly strives to create excellent products.
– Work closely and collaborate with Evispot’s advisors with over 10 years of AI experience.
– Evispot’s office is located in Gothenburg, Sweden.
– Flexible hours and all other startup-related clichés you might desire.


– Background and experience in machine learning or a related field.
Experience of feature engineering and prototyping machine learning applications, that have been deployed to production
– You are well-versed in programming and scripting (not only R and Matlab)
– Experience implementing machine learning systems in Python and R.
– You care about agile software processes, data-driven development, reliability, and disciplined experimentation
– Grit, and a true problem-solving mindset
– You are excited about joining a startup environment where anything & everything is happening at once.


Please contact Tomas Sellden at with your application and questions.

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Tomas SelldenWe are hiring – Machine Learning Engineer

… and the winners are! Evispot AI Challenge

Most Accurate Solution 

1. EZW (70,3%)
By focusing on the core problem EZW was able to developed a superior solution compared to the competition. EZW had a structured pre-processing and used random forest algorithm which resulted in the winning solution.
You now have the right to brag about your machine learning skills! 

A big congrats, well deserved! You are now going to tell Bisnode how they should implement machine learning.

2. Real Human Beings (69,1%)

Well done, Real Human Beings! A well deserved second place! Congratz. You will get azure passes!

3. Klubb Bubbel (64,7%)
Congratz! You will also get azure passes!


Most Innovative Solution 

Deep Engima
Many of the solutions followed a similar processes in terms of pre-processing and choice of algorithm – but Deep Enigma stood out in terms of application area. Deep Engima is winner of the most innovative solution – by proposing a suitable & creative application area of your solution! Congratz!

You are winning a night of beers with Evispot – let’s talk about how to develop your proposed solution!

Once again, a big thanks to Mikael Kågebäck, Christian Lauritzen and David Fendrich in the jury and to our partners! 

Congratulations to the winners! 

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Tomas Sellden… and the winners are! Evispot AI Challenge

Evispot AI Challenge: Powered by Bisnode – has now started!

Yesterday, Evispot kicked off the Evispot AI Challenge, a five day long machine learning competition, co-organized  with Bisnode and Microsoft. With just over 20 teams participating in the challenge Evispot invited the teams to a night of inspiring talks, food & drinks and introduction to the challenge itself. Besides Evispot, we listened to talks from David Fendrich of Crawlica under the theme “Why can we predict anything at all?” and Robert Quinn of IBM under the theme “Did you say Let’s eat Grandpa or Let’s eat, Granpa?”. Now the participants have until Tuesday to complete the case – we are looking forward for the results!


Photo: Fabian Wennerbeck 
Joachim Karlsson, Group Director of Innovation, Bisnode

Joachim introduced Bisnode and their view of the Evispot AI Challenge as well as highlighted the importance of machine learning in the future of credit decisions.



Photo: Fabian Wennerbeck 
”Why can we predict anything at all?” by David Fendrich, CTO Crawlica

David started off by saying that he would give a technical speech, not to talk about business at all. And he certainly did, David speech focused around the Solomonoff induction, Kolmogorov Complexity
and gave some valuable tips of how to tackle AI problems. You can find David’s slide here. 

Photo: Fabian Wennerbeck
“Did you say Let’s eat Grandpa or Let’s eat, Grandpa?” – by Robert Quinn, Senior Software Engineer, IBM

Robert talked about how IBM Watson cognitive journey started with playing Jeopardy. By building a Jeopardy AI-robot, with the two requirements, it should answer within one second and at least be 85% sure to answer the correct answer.

Photo: Fabian Wennerbeck 
Isak, CFO & Co-Founder, Evispot
Isak highlighted the importance of the challenge due to the upcoming regulatory changes in the financial industry.

Photo: Fabian Wennerbeck 
Tomas, CTO & Co-founder,  Evispot
Tomas introduced the challenge in details and declared the challenge’s start. 


Below are more pictures from the evening.

Photo: Fabian Wennerbeck 

Photo: Fabian Wennerbeck 

Photo: Fabian Wennerbeck 

A big thanks to everyone who showed up and had a great evening with us! If you have any questions or comments don’t hesitate to contact us – 

Now we are looking forward for the results!

A special thanks to Fabian Wennerbeck who took the pictures!

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Tomas SelldenEvispot AI Challenge: Powered by Bisnode – has now started!

Credit Scoring on Anonymized Credit Data using Machine Learning

The financial industry has a tradition of data-driven decisions, but uses only a fraction of the available data. Financial companies generate vast volumes of data in their credit operations, which is scarcely feeded back into the operations. From an international perspective, financial companies in Sweden have access to good quality external data. But, there is much to by exploring machine learning to create new insights from the data generated by the credit operations. 


2018 – The Year of Regulations 
Apart from recent advancements in the field of machine learning in credit scoring and rating, 2018 will be a year of major regulatory changes. These regulatory changes, in combination and alone, will become highly important for the implementation of machine learning algorithms in the financial industry. The first regulation, PSD II, will make financial data available through standardised APIs for third parties allowed access by the owner of the data. The second regulation, GDPR, will strengthen the control of the owner of the data (only for physical persons) have on their personal data. The combination of giving stronger control to data owners and opening up the traditionally closed systems expose many opportunities for new entrants. With GDPR the use of personal data in business will be stricter, making anonymisation of data more relevant than ever. In the setting of anonymised data machine learning will play a crucial role to find patterns and anomalies useful for credit assessments.


The Evispot AI Challenge 
Together with Bisnode we are exploring next generation credit decisions by using machine learning on anonymised transaction data. We took it one step further by organising the Evispot AI Challenge, where we asked students of Chalmers University of Technology to help us find innovative solutions.

Joachim Karlsson, Group Director of Innovation at Bisnode, on the collaboration:
”Industry leaders are choosing Bisnode to help them to work better and innovative, to create growth and to find new opportunities using smart data. Our collaboration with Evispot is a way to let innovators take part of Bisnode smart data. Historically, we have positive experience in similar collaborations and we believe there are many good ideas in Evispot’s network and we want to support that.”  


This case reflects one out of many opportunities in using the internal data in credit decisions. The case sets the ground to make way for identifying purchase and payment behaviours to be used in the credit assessment of granting new debts.

Want to take part of the results and insights?  
Fill in your contact details in the following link and we will get back to you:
Follow this link

Do you have any comments, thoughts or questions around this theme?
Don’t hesitate to contact us on or at twitter.

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Tomas SelldenCredit Scoring on Anonymized Credit Data using Machine Learning

Extract Insights from Your Data


We are living in the data age. Every device around us is constantly assessing, calculating and interacting – resulting in enormous amounts of data constantly being created.

The term big data has been frequently used during the last decade. The term is used to describe the collection and analysis of data on a scale or of a complexity that makes the use of data challenging.  Extracting insights and value of these massive datasets is challenging, but when done properly you will find yourself increasingly efficient.

The UK house of commons wrote a study named The big data dilemma on the massive increase of data. The study highlights the importance of taking action and using the data to create valuable insights for your business. To add some perspective: in 2014 204 million emails were sent and every minute 4 million Google search queries were done. Even more astonishing is that 90% of the data currently in the world was created in the last two years and the amount of global data is predicted to grow 40% year on year for the next decade.

– So what can you do?                                     

The credit scoring giant Experian believes the role of big data in financial service is huge, naming fraud detection and general ledger data to gain previously impossible insights as some of many of possible products. Experian states that enabling  ‘real time’ data-decisions is the difference between winners and losers in the financial markets.

This data explosion offers a great opportunity of understanding your environment and peers on a deeper level. Properly exploited, this data should be transformative, increasing efficiency, unlocking new avenues in life-saving research and creating yet unimagined opportunities for innovation. However, the current datasets are nowhere near fully exploited despite research showing that data-driven companies being 10% more productive than those that do not operationalise on their data. Today an estimated 12% of all data analysed, meaning there is yet much to explore.

– Extracting insight and value from these massive data sets is difficult, but when done properly it can be the difference between winning and losing. Evispot was founded on the mission of being experts of insight-extraction in the data age.

Want to learn more about how your business can benefit from data?
Check out the Evi-LAB – our environment for insight extraction.

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Tomas SelldenExtract Insights from Your Data