Skip to main content
warning

The FICO Data Privacy Policy explains FICO’s collection and use of cookies. Cookies help us remember your settings to provide you with a better browsing experience; allow us to assess, monitor, and improve the website’s performance; and enable our partners to advertise to you. You may disable the cookies by changing the settings in your browser, and you may tell us not to share your cookie data with third parties. By using this website, you consent to the use of cookies as described in the FICO Data Privacy Policy.

Blog Blog
  • Authors
  • Newsroom
  • Events
  • Contact

    Topics

    Please select the blog topics that you are interested in (select all):

    • Email
    • RSS
    • ATOM
    • RDF
    Invalid email address
    CHECK YOUR FICO® SCORE
    • Authors
    • Newsroom
    • Events
    • Contact

    Topics

    Please select the blog topics that you are interested in (select all):

    • Email
    • RSS
    • ATOM
    • RDF
    Invalid email address
    Krzysztof Nalborski

    Krzysztof Nalborski

    All posts by Krzysztof Nalborski

    Krzysztof joined FICO in October 2017 as a data scientist for fraud solutions in EMEA having graduated with an MSc in Big Data and High Performance Computing from University of Liverpool and an MBA focused on Business Data Analytics from Radford University. His diverse academic background enables him to “build a bridge” from artificial intelligence and machine learning to more effective and customer-centric fraud and financial crime solutions.

    Filter Posts By:

    • Fraud Analytics for Open Banking: Multi-Layered Self-Calibrating Models Fraud Analytics for Open Banking: Multi-Layered Self-Calibrating Models
      Fraud Analytics for Open Banking: Multi-Layered Self-Calibrating Models
      January 03, 2019
      Fraud Protection & Compliance

      In my previous post, I described how fraud analytics for open banking work. Following an introduction to behavioral analytics, this post focuses on how the data refined through behavioral profiles are combined in an unsupervised machine learning model to produce a score indicative of fraud or non-fraud. Rationale for Utilising Unsupervised Models Regarding fraud ana…

      Krzysztof Nalborski by Krzysztof Nalborski
    • Fraud Analytics for Open Banking: Behavioral Profiling Fraud Analytics for Open Banking: Behavioral Profiling
      Fraud Analytics for Open Banking: Behavioral Profiling
      December 05, 2018
      Fraud Protection & Compliance

      Digital banking channels are increasingly popular, and behavioral profiling of customers is vital in preventing new types of fraud. The open banking revolution makes understanding each customer’s behavior even more important in preventing fraud by considering all the aspects of transactions. Transactions in the world of open banking contain data not previously seen in…

      Krzysztof Nalborski by Krzysztof Nalborski
    • What Are Fraud Analytics? What Are Fraud Analytics?
      What Are Fraud Analytics?
      October 29, 2018
      Fraud Protection & Compliance

      The recent fascination with artificial intelligence and machine learning has made some of us (naturally intelligent) humans confused about the role that these technologies play in the broader field of fraud analytics. In this blog post, I explain their usage and particularly how they will operate in the open banking revolution. [caption id="attachment_37041" align="a…

      Krzysztof Nalborski by Krzysztof Nalborski
    Show More

    Footer

    • Authors
    • Contact
    • Events
    • News
    Blog

    © 2020 Fair Isaac Corporation. All rights reserved. FICO, the FICO Logo and the FICO product and service names referenced herein are trademarks or registered trademarks of Fair Isaac Corporation in the United States and in other countries. Other product and company names herein may be trademarks of their respective owners.