scholarly journals 'On the Take': The Black Box of Credit Scoring and Mortgage Discrimination

2010 ◽  
Author(s):  
Cassandra Havard
Keyword(s):  
Credit Scoring ◽  
Black Box ◽  
Mortgage Discrimination

scholarly journals Towards an Equitable Digital Society: Artificial Intelligence (AI) and Corporate Digital Responsibility (CDR)

Society ◽  
2021 ◽  
Author(s):  
Karen Elliott ◽  
Rob Price ◽  
Patricia Shaw ◽  
Tasos Spiliotopoulos ◽  
Magdalene Ng ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Financial Services ◽  
Credit Scoring ◽  
Black Box ◽  
Machine Learning Algorithms ◽  
Digital Society ◽  
Digital Era ◽  
Trade Offs ◽  
Raising Awareness ◽  
Arbitrary Precision

AbstractIn the digital era, we witness the increasing use of artificial intelligence (AI) to solve problems, while improving productivity and efficiency. Yet, inevitably costs are involved with delegating power to algorithmically based systems, some of whose workings are opaque and unobservable and thus termed the “black box”. Central to understanding the “black box” is to acknowledge that the algorithm is not mendaciously undertaking this action; it is simply using the recombination afforded to scaled computable machine learning algorithms. But an algorithm with arbitrary precision can easily reconstruct those characteristics and make life-changing decisions, particularly in financial services (credit scoring, risk assessment, etc.), and it could be difficult to reconstruct, if this was done in a fair manner reflecting the values of society. If we permit AI to make life-changing decisions, what are the opportunity costs, data trade-offs, and implications for social, economic, technical, legal, and environmental systems? We find that over 160 ethical AI principles exist, advocating organisations to act responsibly to avoid causing digital societal harms. This maelstrom of guidance, none of which is compulsory, serves to confuse, as opposed to guide. We need to think carefully about how we implement these algorithms, the delegation of decisions and data usage, in the absence of human oversight and AI governance. The paper seeks to harmonise and align approaches, illustrating the opportunities and threats of AI, while raising awareness of Corporate Digital Responsibility (CDR) as a potential collaborative mechanism to demystify governance complexity and to establish an equitable digital society.

scholarly journals Are you a good borrower? Mining interpretable pattern structures in credit scoring

2020 ◽  
Vol 4 (3) ◽  
pp. 67-85
Author(s):  
Sergei O. Kuznetsov ◽  
Alexey Masyutin ◽  
Aleksandr Ageev
Keyword(s):  
Binary Data ◽  
Regression Models ◽  
Design Methodology ◽  
Credit Scoring ◽  
Black Box ◽  
Original Research ◽  
Content Type ◽  
Pattern Structures ◽  
Classification And Regression ◽  
The Cost

Purpose The purpose of this study is to show that closure-based classification and regression models provide both high accuracy and interpretability. Design/methodology/approach Pattern structures allow one to approach the knowledge extraction problem in case of partially ordered descriptions. They provide a way to apply techniques based on closed descriptions to non-binary data. To provide scalability of the approach, the author introduced a lazy (query-based) classification algorithm. Findings The experiments support the hypothesis that closure-based classification and regression allow one to both achieve higher accuracy in scoring models as compared to results obtained with classical banking models and retain interpretability of model results, whereas black-box methods grant better accuracy for the cost of losing interpretability. Originality/value This is an original research showing the advantage of closure-based classification and regression models in the banking sphere.

Antidepressant Black Box Warning Draws Fire by Not Including Suicide Causality

2005 ◽  
Vol 39 (3) ◽  
pp. 24
Author(s):  
KATE JOHNSON
Keyword(s):  
Black Box

FDA: Contrast Agent Black Box Behind NSF Reduction

2010 ◽  
Vol 41 (1) ◽  
pp. 10
Author(s):  
KERRI WACHTER
Keyword(s):  
Contrast Agent ◽  
Black Box

FDA Adds Black Box Warning for Elidel, Protopic

2005 ◽  
Vol 38 (7) ◽  
pp. 49
Author(s):  
DEEANNA FRANKLIN
Keyword(s):  
Black Box

Black Box for Elidel, Pimecrolimus Challenged

2005 ◽  
Vol 38 (9) ◽  
pp. 31
Author(s):  
BETSY BATES
Keyword(s):  
Black Box

MI Warning Added to Rosiglitazone Black Box

2007 ◽  
Vol 40 (23) ◽  
pp. 7
Author(s):  
ELIZABETH MECHCATIE
Keyword(s):  
Black Box

Enbrel Gets Black Box For TB Risk

2008 ◽  
Vol 41 (8) ◽  
pp. 4
Author(s):  
BROOKE MCMANUS
Keyword(s):  
Black Box

Der Rückfall als dysfunktionaler Output der Black Box?

2002 ◽  
Vol 48 (6) ◽  
pp. 460-461
Author(s):  
Felix Tretter
Keyword(s):  
Black Box

Revisiting the Black Box

1989 ◽  
Vol 34 (12) ◽  
pp. 1078-1080
Author(s):  
Deborah A. Phillips
Keyword(s):  
Black Box
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