'On the way to look at Big Data as an asset for CWA 4.0.' EU Right to Suggestion of an IDSS MAS-Based Scoring Case Study in Consumer Credit

Abstract

Nowadays, consumers should fear how some of their demographic, financial, employment or behavioural information might impact their ability to be granted loans. DM approaches, applying ML models, often hide black box correlations. In the 2011 Fábio Silva’s case study, the purposed credit suggestion agent settles the solution to the unenforceable entanglement of a right to explanation in consumer credit. When put into practice, the solvency profile automatically drawn up by the model-based decision agent operates by clustering clients as creditworthy. Alternatively, the suggestion agent operating next externalize a genetic automated counterfactual, revealing why a particular application ends up in a refusal of lending credit. By design, this methodology provides interpretations of which parameters were individually lacking and leads to inverse the non-acceptance outcome, being more feasible and effective for consumer applicants. EU representatives must once and for all perceive data as a real asset. Creditors shall be obliged to ascertain the duty by which clients would achieve specific transactional advantages for providing alternative or missing data.  

Keywords: AI-based CWA, IDSS MAS-based Agent, Right to (Automated) Suggestions.