004 Datenverarbeitung; Informatik
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With open banking, consumers take greater control over their own financial data and share it at their discretion. Using a rich set of loan application data from the largest German FinTech lender in consumer credit, this paper studies what characterizes borrowers who share data and assesses its impact on loan application outcomes. I show that riskier borrowers share data more readily, which subsequently leads to an increase in the probability of loan approval and a reduction in interest rates. The effects hold across all credit risk profiles but are the most pronounced for borrowers with lower credit scores (a higher increase in loan approval rate) and higher credit scores (a larger reduction in interest rate). I also find that standard variables used in credit scoring explain substantially less variation in loan application outcomes when customers share data. Overall, these findings suggest that open banking improves financial inclusion, and also provide policy implications for regulators engaged in the adoption or extension of open banking policies.
With free delivery of products virtually being a standard in E-commerce, product returns pose a major challenge for online retailers and society. For retailers, product returns involve significant transportation, labor, disposal, and administrative costs. From a societal perspective, product returns contribute to greenhouse gas emissions and packaging disposal and are often a waste of natural resources. Therefore, reducing product returns has become a key challenge. This paper develops and validates a novel smart green nudging approach to tackle the problem of product returns during customers’ online shopping processes. We combine a green nudge with a novel data enrichment strategy and a modern causal machine learning method. We first run a large-scale randomized field experiment in the online shop of a German fashion retailer to test the efficacy of a novel green nudge. Subsequently, we fuse the data from about 50,000 customers with publicly-available aggregate data to create what we call enriched digital footprints and train a causal machine learning system capable of optimizing the administration of the green nudge. We report two main findings: First, our field study shows that the large-scale deployment of a simple, low-cost green nudge can significantly reduce product returns while increasing retailer profits. Second, we show how a causal machine learning system trained on the enriched digital footprint can amplify the effectiveness of the green nudge by “smartly” administering it only to certain types of customers. Overall, this paper demonstrates how combining a low-cost marketing instrument, a privacy-preserving data enrichment strategy, and a causal machine learning method can create a win-win situation from both an environmental and economic perspective by simultaneously reducing product returns and increasing retailers’ profits.
Correctness of program transformations and translations in concurrent programming is the focus of our research. In this case study the relation of the synchronous pi-calculus and a core language of Concurrent Haskell (CH) with asynchronous communication is investigated. We show that CH embraces the synchronous pi-calculus. The formal foundations are contextual semantics in both languages, where may- as well as should-convergence are observed. We succeed in defining and proving smart properties of a particular translation mapping the synchronous pi-calculus into CH. This implies that pi-processes are error-free if and only if their translation is an error-free CH-program Our result shows that the chosen semantics is not only powerful, but can also be applied in concrete and technically complex situations. The developed translation uses private names. We also automatically check potentially correct translations that use global names instead of private names. As a complexity parameter we use the number of MVars introduced by the transformation, where MVars are synchronized 1-place buffers. The automated refutation of incorrect translations leads to a classification of potentially correct translations, and to the conjecture that one global MVar is insufficient.
Correctness of program transformations and translations in concurrent programming is the focus of our research. In this case study the relation of the synchronous pi-calculus and a core language of Concurrent Haskell (CH) with asynchronous communication is investigated. We show that CH embraces the synchronous pi-calculus. The formal foundations are contextual semantics in both languages, where may- as well as should-convergence are observed. We succeed in defining and proving smart properties of a particular translation mapping the synchronous pi-calculus into CH. This implies that pi-processes are error-free if and only if their translation is an error-free CH-program Our result shows that the chosen semantics is not only powerful, but can also be applied in concrete and technically complex situations. The developed translation uses private names. We also automatically check potentially correct translations that use global names instead of private names. As a complexity parameter we use the number of MVars introduced by the transformation, where MVars are synchronized 1-place buffers. The automated refutation of incorrect translations leads to a classification of potentially correct translations, and to the conjecture that one global MVar is insufficient.
Correctness of program transformations and translations in concurrent programming is the focus of our research. In this case study the relation of the synchronous pi-calculus and a core language of Concurrent Haskell (CH) with asynchronous communication is investigated. We show that CH embraces the synchronous pi-calculus. The formal foundations are contextual semantics in both languages, where may- as well as should-convergence are observed. We succeed in defining and proving smart properties of a particular translation mapping the synchronous pi-calculus into CH. This implies that pi-processes are error-free if and only if their translation is an error-free CH-program Our result shows that the chosen semantics is not only powerful, but can also be applied in concrete and technically complex situations. The developed translation uses private names. We also automatically check potentially correct translations that use global names instead of private names. As a complexity parameter we use the number of MVars introduced by the transformation, where MVars are synchronized 1-place buffers. The automated refutation of incorrect translations leads to a classification of potentially correct translations, and to the conjecture that one global MVar is insufficient.
We investigate translations from the synchronous pi-calculus
into a core language of Concurrent Haskell (CH). Synchronous messagepassing of the pi-calculus is encoded as sending messages and adding synchronization using Concurrent Haskell’s mutable shared-memory locations (MVars). Our correctness criterion for translations is invariance of may- and should-convergence. This embraces that all executions of a process are error-free if and only if this also holds for the translated program. We exhibit a particular correct translation that uses a fresh, private MVar per communication interaction and that is in addition adequate, and which is also fully abstract on closed expressions. A metaresult is that CH has the expressive power and the concurrency capabilities of the synchronous pi-calculus.
We also automatically check variants of translations of synchronous communication into an asynchronous calculus where only an a priori fixed number of MVars per channel (and not per communication interaction!) is available. We obtain non-correctness results for classes of small translations, and exemplary argue for the correctness (and adequacy) for two translations with a higher number of MVars. We introduce a classification of the potentially correct translations.
We consider matching, rewriting, critical pairs and the Knuth-Bendix confluence test on rewrite rules in a nominal setting extended by atom-variables. Computing critical pairs is done using nominal unification, and rewriting using nominal matching. We utilise atom-variables to formulate rewrite rules, which is an improvement over previous approaches, using usual nominal unification, nominal matching and nominal equivalence of expressions coupled with a freshness constraint. We determine the complexity of several problems in a quantified freshness logic. In particular we show that nominal matching is Πp2-complete. We prove that the adapted Knuth-Bendix confluence test is applicable to a nominal rewrite system with atom-variabes and thus, that there is a decidable test whether confluence of the ground instance of the abstract rewrite system holds. We apply the nominal Knuth Bendix confluence criterion to the theory of monads, and compute a convergent nominal rewrite system modulo alpha-equivalence.
A sound and complete algorithm for nominal unification of higher-order expressions with a recursive let is described, and shown to run in non-deterministic polynomial time. We also explore specializations like nominal letrec-matching for expressions, for DAGs, and for garbage-free expressions and determine their complexity. As extension a nominal unification algorithm for higher-order expressions with recursive let and atom-variables is constructed, where we show that it also runs in non-deterministic polynomial time.
Our recently developed LRSX Tool implements a technique to automatically prove the correctness of program transformations in higher-order program calculi which may permit recursive let-bindings as they occur in functional programming languages. A program transformation is correct if it preserves the observational semantics of programs- In our tool the so-called diagram method is automated by combining unification, matching, and reasoning on alpha-renamings on the higher-order metalanguage, and automating induction proofs via an encoding into termination problems of term rewrite systems. We explain the techniques, we illustrate the usage of the tool, and we report on experiments.
The focus of this paper are space-improvements of programs, which are transformations that do not worsen the space requirement during evaluations. A realistic theoretical treatment must take garbage collection method into account. We investigate space improvements under the assumption of an optimal garbage collector. Such a garbage collector is not implementable, but there is an advantage: The investigations are independent of potential changes in an implementable garbage collector and our results show that the evaluation and other similar transformations are space-improvements.