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Assessing Human Information Processi...

Liu, Miao.

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Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach./
Author:	Liu, Miao.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	113 p.
Notes:	Source: Dissertations Abstracts International, Volume: 82-01, Section: B.
Contained By:	Dissertations Abstracts International82-01B.
Subject:	Accounting. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27994087
ISBN:	9798662406506

Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach.
Liu, Miao.

Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 113 p.

Source: Dissertations Abstracts International, Volume: 82-01, Section: B.

Thesis (Ph.D.)--The University of Chicago, 2020.

This item must not be sold to any third party vendors.

This paper studies factors that determine efficient information processing. I exploit a unique small business lending setting where the entire codified information set that loan officers use in their decision-making is observable (to the researcher). I decompose the loan officers' decisions into a part driven by codified hard information and a part driven by uncodified soft information. I show that a machine learning model substantially outperforms loan officers in processing hard information. Using the machine learning model as a benchmark, I find that limited attention and overreaction to salient information largely explain the loan officers' weakness in processing hard information. However, the loan officers acquire more soft information after seeing salient hard information, suggesting salience has a dual role: it creates bias in hard information processing, but facilitates attention allocation in new information acquisition.

ISBN: 9798662406506Subjects--Topical Terms:

557516
Accounting.
Subjects--Index Terms:

Banking

Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach.
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520 $a This paper studies factors that determine efficient information processing. I exploit a unique small business lending setting where the entire codified information set that loan officers use in their decision-making is observable (to the researcher). I decompose the loan officers' decisions into a part driven by codified hard information and a part driven by uncodified soft information. I show that a machine learning model substantially outperforms loan officers in processing hard information. Using the machine learning model as a benchmark, I find that limited attention and overreaction to salient information largely explain the loan officers' weakness in processing hard information. However, the loan officers acquire more soft information after seeing salient hard information, suggesting salience has a dual role: it creates bias in hard information processing, but facilitates attention allocation in new information acquisition.
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