11institutetext: Japan Advanced Institute of Science and Technology, Ishikawa
9231292, JAPAN
11email<EMAIL_ADDRESS>
# Find Your ASMR: A Perceptual Retrieval Interface for Autonomous Sensory
Meridian Response Videos

Qi Zhou  Jiahao Weng  Haoran Xie

###### Abstract

Autonomous sensory meridian response (ASMR) is a type of video contents
designed to help people relax and feel comfortable. Users usually retrieve
ASMR contents from various video websites using only keywords. However, it is
challenging to examine satisfactory contents to reflect users’ needs for ASMR
videos using keywords or content-based retrieval. To solve this issue, we
propose a perceptual video retrieval system for ASMR videos and provide a
novel retrieval user interface that allows users to retrieve content according
to watching purpose and anticipated expectations, such as excitement,
calmness, stress and sadness. An ASMR video perception dataset is constructed
with annotations on affective responses after watching the videos. To verify
the proposed video retrieval system, a user study is conducted showing that
users can retrieve satisfactory ASMR contents easily and efficiently compared
to conventional keywords-based retrieval systems.111This is a pre-print
author’s version of this article. The final authenticated version is available
online at proceedings of HCII 2022(International Conference on Human-Computer
Interaction)

###### Keywords:

ASMR video retrieval user interface user perception.

##  1 Introduction

Autonomous sensory meridian response (ASMR) is a type of video content that
has become popular in recent years due to the pervasive influence of social
medias, such as YouTube and TikTok. Especially for young people, ASMR has
changed their life styles with the daily use of applications for relaxing and
sleeping. As reported in the previous studies, ASMR videos can bring users the
sensation phenomenon called tingles [1, 7]. This sensation is mainly felt at
the back of the users’ heads and is accompanied by a sense of pleasure and
relaxation. However, examining satisfactory ASMR videos from conventional
retrieval interfaces remains a challenging issue.

As shown in Figure 1, the titles of ASMR videos usually describe a simple and
personal introduction to the video content and have difficulty describing
videos for special retrieval purposes, such as relaxation and looking for
companionship and attention. The video frames of ASMR videos are usually
produced with the action sounds and spoken voices. Classifying videos with
multi-modal information is a complicated issue. Therefore, conventional
keywords-based and content-based video retrieval approaches may fail for ASMR
videos. In such cases, the users may want to relax but continuously switch
ASMR videos because they are dissatisfied with the retrieved results. They
wasted time and become unable to relax.

To solve these issues, we propose a novel perceptual video retrieval interface
for ASMR videos. In the proposed system, an ASMR video dataset from online
sources was constructed. Then, the participants were asked to evaluate the
perception scores of all the collected videos. We implemented a perceptual
video retrieval interface with perception filters. We conducted a comparison
study between the proposed system and conventional retrieval interfaces to
verify the user experience in the user study.

Figure 1: Finding satisfactory ASMR videos using only the keywords in the
video titles is difficult. (a)–(d) indicate the four different categories of
ASMR videos used in this work.

##  2 Related Works

ASMR is a sensory phenomenon that includes different triggers in videos, such
as whispering, personal attention, crisp sounds and slow movements. This
sensory– emotional phenomenon can be felt in listeners’ head, neck and
shoulders [1]. The sensitivity of the triggers can be measured with a resting-
state functional magnetic resonance imaging scan [9]. ASMR videos have been
investigated to study the emotional and physiological correlation with
responses [7]. Aside from the tingling sensation, ASMR videos have been
reported to relate to experiences of social connection and physical intimacy
[2]. An online community of video sharing was found to have various ASMR
videos created by ASMR artists looking for cultural and scientific legitimacy
[8]. In this work, we focus on the video retrieval of ASMR videos.

The common approaches for video retrieval are keyword and content-based video
indexing and retrieval [10]. A hierarchical retrieval interface was proposed
to explore video content through poster-style summarization [12]. A
perception-based approach was explored to achieve the desired design using
sensation words [4]. A perceptual video summarization and retrieval was
proposed to provide a precise representation of video contents [11]. The
interaction modalities and parasocial attractions of ASMR videos was annotated
for multi-modal video interactions [5]. However, an effective way to explore
ASMR videos has been lacking in previous works. To solve this issue, we aimed
to achieve perceptual retrieval by annotating the videos in the dataset
construction.

##  3 Retrieval System

###  3.1 System Overview

The proposed retrieval system provides a perceptual retrieval interface in
which users can adjust their perceptual parameters to find satisfactory ASMR
videos as shown in Figure 2. Users can adjust the application purpose of
watching ASMR videos, the desired level of tingles, and the perceptual
expectations. For the retrieval system, an ASMR video dataset was constructed,
and the participants were asked to evaluate the videos for the level of
tingles and perceptual expectations. The proposed system was confirmed to be
superior in terms of retrieval time cost and the quality of retrieved videos
with satisfactory usability scales.

Figure 2: The proposed perceptual video retrieval interface.

###  3.2 ASMR Video Dataset

We classified all the collected videos into four video categories according to
previous findings [7]: (a) spoken with high interactivity, (b) spoken with low
interactivity, (c) no spoken and one or a few contents, and (d) no spoken and
multiple contents. 1 shows example videos of the different categories. In
total, 131 ASMR videos were collected from YouTube: 41 videos for (a), 29
videos for (b), 36 videos for (c), and 25 videos for (d). The representative
content of each video was selected manually and cut into 3–5 min video clips.

###  3.3 Perceptual Annotation

For all the collected videos in the dataset, the ASMR videos were annotated
with the following perception metrics: (a) Anticipated applications: Five
purposes of watching ASMR videos from the typical scenarios of watching ASMR
videos were presented: sleep, relaxation, concentration, companionship, and
attention. (b) Tingles: This refers to the degree of stimulating effect of the
ASMR video. (c) Perceptual expectation: This refers to positive effects on
human emotions.

According to a previous study [7], the perceptual expectations were divided
into four categories, namely excitement, calmness, sadness, and stress, which
were used to measure users’ perceptual expectations after watching the ASMR
video. We adopted these four expressions for the video annotation.

We asked four participants (female graduate students) to join our video
annotation. The participants were asked to watch the ASMR videos and annotated
them using the aforementioned perception metrics. For each video, the
participants were asked to answer the following six questions on a seven-point
Likert scale, with 1 indicating strong disagreement and 7 indicating strong
agreement.

  * Q1

Can you feel tingles from this ASMR video?

  * Q2

Do you feel more excited after watching the video?

  * Q3

Do you feel calmer after watching the video?

  * Q4

Do you feel sadder after watching the video?

  * Q5

Do you feel more stressed after watching the video?

  * Q6

For which purpose do you think this ASMR video is suitable? (multiple-choice
questions)

According to a survey of the participants (works) in advance, all four
participants had experience watching ASMR videos. They had different
preferences for ASMR, with two of them liking humans speaking in ASMR videos
and the others liking ASMR videos without speaking. Moreover, two participants
were more satisfied with videos that made people calmer, and the other two
were more satisfied with videos that made people more excited. All videos were
randomly assigned to the participants according to the four categories (Figure
1).

###  3.4 User Interface

As shown in Figure 2, we designed a novel perceptual video retrieval interface
with a perception filter for an advance search. For the filer, we created two
sections, namely, the video content section and the perceptional retrieval
section, to fulfill the user search scenario. The video content section has
three items: applications, spoken, and tingles. Application denotes retrieval
for the specific purpose of watching, and spoken denotes searching for videos
that have or do not have vocals. Users employ a two-handle slider to select
the range of the tingle feature. The perceptional retrieval section has four
items: excitement, calmness, stress, and sadness. These items also use a two-
handle slider for range selection.

Figure 3: Workflow of the perceptual filter in the proposed user interface.

When users chooses one watching application, the system automatically
determines the maximum and minimum video perception values in the dataset and
changes the corresponding values on the sliders simultaneously, as shown in
the red box in Figure 3. The default states of the sliders are illustrated in
Figure 2, When users change the range of a specific item, the slider can be
changed to the activated state, as shown in the blue box in Figure 3.

Figure 4: Conventional video retrieval interfaces used in the comparison
study. UI-1 represents keyword-based retrieval, and UI-2 represents content-
based retrieval.

##  4 User Study

###  4.1 Comparison Study

We conducted a comparative study between the proposed perceptual retrieval
interface and two conventional retrieval approaches: keyword-based video
retrieval (UI-1) and content-based video retrieval (UI-2). These two user
interfaces were implemented for the user study, as shown in Figure 4. UI-1
denotes a traditional user interface that only has a keyword search, and UI-2
has has a combined traditional user interface and the video content section of
the proposed system.

All participants were asked to use each of the three video retrieval
interfaces to complete three different assigned tasks. Our task was designed
based on a specific scene, the content of the video, and the perceptual
expectations after watching the video. For example, “You are going to rest and
sleep. Please find as many suitable ASMR videos as possible (no spoken, used
for relaxation, and can make people calmer or more excited).”

We invited six graduate students (three males and three females), all of whom
familiar with ASMR videos, to join the study. The participants were randomly
assigned retrieval and permutation tasks. After the participants retrieved the
ASMR videos, they were asked to watch them in order, from beginning to end,
and confirm whether they were satisfactory. The amount of time the participant
took to find the first satisfactory video and the time interval between
finding two satisfactory videos were set as the criteria for evaluating the
proposed system. The total number of video views and the number of
satisfaction videos for each participant were also recorded.

###  4.2 User Experience Study

We asked six graduate students (two males and four females), all of whom were
familiar with ASMR videos, to join the user experience study. They were asked
to use the proposed retrieval system to complete two tasks:

  * (1)

Find as many ASMR videos as possible, with constraints of no spoken, and for
relaxation and calming applications.

  * (2)

Find satisfactory ASMR videos easily.

After completing each task, the participants watched the retrieved videos for
5-10 min to determine whether they were satisfied with the retrieved results.
They were then asked to answer question items from the system usability scale
(SUS).

##  5 Results

Figure 5: Amount of time for finding the first satisfactory video.

###  5.1 Implementation Details

This system was implemented on Python, and used a Django 3.2.0 web framework.
Bootstrap 4.6.1, an open source cascading style sheets (css) framework, was
used to render and decorate the website. JavaScript Query 3.6.0 (jQuery), an
open-source JavaScript library, was used to implement user interactions. When
users chose one watching purpose of the application, we used the asynchronous
JavaScript and XML function in jQuery to obtain specific values from the
dataset and modify the values in the sliders without refreshing the website.

A two-handle slider (Figure 3) was designed with a combination of two
traditional (only one handle) sliders. The z-index, a css attribute, was used
to overlap the two traditional sliders. Then, we declared a function to
determine if the two sliders would collide. If the left handle had the same
value as the right one, it would collide. In this case, the left handle would
not be able to move to the right anymore, and vice versa.

###  5.2 Comparison Study

Figure 5 shows that the proposed interface could find satisfactory videos for
all participants in the shortest amount of time. Although our interface took
more time in the initial parameter setting than a conventional keyword
retrieval, more accurate retrieval results were achieved in a significantly
shorter amount of time for the participants to find the first satisfactory
video. When using the keyword retrieval method, some participants found the
first satisfactory video faster because they could quickly locate familiar
video content by inputting keywords. The content-based retrieval method (UI2)
disregarded the emotional needs of the participants. Thus, compared to the
proposed perceptual retrieval system, the variance in the video content
distribution was larger, and the participants have a relatively lower
probability of quickly finding the first satisfactory video.

Figure 6: Time intervals between finding two satisfactory videos.

As shown in Figure 6, a short interval was observed between finding two
satisfying videos consecutively when using the proposed interface. The
proposed system was verified to retrieve more satisfactory videos, and users
had a better experience in finding and switching between satisfactory ASMR
videos. The participants revealed that they usually did not watch ASMR videos
completely. When bored with the content of an ASMR video, they would look for
other videos and switch between them until they find satisfactory video
content. Therefore, we consider that the interval between closing one video
and finding another satisfactory one is an important indicator when evaluating
a retrieval system, as a short interval can reduce the energy loss caused by
switching between videos and significantly increase the comfort of system
users. One of the participants commented the following about the proposed
retrieval system was: “I feel that the retrieved videos were very new and that
most of them were very interesting. I can quickly find the next satisfactory
video.”

As shown in Figure 7, the proposed system can retrieve the highest ratio of
satisfactory videos relative to the total number of viewed videos. The
participants indicated that the proposed retrieval method increased the
diversity of video types retrieved. According to one of the participants, ”I
usually use a few keywords I know to search for ASMR videos, In this way, I
can find videos that meet my preferences. However, after a period, the videos
retrieved using these keywords will have no new content, and most of them I
have already seen. However, your retrieval method is not limited to specific
video content, and it can find many videos with unexpected new content.”

Figure 7: Ratio of satisfactory videos to total viewed videos.

###  5.3 User Experience

The results of System Usability Scale (SUS) questions are shown in Figure 8.
Five participants reported that they were willing to use our retrieval system
regularly confident in using it. They found the proposed system easy to learn.
However, four participants reported that the system design was complex. We
intend to improve our interface design in our future work. The average score
of the proposed retrieval interface was 72.08 (out of 100), which implies good
overall usability.

Figure 8: Mean SUS responses from the user study.

##  6 Conclusion

We proposed an ASMR video retrieval interface based on user perceptions. We
collected the annotation data of an ASMR video dataset for watching purposes
and perception of feelings. In contrast to the conventional keyword- and
content-based retrieval interfaces, the proposed retrieval interface achieved
better retrieval quantity and accuracyat less time. Through the system
usability experiment, the proposed system was verified to achieve good overall
usability.

In future work, we intend to increase the number of participants in the user
study and the number of participants and videos during video annotation. Using
a deep supervised learning approach for the estimation of perceptual metrics
of an unknown ASMR video using the annotation dataset is a promising topic.
The proposed interface design can be improved for simplicity of use. We also
plan to examine the use of a perception-driven interface for other daily
activities, such as taking selfies [3] and animation design [6].

## Acknowledgement

The authors thank the anonymous reviewers for their valuable comments. This
project has been partially funded by JAIST Research Grant and JSPS KAKENHI
grant JP20K19845, Japan.

## References

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[table]style=plaintop [table]font=scriptsize capbtabboxtable[][]

11institutetext:  Sapienza University of Rome, Rome, Italy, 11email:
<EMAIL_ADDRESS>22institutetext: Utrecht University, Utrecht,
Netherlands, 22email<EMAIL_ADDRESS>
# Transforming Credit Guarantee Schemes with Distributed Ledger Technology

Sabrina Leo 11 0000-0002-5157-2135 Andrea Delle Foglie 11 0000-0002-8946-6338
Luca Barbaro 11 0000-0002-2975-5330 Edoardo Marangone 11 0000-0002-0565-9168
Ida Claudia Panetta 11 0000-0001-7019-3993 Claudio Di Ciccio 22
0000-0001-5570-0475

###### Abstract

Credit Guarantee Schemes (CGSs) are crucial in mitigating SMEs’ financial
constraints. However, they are renownedly affected by critical shortcomings,
such as a lack of financial sustainability and operational efficiency.
Distributed Ledger Technologies (DLTs) have shown significant revolutionary
influence in several sectors, including finance and banking, thanks to the
full operational traceability they bring alongside verifiable computation.
Nevertheless, the potential synergy between DLTs and CGSs has not been
thoroughly investigated yet. This paper proposes a comprehensive framework to
utilise DLTs, particularly blockchain technologies, in CGS processes to
improve operational efficiency and effectiveness. To this end, we compare key
architectural characteristics considering access level, governance structure,
and consensus method, to examine their fit with CGS processes. We believe this
study can guide policymakers and stakeholders, thereby stimulating further
innovation in this promising field.

###### Keywords:

Distributed Ledger Technologies Blockchain Credit Guarantee Schemes SME
Finance

##  1 Introduction

In the credit industry, a guarantee reduces the financial risk of loans by
providing a lending bank with additional assurances, increasing the likelihood
of capital.111European Central Bank: “What is collateral?” (2016):
www.ecb.europa.eu/ecb/educational/ explainers/tell-me/html/collateral.en.html
It also signals the borrower’s intention to repay, reducing monitoring costs.
Credit Guarantee Schemes (CGSs) act as a third-party provider of credit risk
mitigation to lenders. By effectively reducing the risk associated with
lending, they incentivise financial institutions to extend credit to Small and
Medium-sized Enterprises (SMEs), thereby enhancing their financial stability
and prospects for growth. CGSs received increased attention during the
COVID-19 pandemic as government credit guarantee programmes improved banks’
balance sheets and facilitated credit extensions to creditworthy businesses.
The positive impact on post-crisis productivity was attributed to expanded
coverage and simplified procedures in these schemes [7, 10].

However, the literature has highlighted the financial sustainability issues of
CGSs, particularly the risk of high default rates, which can force them to pay
significant rewards [2]. A common criticism concerns the lack of transparency
between the parties involved in the transaction (from customer to CGS and from
bank to CGS), which leads to problems such as moral hazard for borrowers or
adverse lender selection. Furthermore, the correct assessment of the
customer’s creditworthiness and the procedure’s cost-effectiveness influence
the credit guarantees’ additional attributes. Therefore, CGS’s potential also
depends on the sustainability and efficiency of its operational processes.

Emerging Distributed Ledger Technologies (DLTs), such as blockchain, open up a
chance for processes involving third parties to be trustworthily executed
[13], particularly in scenarios where there is a lack of mutual trust and
confidence between the parties. Specifically, by leveraging blockchain’s main
features, including operational traceability and transparency, it is possible
to minimise the risk of fraudulent activities, enhance customer trust, lower
operational costs through process automation support, and reduce downtime.

In this paper, we describe the main challenges and opportunities of blockchain
technology adoption for addressing the inherent weaknesses of traditional
CGSs. We also suggest a complete framework that includes all the important
steps in the CGS operational process, from the application to possibly
enforcing safety measures. This framework will help identify key areas that
could benefit from integration with DLTs. Given the specificity of the
procedures, the actors involved, and data sensitivity in transactions, our
paper raises questions about the appropriate blockchain architecture that can
improve transparency, security, and automation throughout the entire CGS
lifecycle. Our paper provides a roadmap for policymakers, financial
institutions, and stakeholders who seek to modernise and optimise CGS
mechanisms. To the best of our knowledge, this is the first endeavour
exploring a synergy between DLT and CGS. We hope it can serve to stimulate
further research and innovation in this nascent yet promising field.

In the following, Sect. 2, outlines the core ideas that form the basis of our
proposal. In Sect. 3, we discuss why given blockchain configurations are
suitable our setting. Section 4 describes their possible application in the
credit guarantee life cycle. Finally, Sect. 5 concludes the paper.

##  2 Background

###  2.1 Distributed Ledger Technologies

Distributed Ledger Technologies (DLTs) comprehend protocols designed to enable
the transactions’ storage, processing, and validation within a decentralised
network of interconnected peers. A distributed ledger is a registry replicated
over a network of computing systems (henceforth, _nodes_) that records the
sequence of transactions containing the transfer of value or data between
sender and recipient accounts [11]. Its distributed architecture obviates the
necessity for centralised authorities or intermediaries in data management.
Every transaction within this framework features a timestamp and a unique
cryptographic signature to prove that the account’s owner issued it.
Signatures are generated utilising a public/private key scheme, where each
user possesses an account associated with a distinct address to which these
keys are linked. This setting guarantees pseudonymity. We recall that
pseudonymity differs from anonymity in that a unique identifier (in this case,
the account number) is associated with the same individual, singled out across
the registered data. The list of the shared transactions contained in the
ledger is accessible to all network participants (owing to its public nature)
so that everyone can verify that the digital signature belongs to the owner
and trace all the transfers from or to an account.

Blockchain, a widely known class of DLT, entails aggregating of ledger
segments into blocks, which are then sequentially linked backwards to form an
immutable chain. The integrity of DLTs, including blockchain, is fortified
through a confluence of cryptographic methodologies and the distributed
validation of transactions. In blockchains, every block is linked to the
preceding one by keeping in the former a fingerprint number identifying the
latter. This fingerprint is yielded by a mathematical function called
_hashing_. Hashing produces a number (the hash). It is deterministic (given
the same data, the same hash is returned) but one-way (hashes cannot be
reverse-engineered to retrieve the input). Altering a bit turns the associated
hash into a completely different number. Well-known blockchain platforms such
as Bitcoin [22], Ethereum [27], and Algorand [5] necessitate transaction fees
to allow for the submission and processing of transactions. Fees serve as an
economic incentive to remunerate the computing systems in the network which
include and maintain the infrastructure up and running. To ensure a single,
reliable and generally acknowledged version of the transaction record,
blockchains rely on consensus algorithms. These algorithms guarantee that all
participants agree on the content of the ledger and that only trusted nodes
can add new information. Proof of Work (PoW) [15] and Proof of Stake (PoS)
[24] are two renowned consensus mechanisms used to validate transactions and
add new blocks to a blockchain. Blockchain platforms such as Ethereum and
Algorand offer the capability to execute smart contracts, namely executable
programs that are deployed, stored, and run within the blockchain environment
[8]. Smart contracts’ operations are triggered by transactions, hence without
the involvement of a trusted third party. Therefore, the history of
invocations can be verified, replayed and trusted throughout the whole
network. As with transactions, the execution of smart contract code is subject
to costs that fall under the name of _gas_ in the Ethereum nomenclature. These
costs depend on the complexity of the invoked code and the amount of data
exchanged and stored. To reduce the invocation costs of smart contracts,
external peer-to-peer systems are typically employed to save larger chunks of
data. Inter Planetary File System (IPFS)222ipfs.tech is one of the most
commonly used distributed systems to store data across multiple peers without
the involvement of any central authority or trusted organisation. The address
of an IPFS file is based on the hash of the file itself, so that the contents
and its locator are immutably bound. The locator is thus typically saved by
smart contracts, which permanently store the link to that resource on-chain.

Blockchains are often classified according to transactability (public or
private) and consensus mechanism (permissionless or permissioned). If a
blockchain is public, every node is endowed with the capability to initiate
and monitor transactions. This fosters a transparent environment readily
accessible to any users. In contrast, the blockchain is private if only
selected nodes are entitled to participate in transaction initiation and
observation. If any node in the network can participate in the consensus
decision-making process, the blockchain platform is permissionless. Instead,
if only specific nodes can determine the next status of the blockchain, it is
permissioned. As a result, blockchain platforms are typically classified into
four different categories: public permissionless, public permissioned, private
permissionless and private permissioned. These characteristics discriminate
the suitability of a blockchain platform to a given application scenario.

###  2.2 Credit Guarantee Schemes

SME credit markets are known for experiencing financial constraints and
imperfections such as information asymmetries, insufficient or absence of
recognised collateral, high transaction costs for small-scale lending, and
perceived high risk, all contributing to suboptimal credit allocation. In this
scenario, CGSs are crucial in offering lenders third-party credit risk
mitigation to enhance SMEs’ credit availability, acting as a strategic
component in the market for credit distribution, and minimising distortions in
credit markets. Moreover, CGS can operate as a tool at the disposal of
policymakers to help SMEs finance during an economic downturn when risk
aversion rises and a credit crunch is expected [28].

Numerous stakeholders partake and engage in the proceedings. Government
agencies or Ministries oversee public CGSs by providing policy guidance,
funding, and regulatory frameworks. From their standpoint, CGSs are an
integral part of national development strategies, promoting the growth of SMEs
and financial inclusion [25]. Credit Guarantee Institutions (CGIs) manage
CGSs, evaluate credit risk, provide guarantees, and handle claims. They work
with lenders to reduce credit risk and promote financing for SMEs [18]. Credit
institutions such as banks and microfinance institutions work with CGSs and
CGIs to provide lower-risk loans to SMEs. The ultimate beneficiaries of CGS-
guaranteed credit are SMEs (generally speaking, the borrowers), who use it to
finance their operations and promote investment, growth, and job creation. CGS
enhances credit rating to facilitate business expansion. Investors and
shareholders, according to the type of funds provided (i.e., Mutual Guarantee
Institutions [14], Corporate Guarantee Schemes, Public Guarantee Schemes),
expect different types of returns when supporting the development of SMEs.
External auditors independently evaluate the financial status and adherence to
CGI regulations by assessing their efficiency in supporting the funding of
SMEs. One of the multiple challenges associated with evaluating a CGS concerns
providing useful information for the decision-making of agents who maintain an
interest in the entity [17]. Not all stakeholders have a similar degree of
information at their disposal. On the one hand, internal stakeholders, such as
managers, have unlimited access to information. On the other hand, external
stakeholders, such as resource contributors and others, need to receive
quality information. An important group of stakeholders includes banks, as
they mobilise the guaranteed resources towards the final beneficiary. They
require information that allows them to analyse the financial sustainability
of the CGS and its ability to meet its commitments and comply with Basel III
requirements if applicable.333European Central Bank: “Sound practices in
Counterparty Credit Risk governance and management” (2023).
www.bankingsupervision.europa.eu/legalframework/publiccons/pdf/ccr_report/
ssm.ccrgovernancemanagement_202306.en.pdf In addition, even more relevantly,
throughout the life cycle of the guarantee, banks and CGIs need to constantly
share reliable and up-to-date information on the condition of the borrower
they are helping to finance. In this crowded stage, the presence of a
mechanism that standardises data and optimises information sharing may protect
the interests of all stakeholders.

##  3 Selecting a Blockchain Configuration for CGS Support

This section discusses advantages and challenges that the adoption of
blockchain platforms can bring within the CGS scenario.

Information stored on a ledger is tamper-proof, persistent, and non-
repudiable. The layer of trust that blockchain infrastructures thereby provide
is a key feature in potentially semi-trusted, competitive or untrusted multi-
party business scenarios [26]. Therefore, they are apt for the case of a
complex scenario such as that of CGS processes shown in Sect. 2. Furthermore,
the need to encode the cooperative behaviour of the system supporting CGSs
call for the use of environments that support smart contracts. Existing
mechanisms for the semi-automation of collaborative processes based on smart-
contract enabled platforms provide a fertile ground for our specific use case
[12, 6]. As outlined in Sect. 2, finding a suitable platform category is a
fundamental strategic decision to design a system based on blockchain [29]. In
the following, we outline some key criteria guiding this choice in our
context.

A public permissionless blockchain scheme like that of Ethereum and Algorand
puts the secrecy of confidential data at risk and cannot be used in this
scenario except with the necessary encryption of those reserved pieces of
information. A common approach is to encrypt them via symmetric keys
individually provided for readers [23, 16]. However, this solution entails the
additional overhead of managing keys at an individual level (which undermines
scalability), keeping track of the shared ones (at the risk of breaching
confidentiality), or having multiple duplicates of the same message with
different encryptions (thus creating potential security issues caused by
inconsistent copies). A promising alternative in that scenario is to decouple
the attribution of keys from the individuals retaining them as proposed in the
literature with frameworks such as Control Access via Key Encryption (CAKE)
[20] and Multi-Authority Approach to Transaction Systems for Interoperating
Applications MARTSIA [19]. These solutions, grounded in Attribute-Based
Encryption (ABE) [4], resort to IPFS to store sensitive information and
policies that determine data access based on the certified roles of the actors
(e.g., whether an account is linked to a customer or not, a bank or not, and
so forth). Data are thus encrypted and decrypted with keys that decouple the
individuals from their access grants.

Public permissioned schemes (see, e.g.,
EOSIO444github.com/EOSIO/Documentation/blob/master/TechnicalWhitePaper.md)
have been developed to implement more restrictive consensus mechanisms on
public networks. Public permissioned schemes suffer from the same issue as the
public permissionless ones in terms of confidentiality constraints as the
visibility of the transaction contents remains public. In addition, it may
call for additional decision processes to decide who manages the ledger and
leads consensus. Alternatively, organisations may opt for the implementation
of private blockchains.

Private permissioned networks such as Hyperledger Fabric [1] exert control
over the nodes with mechanisms including the verification of their actual
identities, in line with the Know Your Customer (KYC) principles [21].
Platforms of this sort often include mechanisms for Role Based Access Control
[3]. Another advantage of private blockchain networks is that the transaction
costs, if any, are not bound to conversion into fiat currencies, as in the
case of Ether, Algos, or Bitcoin, which is beneficial for limiting
infrastructural costs. Only a subset of nodes participate in the consensus, so
the content of the ledger is under the control of authoritative entities, too.
These aspects are beneficial to preserve data confidentiality and system
security. However, they demand an initial contracting phase and potentially
conflicting subsequent management of who is in control of the ledger due to
the permissioned nature of the infrastructure. In a setting such as that of
CGSs, wherein a multitude of actors with cooperative scenarios and competing
interests are involved, this situation might turn out to be undesirable.

Private permissionless blockchains, like LTO Network555ltonetwork.com have
recently gained momentum. Similarly to the public permissionless setting, any
node can take part in the consensus algorithm. However, unlike a public
blockchain, only selected nodes are allowed to issue and read transactions.
This hybrid nature is promising in our scenario as the distributed
responsibility over the publication of transactions entails that no complex
management procedures are in place to determine the entities in control of the
ledger’s content. At the same time, only nodes associated with certified
actors enter the network. In our scenario, this implies that the exchanged
information is accessible to the sole actors involved in the CGI.

##  4 Integrating Blockchain into the CGS Workflow

In this section, we represent the key stages of the credit guarantee life
cycle, which includes three actors:  (i) the borrower (the debtor of the loans
or SMEs),  (ii) the bank (the lender) and  (iii) the Credit Guarantee
Institution (CGI, the guarantor) [9].  In particular, we examine individual
guarantee schemes, focusing on two specific aspects related to the timing of
guarantee requests in relation to banks, namely whether these are requested
ex-ante or ex-post. In these schemes, the CGI evaluates each loan application
a lender submits to the bank either before (ex-ante) or after (ex-post). In
Figures 1, 2 and 3, we use flowcharts to highlight the key steps of the
processes where the implementation of blockchain-based solutions can help
improve efficiency and ensure process transparency. In addition, bell-shaped
icons highlight the points where smart contracts may step in.

Figure 1 illustrates an example of an ex-ante application process. The smart
contract and typical blockchain features can be adopted to seamlessly align
with the Know Your Customer (KYC) [21] process required by the CGI, starting
with the receipt of the application form. Smart contracts can automate,
verify, and exchange KYC data safely and transparently by utilising certain
configurations of blockchain-based distributed ledgers, allowing customers to
submit their information.

Once stored on the blockchain, data cannot be altered or deleted, ensuring
protection against fraud and unauthorised access. Furthermore, the network’s
interoperability can enable financial data sharing with the bank after the
guarantee is accepted, enabling the loan application to be submitted. The
smart contract can automate the sharing of KYC data between financial
institutions, minimising the workload on both parties and maintaining
compliance with cross-border requirements. Moreover, it can significantly
speed up the KYC process, leading to quicker onboarding of new clients and
lowering administrative costs, enhancing CGI’s competitiveness. The contract
code can automatically verify the information borrowers submit to approve the
KYC status immediately without manual verification and indicate the absence of
required additional data if need be. The CGI can efficiently interact with the
borrower using a notification system based on the blockchain network. Upon
compliance with the predefined rules and regulations of the smart contract
(i.e., the successful outcome of the procedure), the automatic loan request
can be submitted to the bank. This proposal focuses on applying blockchains to
the CGI collateral issuance process. When considering bank valuation,
interoperability must be deemed to allow all parties to participate in the
blockchain network and possibly incorporate the loan provisioning procedure.

Figure 1: Individual Guarantee Scheme - Ex-ante application flowchart Figure
2: Individual Guarantee Scheme - Ex-post application flowchart

In the ex-post application process (Fig. 2), the bank first evaluates the loan
application and the presence of sufficient collateral. The bank can expedite
the inquiry process by sending the request directly to the CGI if necessary,
as the borrower has already been checked and deemed eligible for the loan. In
contrast with the ex-ante scenario, all subjects can be involved from the
beginning. In this context, the effectiveness of blockchains and smart
contracts depends on their ability to automate and optimise processes by
exploiting the technology’s unique characteristics and on the interoperability
that would allow cooperation and data sharing between the different entities
involved. Additionally, the immutability of DLTs improves openness and
auditability among participants by recording KYC data on the blockchain,
making it readily available to authorised parties. As with the ex-ante
process, setting rules and regulations in the smart contract on the blockchain
network can speed up the onboarding process by allowing the CGI to establish
criteria in advance and verify them automatically.

Figure 3: Credit Guarantee Scheme - Enforcement

After the guarantee is approved and the risk-sharing agreement between the CGI
and the bank has been achieved, the last condition to proceed with the loan
disbursement is the guarantee fee payment verification. Once this condition
has been respected, issuing the guarantee certificate is possible. As
mentioned above in the flowcharts, in this stage, the platform’s
interoperability is essential since all the actors are involved in the
process, and with advanced applications, it should be possible to integrate a
smart loan contract. The smart contract previously deployed in Fig. 1 and Fig.
2 can also include this part of the process by assuming that the CGI approves
the guarantee. As previously mentioned, thanks to the smart contract preset
rules and regulations, most of the process is completely automated, even if
negotiating the line of risk conditions between the bank and the CGI requires
human intervention. However, the exchange of documents and information between
the parties involved is quick and secure, and all the subjects know the
progress at any time.

Finally, when the loan contract starts, the bank begins the loan monitoring
phase, verifying the regularity of payments and the ongoing creditworthiness
of the SME and, if necessary, communicating any changes to the CGIs. As
depicted in Fig. 3, the smart contract can be settled to enforce the guarantee
if the trigger event occurs, such as when the borrower is unable or unwilling
to repay as agreed in the guarantee contract. The smart contract has to
predict the eligibility terms of the claim request by the bank according to
the predetermined line of risk (the preestablished risk hierarchy). Knowing
the risk line in case of default is crucial because if the bank can access the
guarantee before other creditors, it may increase moral hazard, reducing the
motivation to take action against the borrower. The smart contract can contain
predefined conditions and encoded dispute resolution mechanisms. If legal
enforcement is necessary, the contract will automatically initiate predefined
actions, resulting in efficient and cost-effective resolutions compared to
traditional guarantee enforcement. The potential of the blockchain network
perfectly matches the need to check the legacy of legal enforcement in this
stage more than in the previous onboarding stages. Notably, the fact that
different stages of the enforcement process are continuous, transparent, and
immutable on the blockchain makes it easier for everyone involved in the
credit guarantee process to trust each other. This is because everyone can
check the terms and conditions of the agreement and see how it is being
carried out in real-time. Next, we conclude our paper with a summary and
discussion of our findings.

##  5 Conclusion

This paper investigates the potential synergies between DLTs and CGSs by
proposing a comprehensive framework for applying a blockchain to the credit
guarantee life cycle. The framework explores different stages of the process
from the CGI’s point of view, starting from the initial application to the
potential enforcement, when the borrower is unable or unwilling to repay the
loan and the bank claims the guarantee. We are unaware of any papers exploring
the use of DLTs in the CGS process. We aim to initiate a new research
direction by providing detailed information on the procedures, stakeholders,
and data security in transactions. Additionally, we examine criteria to select
a suitable DLT architecture that can enhance transparency, security, and
automation in all stages of CGSs. We hypothesise to build a private
permissionless blockchain that includes the actors involved in the CGS
process. Considering the characteristics of this kind of blockchain compared
to the public ones, only nodes associated with the certified actors can
participate, ensuring the privacy of data in exchanging information. Secondly,
we highlight how certain blockchain-based distributed ledger settings match
the need to automate, verify, and share KYC data securely and transparently,
proceeding without further manual intervention. This application could enhance
the KYC process when onboarding a new borrower/guarantee application to the
CGS blockchain network, making the process more effective and efficient.
Moreover, implementing a blockchain network implies ease of use and
communication between the borrower and the bank with the CGI. If the smart
contract code’s predefined rules and regulations are correctly observed, a
slimmer process allows the borrower to easily proceed with the loan request to
the bank (also thinking about the possibility of improving the
interoperability of the network, including later a smart loan contract). This
addresses the double-screening problem that significantly impacts the
operational procedures of CGSs by allowing the CGI to establish essential
criteria for the borrower’s eligibility for the guarantee request. Our
proposal suggests utilising the blockchain network to notify the guarantee
institution when the enforcement trigger event occurs. At this stage, the CGI
must determine if the bank’s claim request meets the criteria based on the
level of risk and legal enforcement history. The network’s transparency allows
all participants to monitor compliance with terms and conditions, accelerating
the process and reducing moral hazard and irregularities.

Acknowledgements. This work was partly funded by Sapienza University of Rome
under grant RM1221816C0CC0C6 (Distributed Ledger and Credit Guarantee
Schemes). L. Barbaro’s work received funding by the Latium Region under PO
FSE+ grant B83C22004050009 (PPMPP).

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