Matriz de efectos olvidados en el contexto
financiero de bancos y cooperativas en Ecuador al momento de invertir
Yanice Ordóñez Parra[*]
Stella Lucín Veliz*
Geovanny Zamora Zamora*
Paula Villalpando Cadena*
ABSTRACT
Financial
institutions serve as entities that provide services to families, businesses
and government agencies. The objective of the research is to determine the
optimal investment strategy for the stakeholders. Therefore, two techniques of
data collection and detailed analysis were employed by calculating correlations
and least squares estimations. Concomitantly, an expert approach using fuzzy
logic was used to identify the best financial strategy. This comprehensive
methodology identified financial patterns, providing accurate recommendations
for decision making and boosting the Ecuadorian financial sector. This approach
laid the groundwork for effective and central strategies such as simplifying
contact channels and efficiently optimizing the time invested in the processes,
channeling them towards the continuous improvement of the financial sector and
offering better benefits to users.
Keywords:
Forgotten Effects in Investments,
Ecuadorian Financial Context, Banks and Cooperatives in Ecuador.
RESUMEN
Las instituciones financieras
sirven como entidades que prestan servicios a las familias, empresas y
organismos gubernamentales. El objetivo de la investigación es determinar la
estrategia óptima de inversión para los grupos de interés. Por lo qué, se
emplearon dos técnicas de recopilación de datos y análisis detallado mediante
cálculo de correlaciones y estimaciones de mínimos cuadrados. Concomitante se
utilizó un enfoque de expertos mediante lógica difusa para identificar la mejor
estrategia financiera. Esta metodología integral identificó patrones
financieros, ofreciendo recomendaciones precisas para tomar decisiones e
impulsar al sector financiero ecuatoriano. Este enfoque sentó las bases para
estrategias efectivas y centrales como son, simplificar las vías de contacto y
optimizar eficientemente el tiempo invertido en los procesos, canalizando hacia
la mejora continua del sector financiero y ofreciendo mejores beneficios a los
usuarios.
Palabras clave: Efectos Olvidados en Inversiones, Contexto
Financiero Ecuatoriano, Bancos y Cooperativas en Ecuador.
INTRODUCTION
In the
financial arena, identifying and addressing neglected effects in investment
decisions represents a significant challenge that requires greater attention.
Despite advances in financial management, there are underexplored areas that
may have a crucial impact on the effectiveness of investment strategies and
risk management in financial institutions. In particular, the lack of
comprehensive studies on these overlooked effects highlights the need for
research that addresses this issue in a holistic manner.
This
research process allowed for a critical examination related to monetary terms,
particularly with respect to the volume figures of Segment 1 credit unions in
Ecuador along with private banks. A descriptive scope was maintained and
focused on detailing characteristics within this select group through an
analysis aimed at discerning their relationship within the framework of the
Financial System, as well as the levels of investment acceptance (Avolio, 2016;
Hernández et al., 2014).
The origin
of cooperative movements dates back to Rochdale, England, where a group of
twenty-eight flannel factory workers, affected by the repercussions of the
post-industrial era, decided to open their own store on December 28, 1844.
Thus, they established the principles of the cooperative movement, baptizing
themselves as "The Rochdale Honest Pioneers' Cooperative Society"
(Giraldo et al., 1995; Posso, 2016).
The
evolution of cooperativism in Latin America has been driven by diverse
influences, including the principles of the Catholic Church, local leadership,
anarchist and socialist doctrines, as well as developmentalist state
orientations. Each of these influences played a fundamental role in the
creation of cooperatives motivated by capitalization "for themselves"
or "for others" (ECLAC, 2022; Castellano and Gómez, 2022; Lezama,
2014).
In Ecuador,
cooperative foundations can be traced back to 19th century artisan guilds and
mutual aid societies that provided services such as loans, grants, purchase and
distribution of basic foodstuffs, and savings funds. These functions eventually
led to the transformation of some nonprofit societies into quasi-consumer
cooperatives or credit unions (ECLAC, 2022; Céspedes, 2018).
For its
part, the Basel Committee on Banking Supervision (BCBS) mentions in its 2016
report that financial cooperatives are distinguished by member ownership, where
each member has a vote and receives deposits, being mainly service providers.
However, situations have also arisen where certain cooperatives offer services
outside their membership group (BCBS, 2016; Calvo et al., 2021; Coba-Molina
& Díaz-Córdova, 2022).
According to
Article 163 of the Organic Monetary and Financial Code (COMYF), enacted in
2014, savings and credit cooperatives, associative entities, mutual savings and
credit housing associations, central savings banks or community banks,
including savings banks, constitute the popular and solidarity financial
sector. They also include auxiliary services for the financial system. The
governance of these bodies is based on the guidelines established in the
Organic Law of Popular and Solidarity Economy, as well as in the regulatory
provisions issued by the Monetary and Financial Policy Regulation Board.
The global
financial crisis of 2007 to 2009 highlighted the essential role of banking
supervision in improving the safety, soundness and protection of consumers of
financial services. This implies ensuring that all financial institutions
comply with minimum standards when dealing with clients, avoiding practices
that could harm consumers or pose risks to the solvency of the financial sector
due to the deterioration of public confidence (BCBS, 2016; Velasco, 2018;
Ordóñez et al., 2021a; Illa et al., 2022).
Recently,
the correlation between economic security and the objectives of inclusion and
integrity in the financial infrastructure has been examined. Effective
provisions have been implemented that allow policymakers to foster financial
inclusion and combat money laundering, terrorist financing and other illicit
activities (Ordóñez et al., 2022). International standard-setting bodies have
demonstrated increased awareness of the risks generated by outsiders in key
fiscal interactions (BCBS, 2016).
Within this
context, we can say that, in the financial context of Ecuador, we delve into
the matrix of overlooked effects when investing in banks and cooperatives, a
vitally important aspect that deserves detailed attention. As mentioned by
Quito et al. (2019), the identification and consideration of these overlooked
effects can have a significant impact on investment decisions and, ultimately,
on the financial results of the institutions. Therefore, The present study has
as its main objective to propose an innovative alternative to analyze and
understand the overlooked effects on investment decisions in the financial
sector. Hypotheses will be formulated that seek to identify underlying
variables and factors not usually considered, with the purpose of improving
strategic decision making and risk management in financial institutions.
The research
is based on data collected from financial institutions in Ecuador, using
financial reports, sector regulations and interviews with experts. The
forgotten effects matrix will be used to analyze the relationship between key
variables in investment, identifying overlooked aspects in the Ecuadorian
financial context. It is expected that the study will contribute to the
identification of relevant variables, improving financial decision making and
risk management. Although the proposed methodology is valuable, possible
limitations in the interpretation of results are recognized due to the
complexity of financial interactions and the limited availability of data. The
literature review will focus on previous research on financial management,
highlighting the importance of addressing neglected effects to situate the
contribution of the study in the academic environment.
The
financial system
The
financial system is the fundamental pillar of a country's economy, since it
allows the population to access various financial services. The system takes
considerable measures to ensure and provide economic resources for the
productive sector, with the objective of achieving stability and growth in
monetary and economic activities. This process enables effective cash
circulation that improves the welfare of a country's financial and monetary
policies (Álvarez et al., 2020; León-Bermeo and Murillo-Párraga, 2021; Zhang et
al., 2022).
According to
Guerrero et al. (2012); and Ergun (2021) investing in strengthening financial
services is considered an important strategy to boost the development of
sectors with minimal income flows, such as rural economies. These investments
invigorate small-scale economies by optimizing available resources, increasing
income generation and minimizing market failures, which significantly
contributes to boosting the local and national economy. However, it is
important to note that Rojas and Avellán (2009) emphasize that deterrents such
as lack of accessible information, together with high transaction costs, tend
to inhibit project financing even when there are no market frictions on the
principles of neoclassical theory.
Financial
education has been internationally recognized as an effective means of
mitigating social exclusion and at the same time strengthening the financial
system, thus contributing profoundly to improving social welfare by
establishing a comprehensive knowledge of financial products and services.
Making informed decisions regarding savings, debt management and investments
could significantly improve the current state of family welfare and, at the
same time, ensure future prosperity, thus avoiding potential obstacles or
detrimental outcomes (Raccanello and Herrera Guzmán, 2014; Ordóñez et al.,
2021b; Roa, 2013).
The
Superintendency of Banks (2021) presents the Unified Chart of Accounts that
illustrates the broad spectrum of financial services provided within the
sector. This includes obligations to the public (Group 21) and demand deposits,
with special attention to sub-account 2103 represented by time deposits, which
is the subject of this research. This subaccount records the entity's
obligations originating from approved methods used to generate income from
public resources (Ordóñez et al., 2021a; COMYF, 2014).
Financial
institutions within this system are largely capitalized by the acquisition of
time deposits by their members and clients (Gutiérrez-Antón et al., 2022;
Ordóñez et al., 2023; Salvador et al., 2023). These deposits imply that clients
assign specific amounts to financial establishments for previously agreed-upon
deposits. Subsequent to these periods they receive their invested capital
together with the interest generated (Muñoz, 2021; El Husseiny, 2023). The
realization of such deposits can only be insisted upon after an interval of
more than thirty days. From a banking institution's point of view, these are
considered future obligations likely to be necessary over medium to long-term
horizons, as they remain immobilized for account holders for this predetermined
duration (Vera, 2021; Botev et al, 2019; Lener, 2022, Roa et al., 2014).
With respect
to fundraising, the Financial and Economic Analysis Unit [UAFE] (2022) together
with the Association of Private Banks of Ecuador [ASOBANCA] (2022), have issued
warnings to both financial institutions and the general public about numerous
predicate crimes. These include fraudulent schemes to raise illegal funds,
illicit economic exploitation, scams and other criminal acts that seriously
damage both the national economic system and the country's global reputation
(UAFE and ASOBANCA, 2022). Money laundering is denoted as the method by which
income obtained through criminal actions is surreptitiously introduced and
integrated within the financial-legal framework. It appears to be legitimate
and disguises illicit activities such as drug trafficking, violent extortion,
illegal trafficking of military weapons, prolifically organized or contracted
assassinations "Sicariato", internationally prohibited illicit
smuggling; as well as criminal trafficking against human beings and other
sinister activities whose profits are directed towards covert negotiations that
directly or indirectly encourage global terrorist actions (UAFE, 2022; De La
Torre, C., and Quiroz, J., 2023).
MATERIALS AND METHODS
The chosen research design is not experimental, but
incorporates longitudinal measurements related to group evolution where
alterations over time are closely examined within specific account groups
(Hernández et al., 2014). This method facilitated the exploration of the
context associated with shifts and changes in collection matters of financial
entities using information obtained from secondary sources found on the
official websites of the Superintendence of Popular and Solidarity Economy, in
addition to those belonging to the Superintendence of Banks by accessing the
respective relevant financial statements for the period between the years 2019
-2021. In the same way, a review of the wide body of knowledge in scientific
production was carried out, with the objective of gathering information framed
in the research.
In the financial context of Ecuador, determining the
optimal investment strategy for various stakeholders is a key objective driving
this research. To achieve this purpose, two different data collection
techniques were employed, followed by a detailed analysis using the time series
model in SPSS statistical software. This approach allowed the calculation of
the correlation coefficient between variables and the estimation of the
ordinary least squares model, thus providing a solid basis for the analysis of
financial data.
In addition, a fuzzy logic experton system approach
was implemented to identify an optimal investment strategy for a financial
institution. The application of fuzzy logic proved crucial in this process, as
it allowed considering relative concepts and varying degrees of membership,
aligning closely with human cognitive processes (Kosko, 1995; Luna et al.,
2018; Quito et al., 2019; Tian & Liu, 2021).
This comprehensive and detailed methodology not only
facilitated the identification of patterns and trends in the financial data,
but also provided accurate recommendations to improve investment decisions and
maximize results for all those involved in the Ecuadorian financial sector.
This rigorous and multidisciplinary methodological
approach not only contributes to a deeper understanding of the neglected
effects of investment decision making, but also lays the groundwork for the
development of more effective financial strategies tailored to the specific
needs of each stakeholder. The combination of statistical techniques and the
application of fuzzy logic in the identification of an optimal investment
strategy represents a significant step towards the continuous improvement of
the financial sector in Ecuador.
RESULTS
For the study, a statistical analysis was first
performed by correlating two variables: years and time deposits. These
variables will be measured at a continuous quantitative level, whose
distribution of the variables is similar to the normal curve.
Table 1. Correlations
between years and term deposits 2019, 2020, 2021 and 2022.
|
|
|
Years |
Time deposits |
|
Pearson correlation |
Years Time deposits |
1.000 0.065 |
0.065 1.000 |
|
Sig. (Unilateral) |
Years Time deposits |
0.159 |
0.159 |
|
N |
Years Time deposits |
237 237 |
237 237 |
Source: Data taken from SIB and SEPS (2019, 2020, 2021
and 2022).
Table 2. Summary
of the model
|
Model |
R |
R square |
Adjusted R-squared |
Standard error of the
estimate |
Durbin-Watson |
|
1 |
0.065a |
0.004 |
0.000 |
1.128 |
2.191 |
Note. a. Predictors: (Constant), Term deposits. b.
Dependent variable: Years. Source: Data taken from SIB and SEPS (2019, 2020,
2021 and 2022).
The results reveal a slightly positive influence
between the years and term deposit data, with a Pearson's influence coefficient
of R = 0.065. However, this relationship is not significant, as evidenced by an
R of 0.004, indicating a very weak relationship between the variables. These
results are attributable to the analysis of the data collected on the uptakes
of financial institutions before, during and after the COVID-19 pandemic. In
addition, the Durbin-Watson result of 2.191 indicates a low linear relationship
and low autocorrelation of the regression terms. This implies that
autocorrelation does not significantly affect the regression terms, indicating
that the model has a good fit to the data.
Table 3. Analysis
of variance
|
ANOVAa |
||||||||||||
|
Model |
Sum of squares |
Gl |
Root mean
square |
F |
Sig. |
|
||||||
|
1 |
Regression Waste Total |
|
1.279 298.823 300.101 |
|
1 235 236 |
|
1.279 1.272 |
|
1.006 |
|
0.317b |
|
Note. a. Dependent variable: Years. b. Predictors:
(Constant), Term deposits. Source: Data
taken from the of SIB and SEPS (2019, 2020, 2021 and 2022).
Complementarily, with the analysis of variances
(ANOVA), the F-test statistic value is 1.006, which indicates that there is no
significant difference between the groups in terms of the variable under study.
The significance test statistic value of 0.317 is greater than the established
significance level, therefore, the null hypothesis cannot be discarded. This
means that there are no significant differences between the variables.
Therefore, it can be deduced that there is a relationship between the years and
terms of the deposits.
Table
4. Coefficients
|
Coefficientsa |
|
||||||||||
|
Model |
Unstandardized coefficients |
Standardized coefficients |
T |
Sig. |
|
||||||
|
B |
Standard error |
Beta |
|
||||||||
|
1 |
(Constant) Time deposit |
|
2020.521 1.114E-11 |
0.088 0.000 |
0.065 |
22942.216 1.003 |
0.000 0.317 |
||||
Note. a.
Dependent variable: Years.
Source: Data
taken from the of SIB and SEPS (2019, 2020, 2021 and 2022).
The Beta coefficient (β) of 0.065 indicates that term deposits are less
volatile than the market, which implies that they are not as subject to
percentage changes in the benchmark index. Table 5 and Figure 1 show the trend
of deposits received in the Ecuadorian financial system during the periods 2019
to 2022. Of the total, 38.80% corresponds to Banking and 61.20% to Savings and
Credit Cooperatives in segment 1.
Table
5. Frequency
table
|
Financial Institution |
|||||
|
|
|
Frequency |
Percentage |
Valid percentage |
Cumulative percentage |
|
Valid |
Banks |
92 |
38.8 |
38.8 |
38.8 |
|
Coop Seg I |
145 |
61.2 |
61.2 |
100.0 |
|
|
Total |
237 |
100.0 |
100.0 |
|
|
Source: Data
taken from the of SIB and SEPS (2019, 2020, 2021 and 2022).
Figure 1. Fundraising
in the Ecuadorian Financial System
61,20% 38,80%
Source: Data taken from the of SIB and SEPS (2019,
2020, 2021 and 2022).
Figure 2. Fundraising
in the Ecuadorian financial system by sector
Source: Data
taken from the of SIB and SEPS (2019, 2020, 2021 and 2022).
According to the SPSS statistical program and its
Figure 2, it can be seen that the trend during the four years in the Ecuadorian
banking sector has been maintained in terms of deposits. However, in the
Savings and Credit Cooperatives, which in the year 2019 have greater
representation than in the Banks, and in the following two periods increased
despite being in a situation of crisis worldwide. Finally, in 2021 the trend
continues to grow. Therefore, the public's preference to leave their
investments in the credit union sector is evident. For this reason, the next
step was to interview 6 experts in the financial system who work specifically
in the area of fundraising in order to establish the best strategy at the time
of making the decision to invest in a financial institution.
The following clarifies the process of structuring
square matrices to determine the "forgotten effect" that contributes
to the proposed research topic. The initial course in utilizing this tool was
to delineate actions and effects with the objective of discerning optimal
strategies, facilitating informed decisions by stakeholders when investing
their surplus funds in time deposits in either Segment I Banks or Credit Unions
in Ecuador. This was achieved thanks to the knowledge of six experts in
financial systems, who undoubtedly used their experience to contribute with
precise improvement strategies.
Table 6 outlines a matrix showing actions and effects
structured as a square: covering an equal number of variables. Both the actions
and effects described adhere to norms established by regulators based on Basel
III standards. After that, the application of this fuzzy logic tool that
incorporates experience and theories related to "forgotten effects"
began. By taking advantage of this tool, any potential forgotten or overlooked
effects can be identified, thus mitigating risks related to fraud or scams when
making investments.
Table 6. Matrix of
actions and effects
|
ACTIONS |
EFFECTS |
|
Demonstrate security and
stability of the financial institution. |
Maintain
stakeholder loyalty. |
|
Offer a competitive investment rate. |
Attract new
customers, partners with new investment proposals. |
|
Increased profit through
time deposits. |
Ease of contact and
efficient process time savings. |
|
Provide personalized service between
advisor and user in time deposits. |
Avoid the
risk of forced liquidations. |
|
Customized investments
according to term and amount. |
Prevent money laundering
and financing of crimes. |
|
Verify the stability of the stakeholder group. |
Improved
quality, consistency and transparency. |
|
Offer pre-cancellation
plan before signing investment document. |
Disclosure of information
after review by control agencies. |
|
Validation of where the funds to be invested come
from. |
Comply with
minimum capital conservation standards for IFIs. |
|
Training and updating of
IFI officials on the standards. |
Introduce additional
safeguards against model risk and financial and real economy measurement
errors. |
|
To be in accordance with the regularizations of
the Control Organisms (COMYF; SIB; SEPS; UAFE). |
To have tools
that contribute to the objectives of the recruitment area. |
Source: Matrix according to Basel III and regulations
of control agencies (COMYF; SIB; SEPS; UAFE).
With the acquired data, we proceed to construct the
frequency and determine the repetitions of the degrees of presumption in
relation to the number of experts consulted. Subsequently, we normalize this
frequency, which represents a distribution between the data points obtained
within this frequency and the total number of expert consultations. After this
step, cumulative frequencies are established starting from the last value in
ascending order until reaching unity. From that stage on, all results have the
same importance as a unit. The consequent accumulation of these processes
starts precisely from 0.1 points until reaching 1, in which the answers that
were provided by each of the experts are placed, as shown in Table 7.
Table 7. Normalization
and accumulation of frequencies
Source: Data calculated based on responses from the 6
experts in the Base Matrix.
In banking and credit unions, the relationship between
actions and effects is crucial to financial stability. Decisions in response to
regulations, such as Basel III, impact the economy and users. Basel III
strengthens financial resilience with tighter capital requirements and sound
risk management. Its implementation prevents crises, improves transparency and
protects depositors. These regulations influence the financial, operational and
risk strategies of institutions, directly impacting their functioning and
credit policies (Bank for International Settlements Basel III, 2019).
After an exhaustive consultation with six experts in
Banking and Credit Unions, valuable insights were gathered on the relationship
between actions and effects linked to the regulations established by the
supervisory bodies, together with Basel III recommendations.
For the study, we created a square matrix in which the
number of rows represents actions and the column represents their implications,
We used the Max-Min convolution process to analyze this matrix. The method used
to discern the highest value from a series of smaller numbers by comparing
between row and column values within our base incidence matrix. To accomplish
this, we implemented autoconvolution on the base matrix, which subsequently
resulted in what is defined as a "transposed" matrix. These are detailed
in Table 8, where expert input is applied to form a square matrix. The complete
data or matrix I will then be transferred for further analysis.
Table
8. Base Matrix
Source: Data
obtained from the responses of the 6 experts surveyed.
Prepared by:
The authors
From now on, we provide an explanation of how the
convolution between Row 1 and Column A was performed:
For 1-A:
(K7٨K7)٧(K8٨L8)٧(K9٨M8)٧(K10٨N8)٧(K11٨O8)٧(K12٨P8)٧(K13٨Q8)٧(K14 ٨R8)٧(K15٨S8)٧(K16٨T8)
(0,767 ٨ 0,767)
٧ (0,733 ٨ 0,667(٧)
0,717٨
0,767(٧ (0,833 ٨ 0,667(٧ (0,767 ٨ 0,733(٧ (0,717 ٨ 0,717(٧ (0,600 ٨ 0,600(٧ (0,867 ٨ 0,750(٧ (0,917 ٨ 0,717(٧ (0,867 ٨ 0,767)
From each interval, the smaller value is chosen: 0.767 ٧ 0.667 ٧ 0.717 ٧ 0.667 ٧ 0.767 ٧ 0.717 ٧ 0.600 ٧ 0.750 ٧ 0.717
٧
0.767 ٧ 0.767
٧
0.767
Among all the selected smaller values, the largest
value is chosen, which in this case is 0.767. This value is placed at the
intersection of row 1 with column A in matrix "I", as shown in Table
9. This procedure is repeated for the rest of the coordinates. The following
table summarizes the results obtained from this continuous process.
Table 9
Table 9. Matrix I
Source:
Calculations obtained according to the responses of the 6 experts surveyed.
Table 10
Table 11. Base Matrix - Matrix I
Source:
Calculations obtained according to the responses of the 6 experts surveyed.
In this research, the neglected effects of the first
generation were tested using the "I" matrix as a fundamental tool.
The analysis included subtraction between BASE and the "I" matrix,
visualized in Table 10, where all quadrants remained intact to ensure
consistency and accuracy. The data resulting from this analytical operation
were presented in terms of absolute value for ease of understanding.
To illustrate further, Base (7K) - I (23K), Base (7L)
- I (23L) and Base (7M) - I (23M). A similar process was followed until we
successfully obtained a dynamic matrix that housed effectively these overlooked
consequences. Significantly hidden variables or elusive effects were identified
by taking into account the values closest to unity in the respective grid in
Table 10. An important aspect that deserves discussion is our focus on the
factor "α",
valued at 0.300 located precisely in the pair of coordinates (7, J).
In an in-depth analysis of how
the action directly influences the effect, thus revealing associations that
provide information on previously overlooked causal factors
arising from the interaction between these relevant variables. As part of the
findings of the current study, the factor "α" was found to be equal to 0.300 within the
cross-sectional grid point "MI - M. BASE" at coordinate pair (7, J).
Careful examination was continued with the objective of discovering obscure
impacts. To facilitate this effort, the maximum-minimum convolution method was
again employed by comparing the intersection points of rows and columns located
in the (7, J) coordinate pair.
Para 7, J:
(K61٨T55)٧(L61٨T56)٧(M61٨T57)٧(N61٨T58)٧(O61٨T59)٧(P61٨T60)٧(Q61٨T61)٧(R61 ٨T62) ٧(S61٨T63) ٧(T61٨T64)
0,000 ٨ 0,100(٧) 0,033 ٨ 0,150 (٧)
0,283٨ 0,017(٧)0,250 ٨ 0,150(٧)0,117 ٨ 0,083(٧)0,017 ٨ 0,067(٧)0,000 ٨ 0,300(٧)0,033 ٨ 0,017(٧)0,233 ٨ 0,050(٧)0,300 ٨ 0,000)
From each interval, the smaller value is chosen: 0.000 ٧ 0.033 ٧ 0.017 ٧ 0.150 ٧ 0.083 ٧ 0.017 ٧ 0.000 ٧ 0.017 ٧ 0.050 ٧ 0.000 ٧
0.000
At the end of each interval, the highest value is
chosen: in this case, it is 0.150
At the end of the process, it was concluded that
Action No. 7 has an impact on the effect specified in Clause J through its
hidden variable C. This effect is illustrated more clearly in Figure 3, where
the variables are highlighted with their respective scenarios, which become key
improvement strategies to be implemented by the sector under study:
Figure
3. Incidence of
causality 7 - J
Source: Data taken from the results in Table 11.
CONCLUSIONS
To conclude,
in the proposed scenario, it has been determined that the implementation of a
pre-cancellation plan at the 7-J coordinates prior to the signing of financial
documents is essential to have useful tools that favor the objectives of the
customer acquisition department. This strategy is mainly based on a hidden
variable, focused particularly on two central aspects:
simplifying the contact channels and efficiently optimizing the time invested
in the processes.
The
"Forgotten Effects" highlights the positive relationship between
annual installments and deposits in banks and cooperatives in Ecuador,
supported by a Pearson correlation coefficient of 0.065. The implementation of
a pre-cancellation plan is mentioned as key to achieving objectives in the
procurement department, improving operational efficiency. These data underline
the importance of properly managing terms and deposits in financial
institutions, influencing liquidity, fund raising, risk management and operational
efficiency. The relevance of this relationship is evident in the optimization
of processes and the achievement of financial goals, highlighting the need for
effective strategies to ensure success in Ecuador's financial context.
The detailed
investigation of the neglected effects in the "I" matrix revealed the
importance of identifying hidden variables or overlooked effects in the
financial context of banks and cooperatives in Ecuador when investing. The
focus on the "α" factor with a value of 0.300 in the (7, J)
coordinate pair highlights the relevance of this analysis to uncover obscure
impacts and previously neglected causal factors.
The
implementation of a pre-cancellation plan at the 7-J coordinates, as suggested
in the study, is presented as a fundamental strategy to favor the objectives of
the customer acquisition department in financial institutions. This strategy is
based on simplifying the contact routes and optimizing the time invested in the
processes, which can improve operational efficiency and internal communication
in the department.
The results
obtained from the neglected effects matrix underline the importance of using
analytical tools such as the "I" matrix to identify and address
overlooked effects in the financial context. The implementation of strategies
such as the pre-cancellation plan can be crucial to improve efficiency and
optimize processes in financial institutions, thus contributing to the
achievement of specific objectives in the collections department.
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[*] D. in Accounting, Professor
- Universidad Católica De Cuenca
jordonezp@ucacue.edu.ec, Http://Orcid.Org/0000-0002-5002-2203
* Bachelor's Degree in Accounting and Auditing, Teacher - Universidad
Católica De Cuenca,
stella.lucin@est.ucacue.edu.ec, http://orcid.org/0009-0008-5467-3784
* Master's degree in business administration with a major in human
resources and marketing Teacher - Universidad Católica De Cuenca, ezamoraz@ucacue.edu.ec http://orcid.org
0000-0003-3265-8846
* Teacher - Universidad Autónoma De Nuevo
León
paula.villalpandocd@uanl.edu.mx, http://orcid.org/0000-0001-9177-4607