![](data:image/png;base64,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)
79
Yulök Revista de Innovación Académica, ISSN 2215-5147, Vol. 6, N.º 2
Junio-Diciembre 2022, pp. 74-90
Sosa, E. Propuesta Metodológica para el Diseño de Procedimientos Analíticos Sustantivos en
Auditoría de Estados Financieros
Idoneidad de los procedimientos analíticos
sustantivos
Coincidentemente con la NIA 520 (IFAC, 2018), Appel-
baum et al (2018) consideran que la aplicación de pro-
cedimientos analíticos sustantivos es más apropiada en
las partidas caracterizadas por grandes volúmenes tran-
saccionales que tienden a ser previsibles a lo largo del
tiempo. A manera de ejemplo, se pueden mencionar los
ingresos por habitaciones en un hotel, los ingresos y gas-
tos por intereses en una entidad financiera; los ingresos
por matrícula y colegiatura en instituciones de enseñanza
y los ingresos por alquileres en compañías dedicadas al
arrendamiento de oficinas o locales comerciales.
Un elemento determinante de la idoneidad de la aplica-
ción de los procedimientos analíticos es la naturaleza de
la cuenta (Instituto de Censores Jurados de Cuentas de
España, 2016). Entre más predecibles sean las relacio-
nes, más precisa es la expectativa (Mc Daniel y Simmons,
2007), por eso, ciertas partidas son más adecuadas para
obtener evidencia mediante procedimientos analíticos que
otras, normalmente, las expectativas desarrolladas sobre
cuentas del estado de resultados son más predecibles y
precisas que las del estado de situación financiera (Scott y
Wallace, 1994; Levy, 2019; Mc Daniel y Simmons, 2007
y Public Company Accounting Oversight Board, 2019).
Las relaciones entre cuentas del estado de resultados sue-
len ser más predecibles que las que relaciones que inclu-
yen únicamente rubros del estado de situación financiera,
por cuanto representan transacciones realizadas a lo largo
de un período de tiempo, mientras que las de este último
representan montos en una fecha determinada (Public
Company Accounting Oversight Board, 2019).
La confianza del auditor para alcanzar un objetivo de
auditoría relacionado con una partida en particular se
puede derivar de pruebas de detalle, de procedimientos
analíticos, o una combinación de los ambos (Cristescu y
Stancu, 2019). La decisión acerca de cuál procedimiento
utilizar para tal efecto depende del juicio del auditor so-
bre la efectividad esperada y la eficiencia de los posibles
procedimientos. Para las partidas que presentan riesgos
significativos de incorrecciones materiales es improbable
que la evidencia obtenida únicamente empleando proce-
dimientos analíticos sustantivos sea suficiente, así, para
algunas declaraciones de los estados financieros, los pro-
cedimientos analíticos sustantivos son apropiados para
proporcionar al auditor el nivel de seguridad requerido,
sin embargo, para otras declaraciones, estos procedimien-
tos pueden no ser tan efectivos como las pruebas de deta-
lle (Public Company Accounting Oversight Board, 2019).
La adecuación de determinado procedimiento analítico
depende de la valoración que efectúe el auditor sobre su
efectividad para detectar incorrecciones significativas
en el contexto de la auditoría, individualmente o de for-
ma agregada con otras incorrecciones (NIA 520, IASB,
2018). La selección de los procedimientos analíticos
sustantivos por aplicar es asunto de criterio profesional
(Rico, 2002; León, 2012; Ramírez, 2013; Moolman,
2017; Appelbaum et al, 2018; Levy, 2019 y Public Com-
pany Accounting Oversight Board, 2019).
El auditor debe determinar la idoneidad de procedimien-
tos analíticos sustantivos para ciertas partidas y declara-
ciones de los estados financieros, considerando los nive-
les de riesgo de errores significativos en dichos estados
(Moolman, 2017). Además, debe evaluar la confiabilidad
de los datos con base en los cuales define su expectativa
sobre los montos contabilizados, teniendo en cuenta la
fuente, la comparabilidad, la naturaleza y la relevancia
de la información disponible, así como los controles re-
lativos a su preparación (NIA 520, IFAC, 2018 y Li et al,
2020).
La NIA 520 (2018) señala que, si los controles para la
preparación de esa información son efectivos, mayor es la
confianza que el auditor puede depositar en los resultados
de la aplicación de procedimientos analíticos. Por esto
mismo, al diseñar procedimientos analíticos sustantivos,
el auditor debe evaluar el riesgo de que la dirección no
cumpla con los controles establecidos (Public Company
Accounting Oversight Board, 2019).
Confiabilidad de los datos
La efectividad de los procedimientos analíticos sustan-
tivos está en función, entre otros aspectos, del grado de
confiabilidad de los datos con base en los cuales estos se
formulan (Public Company Accounting Oversight Board,
2019).
El primer paso para la ejecución de procedimientos ana-
líticos sustantivos consiste en evaluar la corrección de
los datos con referencia a los cuales el auditor establece
la expectativa sobre los montos contabilizados (Instituto
de Censores Jurados de Cuentas de España, 2016). Para
esto, es preciso evaluar si se trata de datos financieros y/o
no financieros, si estos tienen relación con las cuentas e
importes objeto de auditoría, si la fuente de información
es externa o interna (Scott y Wallace, 1994), así como su
experiencia sobre la confiabilidad de los datos obtenida
en la ejecución de auditorías previas.
La NIA 520 (IFAC, 2018) menciona los siguientes facto-
res determinantes de la confiabilidad de los datos: