151

Finance, Accounting and Business Analysis

Volume 8 Issue 1, 2026

http://faba.bg/

ISSN 2603-5324

DOI:

https://doi.org/10.37075/FABA.2026.1.12

Modernizing Solvency Regulation in Algeria: A Comparative Study

of Static and Stochastic Approaches

Toufik Ait Ouali

, Djamila Mendil

Higher School of Computer Science and Digital Technologies (ESTIN), Bejaia, Algeria

Department of Economic Sciences, Abderrahmane Mira University, Bejaia, Algeria

Info Articles

Abstract

History Article:

Submitted 11 August 2025

Revised 9 April 2026

Accepted 11 May 2026

Purpose: This study examines whether Algeria could transition from

its current prudential solvency framework, largely based on the

outdated Solvency I directive, to a more dynamic solvency assessment

approach grounded in stochastic differential equations (SDEs).

Methodology: Using an analytical and comparative methodology, the

paper contrasts the Algerian Solvency I–based framework with a

stochastic solvency model proposed by Wang and Zhu (2021),

highlighting their conceptual foundations, regulatory implications, and

risk management capabilities.

Findings: Solvency I framework relies on static capital requirements

that insufficiently capture market volatility, evolving insurance risks,

and extreme events. In contrast, the stochastic model incorporates

randomness, dynamically manages capital flows between different

financial states, and adjusts solvency levels in real time in response to

market and claims fluctuations. This results in a more accurate and

forward-looking assessment of insurers’ financial resilience.

Practical Implications: Adopting a stochastic solvency framework

could enhance the stability and risk management capacity of Algerian

insurance companies. However, such a transition would require

gradual regulatory reforms, institutional capacity building, and close

coordination between insurers and supervisory authorities.

Originality/Value: This paper contributes to the literature by

providing the first structured comparison, in the Algerian context,

between the Solvency I framework and a stochastic differential

equation–based solvency model, thereby enriching the ongoing debate

on the modernization of insurance prudential regulation in emerging

markets.

Paper Type: Research Paper.

Keywords:

Solvency Standards;

Insurance; Solvency I;

Stochastic Differential

Equations; Algeria.

JEL: G22 ; G28 ; C52

Address Correspondence:

E-mail:

aitouali@estin.dz

djamila.mendil@univ-bejaia.dz

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INTRODUCTION

Prudential regulation in the insurance sector plays a central role in maintaining the financial

soundness of insurance companies, protecting policyholders, and preserving overall economic stability. By

requiring insurers to hold sufficient capital relative to the risks they underwrite, prudential frameworks aim

to ensure that claims obligations can be met even under adverse economic and financial conditions.

Traditionally, insurance companies are required to maintain a minimum level of own funds,

commonly referred to as the solvency margin. This margin serves as a financial buffer designed to absorb

unexpected losses arising from underwriting risk, market fluctuations, and operational uncertainties inherent

to insurance activity.

In Algeria, the current prudential regulatory framework governing insurance companies is largely

based on the former European Solvency I directive. While this framework represented an important step

toward standardizing solvency requirements, it is increasingly considered inadequate in light of the growing

complexity of insurance risks, financial market volatility, and the emergence of new risk sources. Solvency I

relies primarily on static and quantitative indicators, offering a limited capacity to reflect dynamic

interactions between assets, liabilities, and external shocks.

In contrast, recent advances in actuarial science and financial modelling have led to the development

of dynamic solvency assessment approaches based on stochastic differential equations. These models allow

for a continuous and probabilistic representation of insurers’ financial positions by explicitly incorporating

randomness, market volatility, and the evolution of claims and investment returns over time. As a result,

stochastic models provide a more realistic and forward-looking assessment of solvency compared to

traditional static frameworks.

Several international studies have demonstrated that stochastic solvency models improve insurers’

ability to anticipate extreme events, optimize capital allocation, and strengthen enterprise risk management

practices. However, despite their growing adoption in advanced regulatory environments, such approaches

remain largely unexplored in emerging insurance markets, particularly in the Algerian context.

This gap is especially relevant given the structural characteristics of the Algerian insurance sector,

which remains dominated by traditional products and a regulatory framework that has not fully integrated

modern risk-based solvency principles. To date, there is limited academic work that systematically evaluates

the feasibility and potential benefits of transitioning from the Solvency I framework to a dynamic stochastic

solvency model in Algeria.

Against this backdrop, the present study seeks to address the following research question:

Is it feasible for Algeria to adopt a dynamic solvency framework for insurance companies based

on stochastic differential equations, and what advantages would such a transition offer compared to the

current Solvency I–based system?

To answer this question, the paper adopts an analytical and comparative approach. It first presents

the existing prudential standards governing insurance solvency in Algeria. It then reviews relevant literature

on insurance solvency and stochastic modelling. Subsequently, it introduces a stochastic solvency model

based on stochastic differential equations proposed by Wang and Zhu (2021). Finally, a comparative

discussion highlights the limitations of the Solvency I framework and the potential benefits of adopting a

dynamic stochastic approach within the Algerian regulatory environment.

PRESENTATION OF THE CURRENT PRUDENTIAL STANDARDS IN ALGERIA

In Algeria, the regulatory oversight system for insurance companies is founded on the 'Solvency I'

guideline. This regulation is now outdated, necessitating modifications to align with current and forthcoming

solvency criteria. This paper outlines the prudential criteria for regulatory oversight in Algeria's insurance

industry.

The required minimum share capital

The share capital of a company is the fixed sum provided by shareholders or partners through

monetary or non-monetary contributions. It may increase via the inclusion of reserves or earnings and

diminish through the reimbursement of contributions or as a result of losses. As per the Commercial Law,

the capital of joint-stock companies must be entirely subscribed, with all contributions in kind fully released

upon issuance and at least one-fourth of the nominal value released upon subscription for cash contributions.

Law no. 06-04 mandates the complete cash payment of the share capital of insurance companies upon

subscription.

The establishment of an insurance company necessitates a minimum capital, which is contingent upon

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the specific sorts of insurance activities pursued. The minimum share capital requirements were originally

established by the Executive Decree No. 95-344 and subsequently amended by the Executive Decree No. 09-

375. The latter increased the funds to improve the financial soundness of insurance companies from their

establishment.

The revised standards differ based on insurance and reinsurance activities, and noncompliance may

lead to penalties.

Regulatory framework governing commitments

Regulatory and technical provisions related to an insurance company's operations constitute regulated

commitments, evaluated and documented on the liabilities side of the balance sheet, in accordance with the

double-entry accounting principle. The assets designated to represent these obligations are explicitly

regulated to safeguard the interests of policyholders.

The insurer, aiming to optimize revenues via profitable investments, must adhere to investment

mandates that guarantee the security, return, liquidity, and alignment of its assets. These mandates establish

regulations for the allocation, distribution, and placement of investments. Government securities must

comprise a minimum of 50% of regulated commitments, with defined limits for securities, real estate assets,

and other investments.

The regulator intervenes by enforcing stringent regulations to guarantee that investments adhere to

these mandates, encompassing allocation guidelines among asset classes, diversification to mitigate

concentration risks, and geographic distribution. Eligible assets denoting controlled obligations comprise

government securities, additional securities issued by solvent corporations, real estate assets, and diverse

other investments adhering to prevailing legislation. In compliance with these regulations, companies may

depict technical provisions by diminishing their amount by 60%, contingent upon this decrease not

surpassing 15% of the company's total regulated commitments.

Pursuant to the Decree of March 31, 2013, insurance and reinsurance companies are required to cover

their regulated commitments, mainly technical provisions, by recognizing representative assets on the

balance sheet in order to ensure their solvency. In this framework, at least 50% of regulated commitments

must be covered by government securities, half of which must be in the form of medium- and long-term

instruments. The remaining portion is allocated among other eligible assets in accordance with the regulatory

provisions in force.

Time deposits with the same financial institution must not surpass 25% of the total regulated

obligations. Investments in securities issued by unlisted Algerian companies are restricted to 25% of the total

regulated commitments. Investment in real estate in Algeria is limited to 10% of the regulated commitments,

and the aggregate real estate assets must not surpass 40%.

Investment in securities issued by the same issuer, excluding those issued or guaranteed by the State,

is restricted to 5% of the total value of regulated commitments. The involvement of an insurance or

reinsurance company in the share capital of another entity must not surpass 50% of the share capital and 5%

of the regulated obligations of the insurance or reinsurance company.

Representation of regulated commitments

The insurance company assumes obligations to policyholders to indemnify for losses and develops

reasonable reserves to address these responsibilities. Nevertheless, even when implemented judiciously, these

provisions may occasionally be inadequate. The insurance company must maintain a solvency margin,

which serves as an additional buffer to technical provisions, to protect against unanticipated events and

safeguard the interests of policyholders.

The solvency margin is defined as the collection of resources, including share capital and reserves that

offer supplementary protection to the assets held against technical provisions.

The calculation of the solvency margin encompasses share capital or establishment fund, regulated or

unregulated reserves, regulated provisions, and carryovers, whether debtor or creditor. The solvency buffer

for property insurance must be a minimum of 15% of technical provisions and, at all times during the year,

must not fall below 20% of premiums issued and/or accepted, net of taxes and cancellations. The parameters

for life insurance differ by category, encompassing life-death, marriage-birth, and capitalization insurance.

If the solvency margin falls below the mandated minimum, the insurance company must rectify the

situation within six months by either augmenting its share capital or establishment fund, or by providing a

guarantee to the Treasury. The Insurance Supervision Commission determines the release of this guarantee

once the situation has been rectified.

The stringent regulation of insurance companies is a significant concern for authorities globally. The

main goal is to guarantee that these companies reliably meet their obligations to policyholders. Prudential

regulation, centred on solvency, includes the precise evaluation of obligations, oversight of investments, and

the stipulation of a solvency margin.

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The Insurance Supervision Commission (CSA), created by the Ordinance No. 95-07, is essential for

maintaining governmental monitoring of insurance and reinsurance operations. The CSA's objectives

encompass overseeing insurance companies' adherence to legislative regulations, assessing their capacity to

fulfil financial obligations, and doing comprehensive evaluations of funding sources. By executing these

duties, the CSA significantly enhances integrity, stability, and legality within the insurance sector, hence

bolstering public confidence in the insurance system.

Supervisory measures include off-site control, which involves analysing documents provided to the

administration, and on-site control, a method focused on checking the consistency between reported

information and the actual state of the company. Off-site control focuses on the meticulous analysis of

administrative records, but on-site control entails direct inspection to verify the real conformity of the

information supplied by the organization. Both methodologies are critical instruments to ensure

transparency, legitimacy, and adherence of economic activity to specified criteria.

The Ministry of Finance is integral to the approval process for insurance companies, necessitating

prior consent from the Minister to ascertain permissible activities. This duty entails formulating stringent

standards for the professional credentials of insurance company administrators and executives.

Consequently, the Ministry serves as a crucial regulatory function in assuring that insurance companies

adhere to elevated standards of competence and integrity, so bolstering the robustness and dependability of

the financial system.

Numerous alternative ways of regulation are vital in the insurance sector. The Auditor plays a vital

function in validating account compliance and guaranteeing financial transparency. Actuaries, experts in

statistical analysis, are essential for the accurate pricing of insurance products and the management of

reserves. The Audit Committee concentrates on evaluating the veracity of accounting information and

providing assessments of internal control, whereas the Risk Committee is tasked with formulating and

revising the company's risk map. These control systems hold significant importance in the insurance

company due to the inverse production cycle, wherein premiums are received well in advance of claims

payments. This continuous oversight by authorities seeks to safeguard policyholders against uncertainties

associated with insurance.

BRIEF LITERATURE REVIEW

This literature review examines research on the solvency of insurance in Algeria. Recent studies on

the insurance industry in Algeria underscore several vital elements of its operation. In the context of Algeria's

economic changes, risk management is of utmost significance, as indicated by Rezazi and Temam (2003),

who advocate for international strategies to enhance risk management, particularly in light of the various

challenges associated with risk diversity, which is essential for enterprises and national economies, especially

during times of economic transformation. The necessity of risk management is apparent through proposed

international strategies designed to enhance this management in response to the various issues associated

with risk diversity. This emphasis notably underlines the significance of prudential oversight of insurance

companies' solvency, underlining the requirement of such supervision to ensure the sector's proper operation

and safeguard policyholders' interests (Abboura 2011).

Maintaining adequate reserves to meet obligations to policyholders is also crucial (Mohsen and Hani,

2017). The ramifications of regulatory reforms are examined, as demonstrated by Sadek and Boulenouar

(2018) in their examination of the 2006 prudential regulation reform's impact on the insurance sector in

Algeria, emphasizing repercussions on public and private companies. The government's readiness to

implement a new prudential framework aligned with international norms emphasizes the necessity of

insurers' participation in this process to accurately represent the country's economic reality (Alouache et al.

2021).

Establishing a supervisory structure for insurance activities is essential, as highlighted by Riad et al.

(2020), emphasizing the critical significance of solvency, particularly within the context of the 'Solvency II'

regulation. They assert that substantial alterations in liability evaluation are consistently exposed to

provisioning risk when determining solvency capital. The legal ramifications of the shift from Solvency I to

Solvency II are examined by Lalaoui and Haffar (2022), who delineate implementation issues, including

organizational transformation and the costs involved with adopting Solvency II. Bouabdallah and Oubelaid

(2022) evaluate the implications of implementing the Solvency II standard formula on the capital requisites

of an Algerian insurance company, highlighting the novel quantitative mandates established by Solvency II,

such as the Solvency Capital Requirement (SCR) and the Minimum Capital Requirement (MCR).

Metchat and Boudaoud (2023) have conducted recent research that analyses emerging patterns in

Algeria's insurance sector, underscoring the impact of constantly evolving prudential legislation. There is a

critical necessity to keep sufficient solvency in response to increasing hazards. The analysis by Boucherak

(2023) determines that the insurance company possesses sufficient equity to meet the necessary solvency

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capital, highlighting the significant influence of risks associated with premiums and reserves, particularly in

the automotive sector. The report recommends modernizing Algeria's solvency system to conform with

Solvency II, thereby ensuring insurers' financial stability.

Our examination of research into the existing prudential rules for monitoring the solvency of insurance

companies in Algeria clearly indicates a consensus on the need to transition to the Solvency II directive.

Nonetheless, literature analysing critiques of Solvency II demonstrates a variety of perspectives among expert

scholars. Gunther and Richter (2015) identify a deficiency in the existing standard formula, asserting that it

inadequately represents the liquidity-related catastrophic risk. This critique highlights the necessity for the

regulatory framework's suppleness to accommodate market advances.

Rae et al. (2018) assert that Solvency II has not fulfilled its anticipated goals, indicating the necessity

for modifications to rectify procyclicality and market inconsistencies. This analysis underscores the intricacy

of the legislation and stresses the necessity for a more comprehensive approach. The research by Santomil et

al. (2019) indicates that the Solvency II minimum capital requirement is inferior to that determined by the

standard model. This observation underscores possible discrepancies in risk evaluation across various

techniques.

The findings of Cooke et al. (2019) substantiate apprehensions by demonstrating that Solvency II

attenuates the significance of the risk margin, thus diminishing the technical reserves of insurance companies.

This observation prompts inquiries regarding the system's capacity to sustain sufficient coverage against

related risks, a notion corroborated by Drenovak et al. (2020), who assert that the Solvency II regulatory

framework results in diminished diversification within the bond portfolio, consequently heightening the

credit risk faced by insurance companies. This comment underscores a vital element of risk management

within the regulatory framework.

Pelkiewicz et al. (2020) contend that Solvency II overlooks the risk margin, demonstrating

disproportionate sensitivity to fluctuations in interest rates, particularly concerning annuities. This

assessment indicates that the regulatory framework may need modifications to more effectively address the

intricacies of insurance operations. Scherer and Stahl (2020) adopt a nuanced stance, recognizing that the

Solvency II standard formula exhibits greater sensitivity to risk than its predecessor, despite the stochastic

model still encompassing significant uncertainty. This viewpoint emphasizes the necessity of achieving

equilibrium between risk sensitivity and model stability.

The examination of these diverse criticisms uncovers several fundamental issues pertaining to

Solvency II, encompassing portfolio management and the handling of risks. These observations indicate the

necessity for continuous assessment of the regulatory framework to guarantee its efficacy and pertinence in

a constantly changing financial landscape.

An analysis of the Solvency I and II directives reveals that both frameworks exhibit a degree of inertia.

Consequently, it is clear that investigating a more dynamic model is essential, and the literature proposes

alternative models grounded in mathematical and stochastic methodologies.

The investigation of stochastic differential equations within the insurance sector is still somewhat

constrained. Paul (2007) employed an alternative viewpoint by treating the necessary solvency capital as a

constraint, utilizing deterministic control theory to establish the optimal premium approach. Similarly,

Delong and Gerrard (2007) utilized a stochastic differential equation grounded in Brownian motion to

represent the fluctuations in claims intensity. Their methodology incorporated stochastic control theory to

determine the optimal strategy, particularly when the insurance company's wealth diverges from the

established profit solvency target.

Shi et al. (2008) employed an integrative strategy that amalgamated risk tolerance and utility attitude

with decision-making objectives, utilizing Backward Stochastic Differential Equations (BSDE) to formulate

a model and ascertain the precise pricing formula for unit-linked life insurance products.

Xiong (2011) enhanced the research by investigating the diffusion model and its relevance to risk and

insurance theory. The anticipated discounted penalty function is a substantial enhancement of the chance of

ruin, fulfilling an elliptic partial differential equation under specific starting boundary conditions. Delong's

(2012) comprehensive analysis explored multiple dimensions, encompassing financial risk, systematic and

non-systematic insurance loss (including longevity risk), along with potential interdependencies among these

elements.

Finally, it should be noted that the work of Floryszczak et al. 2018 although not included in the

provided text, could be incorporated into this presentation depending on its context or its relationship with

the works mentioned previously.

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SOLVENCY ASSESSMENT MODEL FOR INSURANCE COMPANIES BASED ON

STOCHASTIC DIFFERENTIAL EQUATIONS

Upon examining the attributes and nuances of the prevailing solvency standard for insurance

companies in Algeria and evaluating research on their advantages and disadvantages relative to the "Solvency

II" directive, the primary conclusion is that neither of these directives employs a dynamic methodology in

the computation of solvency ratios. This observation pertains to all insurance companies assessing their

solvency threshold.

In our research on the solvency evaluation of Algerian insurance companies, we focused on the model

of stochastic differential equations, influenced by the work of Wang and Zhu (2021). The researchers

conducted a thorough review of the solvency framework of insurance companies in China. Their

methodology employs a model utilizing stochastic differential equations to ascertain the critical conditions

for sustaining the dynamic solvency of an insurance company. They analysed and modelled these conditions

while suggesting solutions to maintain solvency amid anticipated external disruptions.

This model utilizes capital flow analysis to evaluate the solvency of insurance companies. This

approach considers financial dynamics across several stages, encompassing financial health, risk, and

reserves, rather than simply delineating capital standards. The model defines an insurance company as a

system driven by capital, wherein insurance premiums supply essential resources on one side, while claims

expenditures safeguard policyholders on the other. The corporation concurrently employs its capital to yield

profits via investments.

To better understand this dynamic, a compartmental model subdivides the company's funds into three

distinct states: the health fund, the risk fund, and the reserve fund. Fund transfers between these states

symbolize capital flows, as depicted in the figure below:

Figure 1. Organization of an insurance company

The SDE-based model conceptualizes an insurance company's capital flow as a dynamic system

across three interconnected states: health state (premiums and underwriting), risk state (investments),

and reserve state (claims provisioning). Solvency is assessed through the system's stability over time.

Model Specification and Dynamics

Health State (S(t)): This state reflects capital from collected premiums. Its growth is constrained by

market capacity, and it is subject to stochastic fluctuations in premium income. Capital outflows include

operating expenses, transfers to the risk state for investment, and allocations to the reserve state.

Risk State (I(t)): This state manages capital allocated for investments. Returns are subject to random

market fluctuations. Outflows cover investment costs and further contributions to the reserve state.

Reserve State (R(t)): This state holds funds earmarked for future claim payments (compensations to

policyholders). Inflows come from the health and risk states. Outflows are claim payments, which occur

at stochastic intervals.

The dynamics are formally described by the following system of stochastic differential equations,

where randomness is introduced via independent standard Brownian motions B

(t), B

(t):

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157

󰇛󰇜    󰇟󰇛󰇜   󰇛󰇜󰇛  󰇛󰇜󰇜  󰇛󰇜  󰇛󰇜   󰇛󰇜󰇠  󰇛󰇜󰇛󰇜

(1)

󰇛󰇜    󰇟󰇛󰇜 󰇛󰇜   󰇛󰇜   󰇛󰇜󰇠  󰇛󰇜󰇛󰇜

(2)



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󰇜

 

󰇟

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󰇛

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

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



󰇛

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



󰇛



󰇜

(3)

where:

S(t), I(t), R(t) — Capital levels in the health, risk, and reserve states at time t.

λ — Premium growth rate.

K — Carrying capacity (maximum attainable premium volume).

β, ω, μ — Transfer rates from health to risk state, health to reserve state, and risk to reserve state, respectively.

, d

— Expense rate in the health state, cost rate in the risk state, and claims payment rate in the reserve

state, respectively.

r — Expected rate of investment return.

, σ

— Volatilities (standard deviations) of the capital flow fluctuations in each state.

Solvency Condition Derived from Stability Analysis

Following the stability analysis of the stochastic system by Wang and Zhu (2021), a sufficient

condition for the long-term solvency of the insurance company — interpreted as the existence of a stable

positive equilibrium — can be summarized by three constraints on the model parameters:

    

󰇛

   







󰇜

 

(4)

󰇛



󰇜



   󰇛  



󰇜    



(5)

󰇛





󰇜



   



󰇟

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  

󰇜



󰇛

  

󰇜

󰇠

(6)

These conditions imply that solvency is sustainable if the premium growth is sufficiently high (4), the

volatility of investment returns is bounded relative to their net performance (5), and the volatility of claim

reserves is controlled relative to the funding from other states (6).

DISCUSSION: COMPARATIVE ANALYSIS AND FEASIBILITY FOR THE ALGERIAN

CONTEXT

Building upon the analytical framework presented in the previous section, this discussion provides a

comparative analysis of the Solvency I-based approach and the stochastic differential equation (SDE) model.

The aim is to evaluate their respective merits and limitations in light of the research objectives: assessing the

feasibility of a transition for Algeria and identifying the potential benefits.

Comparative Analysis of Core Principles

A fundamental divergence lies in the philosophical approach to risk. The Solvency I-inspired

framework is fundamentally static and factor-based. It employs predetermined, deterministic formulas (e.g.,

a percentage of technical provisions or premiums) to calculate a solvency margin. While this ensures

simplicity and ease of regulatory oversight, its major limitation is its insensitivity to the specific risk profile

of an individual insurer and to dynamic market conditions. It cannot capture non-linear correlations between

risks or simulate the impact of extreme "tail events."

In stark contrast, the SDE-based model is inherently dynamic and stochastic. As formulated by Wang

and Zhu (2021) and presented in Section 3, it models key financial variables (reserves, asset returns, claim

processes) as continuous-time processes subject to random shocks (Brownian motions B

(t). This allows for

a forward-looking, risk-sensitive assessment. The model can simulate thousands of potential future economic

and claim scenarios, estimating the probability of insolvency over a given time horizon rather than providing

a single, static capital figure.

Addressing the Research Objectives: Feasibility, Comparison, and Benefits

Objective 1 & 2: Feasibility of Transition and Direct Comparison

The feasibility of adopting an SDE model in Algeria must be evaluated against key practical criteria,

which also serve as points of comparison:

Data Requirements: Solvency I requires primarily accounting and volume data. The SDE model

demands high-quality, granular historical data on investments, claims, and macroeconomic variables to

calibrate parameters (σ

, r, λ, K) reliably. This represents a significant initial hurdle for Algerian insurers and

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the regulator.

Computational & Expertise Complexity: Implementing Solvency I is computationally

straightforward. The SDE model requires advanced actuarial software and, crucially, specialized expertise

in stochastic calculus, statistical estimation, and model validation—a skillset currently in short supply in the

local market.

Regulatory Oversight: Supervising a standardized ratio (Solvency I) is simpler than validating the

internal stochastic models of multiple insurers, which would require the Algerian regulatory authority to

build significant new technical capacity.

Objective 3: Potential Benefits of a Dynamic Framework

Despite the challenges, the potential benefits of moving towards a dynamic framework are substantial

and justify a strategic, phased exploration:

Enhanced Risk Sensitivity: Capital requirements would be aligned with the insurer's actual risk

exposure, promoting more efficient capital allocation. Less risky insurers would be rewarded, incentivizing

sound risk management.

Proactive Risk Management: The ability to run stress tests and scenario analyses (e.g., simulating a

market crash coupled with a spike in health claims) would empower both insurers and regulators to identify

vulnerabilities before they crystallize.

Policyholder Protection & Systemic Stability: A more accurate assessment of solvency strengthens

the entire financial system by reducing the likelihood of unexpected insolvencies, thereby offering superior

long-term protection for policyholders — a core regulatory goal.

Alignment with International Best Practices: While a full leap to Solvency II may be premature,

exploring dynamic models positions Algeria on a pathway aligned with global regulatory evolution,

potentially improving the international perception of its insurance market.

A Proposed Pathway for Algeria

A sudden, wholesale replacement of the current system is neither feasible nor advisable. A pragmatic,

incremental pathway is recommended:

Pilot Studies: The regulator could initiate pilot projects with the largest, most sophisticated insurers

to develop and test SDE models for specific lines of business (e.g., life insurance).

Capacity Building: Parallel investment in training for actuaries, regulators, and data scientists is

essential. Partnerships with universities and international bodies could be sought.

Hybrid Approach: In a transitional phase, Algeria could consider a "tiered approach" where the

standard Solvency I rules apply, but insurers demonstrating advanced modelling capabilities are allowed to

use approved internal (SDE-based) models for part of their capital calculation, subject to strict validation.

Stakeholder Engagement: As noted in prior literature (Aissat-Leghima and Belkadi-Attab 2019), a

continuous dialogue between insurers, the regulator, and academia is vital to build consensus and tailor the

model's complexity to the local context.

CONCLUSION

This study set out to explore the potential for Algeria to transition from its current Solvency I-based

prudential framework to a more dynamic model grounded in stochastic differential equations. Through a

comparative analytical approach, the paper has addressed its three core objectives.

First, regarding the feasibility of such a shift, the analysis concludes that while a full, immediate

adoption is challenged by significant requirements in data infrastructure, technical expertise, and regulatory

capacity, a phased and strategic exploration is both possible and desirable. Initial steps should focus on pilot

studies and capacity building.

Second, the comparison between the two models reveals a fundamental trade-off. The existing

framework offers simplicity and ease of supervision but lacks risk sensitivity. The SDE-based model offers a

superior, forward-looking assessment of solvency by incorporating randomness and dynamic interactions,

but at the cost of complexity and higher implementation demands.

Third, the potential benefits of moving towards a dynamic framework are compelling. They include

more efficient capital allocation, proactive risk management through scenario analysis, enhanced

policyholder protection, and better long-term alignment with international regulatory trends. These benefits

suggest that the SDE model represents a more robust conceptual foundation for solvency assessment in a

complex financial world.

In light of these findings, the primary recommendation for Algerian policymakers is not an abrupt

regulatory change, but the initiation of a structured transition program. This program should prioritize

investments in data systems and human capital, foster collaboration between industry and academia, and

consider a tiered regulatory approach that allows advanced models to be introduced gradually. Such a

pathway would enable Algeria to modernize its solvency regime in a manner that is both prudent and

Toufik Ait Ouali, Djamila Mendil/ Finance, Accounting and Business Analysis, Volume 8, Issue 1, 2026

159

progressive, ultimately strengthening the resilience of its national insurance sector.

Acknowledgments

The authors would like to thank everyone who contributed directly or indirectly to the completion of this

research, as well as for their support and assistance.

Funding

The authors declare that this research received no external funding.

Data Availability Statement

The data used in this study are available from the corresponding author upon reasonable request.

Conflict of Interest

The authors declare no conflict of interest.

AI Tools Statement

AI-based language editing tools were used to improve grammar and clarity. All intellectual content,

interpretation, and conclusions are solely the responsibility of the authors.

Author Contributions

• Conceptualization: AIT OUALI Toufik

• Methodology: MENDIL Djamila

• Software: AIT OUALI Toufik

• Validation: MENDIL Djamila

• Formal analysis: MENDIL Djamila

• Investigation: AIT OUALI Toufik

• Resources: AIT OUALI Toufik

• Data curation: AIT OUALI Toufik

• Writing – original draft: AIT OUALI Toufik

• Writing – review & editing: MENDIL Djamila

• Visualization: MENDIL Djamila

• Supervision: MENDIL Djamila

• Project administration: MENDIL Djamila

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