Sukuk market surveillance: 5 patterns regulators are watching in 2026

Context: why sukuk need different surveillance than bonds

The sukuk market is larger than many assume. The IIFM Sukuk Report 2025 puts global outstanding at approximately USD 902.82 billion at end-2024, with 2024 annual issuance of approximately USD 205 billion.[^1] Saudi Arabia, Malaysia, Indonesia, the UAE, and Qatar are the primary players.

Sukuk follow a fiqh logic that has no parallel in conventional bonds:

• AAOIFI SS 17 (Shariah Standard 17, Investment Sukuk) requires that sukuk represent undivided shares in the ownership of tangible assets, usufructs and services, not conventional debt[^2]
• AAOIFI SS 21 (Financial Paper — Shares and Bonds) governs the broader category of equities and conventional bonds and provides the foundation for Shariah equity screening; sukuk-specific secondary-market tradeability rules sit primarily in SS 17[^3]
• AAOIFI SS 62 (Sukuk) — Exposure Draft published November 2023 with feedback deadline extended to 31 July 2024 — would mandate actual transfer of legal ownership of underlying sukuk assets to sukuk holders, generating market debate and delays in some issuances[^4]

Each of these has implications for what a trade-surveillance system must watch. SAMA, CMA, and BNM circulars require banks and financial institutions to evaluate sukuk transactions under both a Shariah lens and a regulatory market-abuse lens. That is a real data and annotation challenge.

A note: I am not a sukuk market expert. My background is data. This piece is written from the perspective of a data team trying to understand what a regulator needs. For actual surveillance-system planning, refer to trade-surveillance advisors (NICE Actimize, FIS, Aquila, Eventus), a Shariah advisor, and the official documents of CMA, SCA, DFSA, FSRA, QFMA, CBB, and BNM.

Pattern 1: spoofing on Tadawul and Nasdaq Dubai

Spoofing is a classic surveillance pattern — a trader places large buy or sell orders without intent to execute, moves the price, then withdraws the orders after the trade fills on the opposite side. Prohibited under:

• CMA Saudi Arabia — the Capital Market Law and Market Conduct Regulations (with regulatory updates through 2025)[^5]
• CMA UAE — Federal Decree-Laws 32/33 of 2025 (effective 1 January 2026), which replaced the SCA framework under Federal Law No. 4 of 2000[^6]
• DFSA + FSRA — DIFC and ADGM rules on Market Abuse
• QFMA + CBB + BNM — equivalent frameworks

Sukuk differ from equities in:

• Lower liquidity — Sukuk generally trade thinner than conventional bonds and thinner than equities. This makes spoofing both easier (a small daily volume means medium-sized orders move price) and harder to detect (a thin behavioral baseline gives less to compare against)
• Issuer context — Saudi sovereign sukuk trade with heavy institutional bias, corporate sukuk trade with broader patterns, and the two have different “natural” rhythms
• Fatwa events — A signal from a sukuk issuer’s Shariah board can move the market suddenly. A spoofing attempt right before or after a fatwa must be detected

What needs annotation to train a detection model:

A model that fails to grasp that Saudi sovereign sukuk trade thinner than Nasdaq Dubai-listed sukuk will fire many false positives, or it will miss suspicious activity because “the volume looks broadly normal.” Read sukuk surveillance solutions for banking.

Pattern 2: AAOIFI SS 17 tradeability and secondary-market grey zones

AAOIFI SS 17 (Investment Sukuk) is the canonical standard governing sukuk and their tradeability; the SS 62 exposure draft (2024) would further tighten asset-transfer expectations.[^2][^4] The key points commonly drawn from SS 17 and supporting AAOIFI materials:

• Sukuk backed by a real asset (ijarah, musharakah, mudarabah, istisna’a) are typically tradeable at market price
• Sukuk backed predominantly by outstanding debt (murabaha as debt) — generally not tradeable at a discount or premium to face value under the general rule
• Exceptions exist where the underlying assets are predominantly real and debt sits below a defined threshold

In the secondary market many sukuk are hybrid — a murabaha layer plus an ijarah layer plus another. The ratio between real asset and debt drifts over time (escrow absorption, partial redemption, cash-flow distribution). That creates a grey zone:

• At what point does a sukuk shift from “tradeable at market price” to “restricted”?
• How does the surveillance system catch trades that breach that shift?
• Who annotates the fiqh judgment on each sukuk at each point in time?

This is not just a Shariah question — it is a data question. The model needs:

• Annotation of each sukuk’s type (contract structure, asset-to-debt ratio, drift over time)
• Annotation of each issuer’s Shariah board fatwas
• Annotation of trading behavior “consistent with AAOIFI SS 17 / SS 62” versus “outside the envelope”

Note that some central banks in the region (BNM Malaysia in particular, via its in-house Shariah Advisory Council) hold a broader interpretation of what is permissible in the secondary market than the AAOIFI Gulf school.[^7] Sukuk listed on Bursa Malaysia may follow the BNM Shariah Council’s interpretation; sukuk on Tadawul follow a position closer to AAOIFI. A cross-jurisdictional model must learn this.

Pattern 3: spread manipulation between dual-listed tranches

Many sukuk are listed on two or more exchanges. Examples:

• Saudi sukuk listed on Tadawul + Nasdaq Dubai
• UAE sukuk listed on ADGM + DIFC
• Malaysian sukuk listed on Bursa Malaysia + LFX (Labuan)[^8]
• Bahraini sukuk listed on BHB, with cross-listing on Nasdaq Dubai available structurally[^9]

Dual-listing creates an arbitrage spread opportunity. Legitimate within limits, but problematic when:

• A single trader places synchronized orders on two exchanges to create the illusion of liquidity
• A trader exploits the close + open time difference between markets (Tadawul closes before Nasdaq Dubai) to generate gains on exclusive information
• A trader pushes a tranche price on a thin-liquidity exchange to move the price of the deeper-liquidity tranche on the other

DFSA and FSRA both monitor this under their Market Abuse frameworks. Regulators in the region coordinate through IOSCO multilateral arrangements and bilateral cooperation, but practical cooperation in detecting synchronized cross-border trading remains incomplete, especially across Gulf borders.

What needs annotation in a detection model:

• Matching sukuk identifiers across two exchanges (ISIN, CUSIP, local symbol, Nasdaq Dubai symbol, Tadawul symbol)
• Synchronized transactions within a defined time window
• Trader identity (within the bounds available to the regulator)
• Behavioral tags for normal versus suspicious patterns

Pattern 4: Shariah non-compliance signals from news and social media

This is the newest pattern and the most technology-heavy. The regulator’s question: when do sukuk shift from “Shariah-compliant” to “under Shariah suspicion”?

Real examples from the last decade:

• AAOIFI SS 62 (2024 Exposure Draft) on sukuk asset transfer / tangibility — triggered public debate about whether specific sukuk breach the draft. Some issuances were postponed[^4]
• Sheikh Taqi Usmani’s historical critiques of sukuk structures (2007-2008) shook the market — AAOIFI subsequently noted that a large share of sukuk in issue may not be Shariah-compliant[^10]
• Individual Shariah-board fatwas on specific issuances can create open “fiqh disagreement” that affects price

A model that scans news and social media for Shariah non-compliance signals needs:

• A dataset of Arabic and English news annotated as “contains a negative Shariah signal” / “contains Shariah support” / “neutral”
• Precise annotation of the Shariah school (AAOIFI school, BNM school, individual Shariah advisor, government fatwa house)
• Annotation of reach and source authority (a tweet from a known scholar ≠ an anonymous post)
• Linking the signal to specific sukuk + issuer + tranche

Islamic finance contract NLP solutions come in here too — because a strong model also links the signal back to a specific clause in the issuance document.

Caveat: extracting Shariah signals from text is sensitive work. A model that fails to distinguish respectable academic debate from an attack on an issuance will create misleading alerts. The final fiqh decision rests with the institution’s Shariah board, AAOIFI, and BNM — not with an alerting model.

Pattern 5: substitution patterns between sukuk and conventional instruments

The subtlest pattern. An investor who claims Shariah alignment in their funds sells sukuk and buys conventional bonds in a narrow time window. Or vice versa. That can be:

• Legitimate — portfolio rebalancing, liquidity flow, strategy change
• Shariah-grey — investor claims Shariah compliance in their funds but harvests yield opportunities through conventional bonds
• Hidden for laundering — value transferred between two instruments to mask source of funds

Saudi Arabia, the UAE, and Malaysia under FATF require financial institutions to scan for suspicious activity patterns. SAMA, CBUAE, and BNM all have AML guidance for both conventional and Islamic instruments.

The model needs:

• Trading data for a client across the full portfolio (sukuk only is not enough)
• Annotation of each trade type (sukuk / conventional bond / Islamic fund / conventional fund)
• Annotation of normal patterns versus suspicious patterns (binary at first, graduated later)
• KYC context per client (conventional institutional investor, verified Islamic fund, individual claiming Shariah alignment)

Read AML solutions for banks and the KSA bank AML modernization blueprint for the integrated operational frameworks.

Regional regulator positions

A summary of each regulator’s position on sukuk-market surveillance (per published official documents and guidance, as of 2025):

The regulators are moving toward automated trade-surveillance tooling in the 2026 decade — this is on the record in CMA annual reports, the DFSA Annual Report, and the BNM Financial Stability Report. NICE Actimize, Eventus, Trillium, FIS, and Nasdaq Trade Surveillance compete in the region. But all of these tools need local training data to understand sukuk context.

What needs annotation — summary

Across the five patterns, the common annotation layers:

Every layer needs annotation teams that understand Arabic, Shariah, finance, and Islamic-market context. A rare combination. A working model is not built by an annotation team that only understands spreads and FX.

What Annota8 does — and does not do

We do:

• Build training data for sukuk trade-surveillance patterns with an Arabic team and a Shariah advisor
• Annotate contract structure, asset-to-debt ratio, fatwas, trading patterns
• Support Arabic and English NLP on news and social media for Shariah signal detection
• Follow Saudi PDPL, Malaysian IFSA, and DFSA / FSRA guidance on personal data

We do not:

• Sell trade-surveillance systems. Our partners (financial institutions and tech partners like NICE Actimize, Eventus, Aquila) do
• Issue Shariah rulings. The final decision sits with the institution’s Shariah board, AAOIFI, and BNM
• Provide Market Abuse legal advice. Engage licensed legal advisors in the institution’s jurisdiction

What this means for the buyer

• If you are building sukuk surveillance, start with the annotation layers and then the model, not the reverse
• Use an Arabic annotation team plus a Shariah advisor — a model without context fails
• Understand the difference between the AAOIFI Gulf school and BNM Malaysian interpretations if you operate cross-jurisdiction
• Do not rely on a lightly modified conventional-bond surveillance model. Sukuk are structurally different
• Engage the regulator early — CMA, SCA, DFSA, FSRA, QFMA, CBB, and BNM all welcome pre-deployment review of a surveillance model