AI solutions for banking and financial services, built for the regulator in the room
We build AI solutions for banking and financial services firms that read KYC packs, triage claims, flag anomalies and answer customers, with the audit trail a SAMA, RBI or UAE Central Bank examiner expects. We also run the cryptographic inventory and quantum risk assessment Saudi banks must file by 31 December 2026 and 31 March 2027.
AI in BFSI has two clocks running at once
The first clock is operational: documents arrive faster than teams can read them, customers expect an answer in minutes, and legacy core systems resist every new channel. The second clock is cryptographic: regulators have set dates by which the RSA and elliptic-curve keys protecting payments and customer data must be inventoried and replaced. Most AI vendors see only the first clock.
Where we deliver: in Saudi Arabia, under SAMA's August 2026 circular on quantum computing risks, NCA ECC-2:2024 and the SDAIA PDPL; in UAE, under UAE PDPL and the Cyber Security Council's November 2025 National Encryption Policy; in India, under RBI and SEBI cyber frameworks, the DPDP Act 2023 and the DST quantum-safe roadmap of February 2026; and in United States, aligned to NIST FIPS 203 and 204 and the OMB M-26-15 schedule. Offices are on our locations page.
Six places AI earns its keep in a bank or insurer
Each workflow below connects to a core system, has a human decision point and produces an auditable record.
Financial document processing
KYC packs, bank statements, salary certificates and Arabic or bilingual invoices are extracted, validated against your customer master and routed with every field traceable to its source page. See intelligent document processing.
Customer service and knowledge assistants
Retrieval-grounded assistants over product terms, policy wordings and procedures, in English, Arabic and Indian languages, that answer only from approved content and hand off to a person when confidence drops.
Learn more →Fraud and anomaly analytics
Transaction, device and behavior features scored in near real time, with explanations an investigator can read. Fraud detection AI for banking is tuned to your false-positive budget, not a vendor benchmark.
Risk modeling and forecasting
Collections propensity, liquidity and claims-frequency forecasts built in a governed data platform, with model documentation written for validation teams from the first version.
Learn more →Policy and contract information extraction
Clauses, exclusions, limits and renewal dates pulled from policies and loan agreements into structured records, so claims handlers search terms rather than PDFs. AI for insurance claims starts here.
Secure enterprise platform integration
Digital onboarding platforms and licensed integrations with depositories, payment rails and core banking, built with the identity, logging and segregation controls your security policy requires.
Learn more →Document AI, governed GenAI and quantum-safe cryptography from one engineering team
Our document AI, analytics, agentic GenAI and enterprise API teams work with the same security architects who run our post-quantum cryptography practice. One party can extract a KYC document, build the approval workflow around it and tell you which TLS certificates and HSM keys protecting that workflow must move to ML-KEM and ML-DSA.
The PQC timeline is short for a bank. NIST published FIPS 203, 204 and 205 in August 2024, and its draft IR 8547 deprecates RSA-2048 and P-256 after 2030 and disallows them after 2035. Our post-quantum cryptography service covers inventory, crypto-agility design and migration planning.
A worked example: document onboarding plus a quantum-safe cryptography inventory
A bank wants faster account opening and a plan for SAMA's quantum circular. We run the two as one program, because the onboarding platform is the first system whose cryptography gets inventoried.
- 01
Identify the onboarding bottleneck
Account opening stalls on manual reading of ID, address and income documents. We measure handling time per pack and agree the pilot: retail onboarding, one segment.
- 02
Map systems and cryptographic assets
Core banking, the KYC vendor, the document store and the API gateway are mapped for integration and for cryptography: certificates, key lengths, HSM slots and signing algorithms go into a cryptographic bill of materials.
- 03
Define pilot metrics and inventory scope
Extraction accuracy per field and straight-through rate for onboarding; coverage of in-scope systems and exposure ranking for the CBOM, aligned to the SAMA inventory date of 31 December 2026.
- 04
Prototype extraction with real packs
Anonymized production documents in Arabic and English run through a multi-model pipeline with a judge model, field-level confidence and a review queue.
- 05
Validate security and compliance
Residency, access controls, audit logging and model documentation reviewed by your security and compliance teams. Quantum-vulnerable algorithms in the onboarding path are flagged for the risk assessment due 31 March 2027.
- 06
Integrate and plan the migration
Extraction results post to core banking through the existing gateway. The risk assessment produces a crypto-agility design and a migration order, starting with long-lived customer data.
- 07
Monitor both programs
Straight-through rate and review backlog are tracked weekly. The CBOM is refreshed as systems change, so the board report stays current.
How value is measured in regulated finance
Success is counted in handling effort per document, model error per field, cases resolved without escalation, audit findings closed and, for cryptography, the share of in-scope systems inventoried and migrated against the regulator's dates. The baseline comes from your operations data before any model runs, and we test under month-end volumes, poor scans and mixed-language packs. If a field cannot reach the agreed accuracy it stays with a human reviewer.
Governance that satisfies SAMA, RBI, SEBI and UAE Central Bank
Every AI workflow we deliver to a financial institution carries model documentation, data lineage, role-based access, immutable logs and a human approval point. Data stays in the jurisdiction the regulator requires, in your tenant.
The frameworks follow the market: in Saudi Arabia, SAMA's cyber security framework and its 2026 quantum circular, NCA ECC-2:2024 and the SDAIA PDPL; in UAE, UAE PDPL, the Central Bank's information security requirements and the National Encryption Policy of November 2025; in India, the RBI cyber security framework, SEBI's cyber resilience framework and the DPDP Act 2023; in United States, NIST SP 800-53 controls and FIPS 203 and 204 for new cryptography. Proposals pass your compliance review before touching production.
Why banks and insurers work with Constient
Because we have built onboarding platforms and licensed integrations for securities firms in India, done SAMA and NCA ECC compliance work in Saudi Arabia, and run Arabic document extraction feasibility with multiple vision models. The same group carries the post-quantum practice, so quantum-safe banking is handled by people who already know core systems.
On the quantum side we are research-led: no bank has yet taken a quantum system from us into production, and we will tell you that before you ask. What we offer today is an inventory, a risk assessment and a migration plan built on published NIST standards and the regulator's dates.
Frequently asked questions
How quickly can Constient start a SAMA quantum circular inventory?
Within two to three weeks of a scoping call, subject to access approvals. The first deliverable is a cryptographic bill of materials covering certificates, keys, HSMs, signing and tokenization across in-scope systems, structured to the 31 December 2026 inventory requirement. The risk assessment and action plan for 31 March 2027 follow from it, with wording confirmed against the SAMA rulebook.
Where does our customer data stay during an AI pilot?
In your region and your tenant. For Saudi banks that means in-Kingdom infrastructure under the SDAIA PDPL and SAMA requirements; for UAE institutions, in-country under UAE PDPL; for Indian firms, in India under RBI localization directions and the DPDP Act 2023. We work on anonymized samples wherever the pilot allows and document every data flow for your compliance team.
Can your document AI handle Arabic and bilingual documents?
Yes. We have run extraction feasibility on Arabic invoices using several vision language models with a judge model selecting the best reading per field. Accuracy is measured on your own document mix during the pilot rather than quoted in advance, and low-confidence fields route to a reviewer rather than being guessed.
How do you integrate with core banking and payment systems?
Through your existing API gateway or integration layer wherever possible, read-only first. We have built licensed integrations with depositories and payment providers for Indian securities firms and connected document workflows to core platforms through approved middleware. Direct database access is a last resort, only with your security team's sign-off.
What does a BFSI AI engagement cost and how is it structured?
Discovery and pilot are fixed price. Production work is a fixed-price build with a support agreement or a dedicated team billed monthly, depending on how many workflows and systems are in scope. Cryptographic inventory and risk assessment are scoped by number of systems and delivered as fixed-price packages, with migration engineering priced after the assessment.
Build a financial services technology roadmap with both clocks in view
Bring the document backlog, the fraud question or the SAMA deadline. We will map the systems and propose a bounded pilot.