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Industry · Financial Services

Technology built for
the regulated enterprise.

Financial services organizations carry the heaviest legacy debt of any industry — COBOL core banking systems running for forty years, batch processes reconciling overnight on systems nobody fully understands, and integrations that exist in production but not in any documentation.

Shelorve delivers AI, cloud, legacy transformation, and Salesforce inside the regulatory and compliance environment that makes this industry different from every other. Built in from the first decision. Not retrofitted at the end.

The Challenge

What makes financial services technology different

SOX and FFIEC as architectural requirements
Regulatory compliance in financial services is not a checklist applied after the system is built. SOX requires audit trails, access controls, and change management designed into the architecture from day one. FFIEC model risk management guidance (SR 11-7) mandates explainability and validation documentation for any AI used in credit or risk decisions. These are first-class architectural requirements that shape every decision Shelorve makes in a financial services engagement.
Legacy core banking complexity
Core banking systems in financial services are among the most complex technology estates in any industry. COBOL programs that have been modified thousands of times by practitioners who are no longer available. Batch jobs that run at 2am reconciling accounts across systems that were designed to work independently. Dependencies that exist nowhere in documentation but will fail catastrophically if disturbed. This is precisely the environment Reveliq™ was designed for.
Real-time AI in regulated environments
AI in financial services must be explainable, auditable, and operationally robust — simultaneously. A fraud model that catches fraud is not sufficient if the compliance team cannot explain to a regulator why a specific transaction was flagged on a specific date. Shelorve designs explainability and audit trail into every AI system in financial services from the first sprint.
Data residency and sovereignty
Financial institutions operate under data residency requirements that govern where data can be stored and processed. Cloud architecture must reflect these requirements from the first infrastructure decision — not as a retrofit after the data model is already built around services in the wrong region.
What We Deliver

Services for Financial Services

AI & Fraud Detection

Real-time SageMaker ML scoring for fraud and AML — sub-50ms latency, explainable outputs for regulatory review, and a complete audit trail built into the pipeline from day one.

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Core Banking Modernization

Reveliq™-led migration from COBOL to AWS serverless — zero downtime, compliance maintained throughout every phase, risk-ranked sequencing based on the complete dependency map.

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AWS for Financial Services

SOX-compliant AWS architecture — security controls, data residency, audit logging, and FinOps built into the baseline infrastructure. Not retrofitted after the system is live.

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Salesforce for Financial Services

Wealth management platforms, advisor portals, and client lifecycle management — connected to core banking via MuleSoft, configured for financial services compliance requirements.

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100%
Audit trail built into every financial services AI system from sprint one
0
Compliance requirements retrofitted after build
Day 1
Compliance team has everything they need for regulatory review before go-live
Financial Services · Common Questions

What financial services leaders ask us before they engage

Yes. Every financial services engagement is designed with compliance as a first-class architectural requirement — not retrofitted after build. We have delivered AI systems, cloud migrations, and Salesforce implementations that satisfy SOX, FFIEC, BSA, and OCC requirements. Compliance is a design input, not a post-delivery audit.
Yes. Shelorve uses Reveliq™ to map every dependency — including undocumented integrations between COBOL programs, batch jobs, and downstream systems — before touching production code. We have completed zero-downtime migrations of core banking systems using traffic-shifting and parallel-run approaches, with compliance maintained throughout every phase.
Fraud detection, AML transaction monitoring, credit risk scoring, predictive churn modeling, and document intelligence for KYC and onboarding. All built with model explainability and a full audit trail — so the compliance team can answer any regulatory question about any model decision on any date.
Data residency requirements are defined before any architecture decision is made. We work in compliant AWS regions and implement data classification, access controls, and residency enforcement as part of the baseline architecture. These are not constraints we work around — they are architectural inputs we design from.
Yes. FFIEC SR 11-7 requires model validation, documentation, and ongoing monitoring for all models used in credit and risk decisions. Shelorve designs the governance framework — model documentation, validation evidence, performance monitoring, and drift detection — into every AI engagement in financial services. The compliance team has what they need for regulatory review before the model goes live.
Financial services transformation

Starts with understanding
what is actually there.

Tell us what you are trying to solve. We know the regulatory environment, the legacy complexity, and what it takes to change systems that the business cannot afford to get wrong — because we have done it before, in production, under real conditions.

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