https://github.com/yiqiaowang/learning/blob/master/Haskell-Programming-from-First-Principles.pdf
Some Haskell programs use functional reactive programming (FRP) models or other abstractions that avoid explicit mutable shared state altogether. Instead, changes propagate through pure functional transformations, avoiding race conditions naturally
https://acetalent.io/landing/Blog/Chapter2
https://www.learningcardano.com/why-functional-programming-languages-are-immutable/
https://github.com/OmononStephens/atc-haskell-tutorial/blob/main/chapter2.md
https://gist.github.com/cscalfani/b0a263cf1d33d5d75ca746d81dac95c5
https://github.com/haroldcarr/simple-blockchain
https://hackage.haskell.org/package/blockchain
https://serokell.io/blog/daml-interview
https://docs.immutable.com/x/anatomy-smart-contract/
Haskell in Financial Services and Fintech Derivative Pricing and Trading: Major financial institutions like Barclays use Haskell for specifying exotic equity derivatives via domain-specific embedded languages (e.g., FPF) that leverage Haskell’s compositionality and strong typing to model complex financial instruments succinctly and safely. Risk Management & Quantitative Modeling: Firms such as ABN AMRO and Credit Suisse use Haskell to build tools for counterparty risk evaluation, portfolio risk assessment, and mathematical modeling, benefiting from Haskell’s expressiveness to represent mathematical logic clearly and rigorously. Algorithmic Trading & Market Infrastructure: Some trading firms (like Allston Trading) and fintech startups adopt Haskell for back-end trading infrastructure, where low-latency, concurrent processing and correctness are paramount. Haskell’s concurrency models and pure functions enable reliable parallel computations essential in this domain. Functional Domain-Specific Languages (DSELs): Haskell allows creation of custom DSELs tailored for financial contracts, compliance reporting, and transaction systems, thus enabling easier updates and regulatory compliance in complex financial products. 3. Data Transformation and Smart Contracts Smart Contract Development: Haskell's functional paradigm facilitates building deterministic, side-effect-free smart contracts that can be reasoned about formally before deployment, minimizing runtime errors and security flaws. Languages like Plutus (Cardano) and SymPL (Symbiont) provide safe environments for writing contracts that execute on blockchains. Immutable Data Handling: The immutability inherent in Haskell data structures maps naturally onto blockchain’s append-only ledger and immutable state, ensuring transformations produce predictable and auditable outcomes necessary for trust in financial workflows. Automated Compliance and Reporting: Financial applications built in Haskell can embed regulatory rules directly into smart contracts enabling automated compliance verification, auditing, and transparent transaction recording, significantly reducing manual errors and processing time. Concurrent and Parallel Data Processing: Haskell's powerful concurrency frameworks allow handling large-scale financial data transformations, transaction validations, and event-driven smart contract executions efficiently without sacrificing correctness. 4. Industry Adoption and Impact Companies and Banks Using Haskell: Besides Cardano and IOHK, major institutions like Barclays, Standard Chartered, Tinkoff Bank, and Morgan Stanley employ Haskell in critical financial infrastructure, demonstrating trust in Haskell's robustness for precise financial computations. Fintech Startups: Startups rapidly iterate on fintech products using Haskell’s productive abstraction mechanisms for quick scaling and innovation in areas like P2P lending, payment systems, and blockchain integration. Improved Code Quality and Maintenance: Real-world reports indicate significant decreases in bugs (up to 50%), better maintainability, and faster development cycles in Haskell-based financial systems versus traditional imperative languages.