[ExI] New Study Finds a Single Neuron Is a Surprisingly Complex Little Computer

write2mark1 at gmail.com write2mark1 at gmail.com
Mon Sep 13 02:16:56 UTC 2021

> Why Fintech Companies Use Haskell
> Fintech <https://serokell.io/fintech-development> is one of the biggest
> and fastest-growing IT markets today.
> It is an emerging industry that uses technology to compete with
> traditional financial methods in the delivery of financial services. Mobile
> banking, investing services, and cryptocurrency are all solutions that make
> financial services more accessible to the general public.
> One significant trend that we have witnessed in fintech is the use of
> functional programming languages. In this blog post, we will delve deeper
> into the state of fintech right now, and how exactly functional programming
> can improve modern fintech products. In the end, we will list some
> companies that use FP in their trading, banking, or fintech infrastructures.
> Benefits of functional programming languages
> [image: FP benefits]
> Banks, trading firms, and fintech projects use functional programming
> languages like Haskell because of the properties which imperative
> programming does not provide. Most of the big companies mention three main
> reasons:
>    1. Strong typing helps prevent errors in the code that could lead to
>    problems somewhere down the path. For example, Barclays lists strong typing
>    as one of the reasons for choosing Haskell for their derivative algorithms.
>    2. The code is more readable and maintainable, and as a result, it is
>    easier to find bugs and reduce the risk of exploits.
>    3. Functional programming handles concurrency better, so these
>    languages excel at complex tasks that involve parallel actions.
> Let’s look at the most popular areas in fintech right now and how
> functional programming can help in their specific use cases.
> State of fintech
> [image: State of fintech]
> Term “fintech” includes a massive amount of companies that work on a range
> of technologies and projects with different approaches.
> Today, thousands of startups are working on unique technologies, some of
> which include KYC/ID with AI and telemetry, payment and lending protocols,
> and others. The field is a puzzle that consists of a huge amount of details.
> Furthermore, all these small puzzle pieces are trying to be interoperable
> with each other in real-time. To achieve that speed of service,
> technologies that provide faster and more concurrent services need to be
> employed. Some of the functional programming technologies (for example,
> ones that support actor-like models) are well-suited for making this
> diverse ecosystem more effective.
> To give an overarching view, here are some of the global trends that we
> see in the fintech market and FP technologies that can help them in their
> rise.
> AI, Big Data, IoT
> The technologies mentioned above are the most demanded. They are used for
> the development and implementation of chatbots, virtual consultants and
> virtual advisories, voice recognition, process automation, predictive
> analysis (including credit scoring and fraud monitoring). The goal of using
> those technologies is personalization, transaction security, an increase in
> time management efficiency, and client behavior analysis.
> FP can bring success to these fields. Scala is already widely used in big
> data for its superior concurrency and Apache Spark
> <https://spark.apache.org/>, while Nerves
> <https://www.nerves-project.org/>, an Elixir framework, looks very
> promising <https://www.cognizantsoftvision.com/blog/year-of-elixir/> for
> IoT.
> Transaction processing and infrastructure
> The number of card transactions grows by a CAGR of 13.6% annually,
> according to the Global Payments 2019 report
> <https://image-src.bcg.com/Images/BCG-Global-Payments-2019-Tapping-into-Pockets-of-Growth-September-2019-rev_tcm9-231986.pdf>.
> One reason for that is the integration of biometric analysis and
> contactless payments.
> Functional programming languages allow for the building of stable
> infrastructures that are more reliable, fault-tolerant, and have fewer
> errors. In particular, Elixir is great for situations where you need to
> handle a lot of small interactions from a multitude of users.
> Credit and insurance technologies
> Today, credits and insurance are issued not only by traditional banks but
> by smaller private companies and startups. There are tons of projects that
> provide P2P lending, and technologies in this field are developing very
> fast.
> If you are a startup in the field of credit or insurance, you need to move
> fast. A well-built FP team will be able to iterate quickly and scale your
> product better, since the paradigm allows for better productivity and
> faster large-scale changes.
> Read our interview <https://serokell.io/blog/haskell-in-industry-riskbook>
>  with a startup in the field of reinsurance, Riskbook, to learn more
> about the benefits of Haskell for rapidly changing fields.
> Blockchain and cryptoсurrencies
> Businesses use blockchain technology as a fast and safe way of dealing,
> monitoring funds, making quick international payments, storing and sharing
> reports. A lot of banks unite under Ripple or HyperLedger partnership to
> exchange information between them. Blockchain can be used to store
> biometric data as well.
> Functional programming (especially Haskell) is great for handling
> blockchains due to immutability, type safety, and the ability to manage
> distributed computation well. Haskell also enables one to build excellent
> domain-specific languages, such as smart contract languages
> <https://serokell.io/blog/lorentz-implementing-smart-contract-edsl-in-haskell>
> .
> Companies that use functional programming
> Fintech
> Klarna
> [image: Klarna]
> The European payments startup Klarna <https://www.klarna.com/>uses a wide
> variety of functional programming languages like Scala, Erlang, Clojure,
> and Haskell. The core of their services is in Erlang.
> Digital Asset
> Digital Asset is a fintech company that helps companies design and run the
> next generation of business applications, mainly with the help of DAML
> <https://daml.com/>, a smart contract language written in Scala. They
> have a multitude of languages on their GitHub, including Haskell and Scala.
> You can read our interview with them on our blog
> <https://serokell.io/blog/daml-interview>.
> Adjoint
> [image: Adjoint]
> Adjoint <https://www.adjoint.io/> digitises cash and settlement processes
> for multinational corporates. Right now, their main product is Adjoint
> Treasury, a real-time payments and settlement platform for corporate
> treasuries.
> Banking & trading
> Barclays
> Barclays <https://www.barclays.co.uk/> has an embedded domain-specific
> functional language (FPF) written in Haskell to specify exotic equity
> derivatives. We have covered it in more detail in our Haskell stories of
> success <https://serokell.io/blog/top-software-written-in-haskell>.
> Standard Chartered Bank
> [image: Standard Chartered]
> Standard Chartered <https://www.sc.com/> uses their own strict dialect of
> Haskell called Mu, and has an insanely large codebase, featuring around
> half a million lines of Haskell code and 4.5 million lines of Mu code.
> Tinkoff Bank
> Tinkoff <https://www.tinkoff.ru/eng/> uses Haskell for the backend of
> Tinkoff Travel Agency and Scala for the backend of Tinkoff Bank.
> Jane Street
> [image: Jane Street]
> Jane Street uses OCaml for almost all the backend, from low-latency
> trading and market risk systems to tools for managing and monitoring
> infrastructure, workflow tools, and data analytics.
> To learn more about the reasons for this choice, you can watch a detailed
> talk from their tech side: Why OCaml
> <https://www.youtube.com/watch?v=v1CmGbOGb2I&feature=emb_title>.
> Morgan Stanley
> Morgan Stanley uses Scala and is home to massive large-scale Scala
> projects. For more information on Scala at Morgan Stanley, you can check this
> short video <https://vimeo.com/147697498>.
> And many more
> In addition, many other financial companies have used or use Haskell or
> other functional programming languages:
>    - JP Morgan
>    - BNB Paribas
>    - Merrill Lynch Bank of America
>    - Deutsche Bank
>    - ABN AMRO
>    - Credit Suisse Global
>    - Allston Trading
> With a lot of heavyweight banks and startups doing functional programming,
> it seems to be a trend that won’t go away. Furthermore, fintech is becoming
> more complex and distributed every minute, with banks realizing that in the
> face of the COVID crisis, they are not digital enough. Functional
> programming, it seems, has the tools to solve the problems associated with
> that. Whether you are a fintech startup or a bank, perhaps it is time to
> start thinking about making a switch to a more future-proof technology.
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