Mobile Currency Converter Development for iOS & Android

Note: when converting 10,000 USD to RUB, a loss of 47 rubles due to Float rounding appears as a bug to the user—not a feature. Technically, a converter is simple, but errors in arithmetic, caching, or API integration turn it into a source of complaints. In this article, we break down how to build a reliable module from scratch: from selecting a rate provider to handling edge cases with locales and rounding. Our team brings over 10 years of mobile development experience and more than 40 fintech modules to date—we know all the pitfalls and guarantee accuracy across all devices.

How to choose an API for currency rates?

Choosing an API depends on requirements for update frequency and currency coverage. Compare popular options:

ExchangeRate-API is 3x cheaper than Fixer.io on average request volume. For most apps, daily updates are sufficient—the CBR provides XML at https://www.cbr.ru/scripts/XML_daily.asp, parsed via XMLParser on iOS or XmlPullParser on Android. Note: the CBR uses windows-1251 encoding and may change the response format. We always apply automatic regression tests on sandbox data and provide a fallback to another provider.

Why Decimal, not Float?

Never use Float or Double for financial calculations. The difference in cents becomes noticeable when converting large sums. Compare precision:

For 1,000,000 USD, a 0.01% discrepancy yields a 100 USD error. On iOS we use Decimal, on Android BigDecimal. They guarantee cent‑level precision and correct rounding according to financial math standards. Learn more about the Decimal data type.

Offline caching and background sync

Rates are stored locally: Core Data / Room to enable offline use with the last known values. We display the timestamp of the last update so the user knows how fresh the data is. For the latest rates, we use background sync via WorkManager (Android) or BGTaskScheduler (iOS). On one project we implemented a TTL of 30 minutes and a 7‑day cache. The user always sees data freshness, and when offline—a warning.

import Foundation

struct CurrencyRate: Decodable {
    let code: String
    let nominal: Int
    let value: Decimal
}

class CBRParser: NSObject, XMLParserDelegate {
    private var rates: [CurrencyRate] = []
    private var currentElement = ""
    private var currentCode = ""
    private var currentNominal = ""
    private var currentValue = ""

    func parse(data: Data) -> [CurrencyRate] {
        let parser = XMLParser(data: data)
        parser.delegate = self
        parser.parse()
        return rates
    }

    func parser(_ parser: XMLParser, didStartElement elementName: String, namespaceURI: String?, qualifiedName qName: String?, attributes attributeDict: [String : String] = [:]) {
        currentElement = elementName
    }

    func parser(_ parser: XMLParser, foundCharacters string: String) {
        switch currentElement {
        case "CharCode": currentCode += string
        case "Nominal": currentNominal += string
        case "Value": currentValue += string
        default: break
        }
    }

    func parser(_ parser: XMLParser, didEndElement elementName: String, namespaceURI: String?, qualifiedName qName: String?) {
        if elementName == "Valute" {
            let rate = CurrencyRate(code: currentCode.trimmingCharacters(in: .whitespacesAndNewlines),
                                    nominal: Int(currentNominal.trimmingCharacters(in: .whitespacesAndNewlines)) ?? 1,
                                    value: Decimal(string: currentValue.trimmingCharacters(in: .whitespacesAndNewlines).replacingOccurrences(of: ",", with: ".")) ?? 0)
            rates.append(rate)
            currentCode = ""
            currentNominal = ""
            currentValue = ""
        }
    }
}

Process of developing the converter

1. Analysis – gather requirements (currencies, precision, update frequency) and select API.
2. Design – architecture: data layer, repository, cache, view model (MVVM + Clean Architecture).
3. Implementation – codebase with unit tests (20+ tests for arithmetic and caching).
4. Integration – connect chosen API, handle errors (no network, rate limits, format changes).
5. Testing – test on 10 real devices with different locales and regions.
6. Deployment – release to App Store / Google Play, passing review.

What's included

• Source code in Swift (iOS) or Kotlin (Android) with comments.
• API documentation and instructions for key renewal.
• Configured caching scheme (local DB) with TTL.
• Test report with code coverage >80%.
• Support for 2 weeks after delivery.

Timeline and cost

Implementation timeline: 3 to 7 business days. The price is fixed after the TOR is agreed upon and does not change. Save up to 30% on development time when ordering a comprehensive solution. Contact us for a project estimate—we will find the optimal solution for your budget.

Typical mistakes in converter development

• Ignoring Decimal: 95% of converter bugs are related to rounding.
• Missing locale handling: on a German locale the comma is a thousands separator, breaking parsing.
• Tight coupling to one API: always design for switching providers.
• No cache expiry check: the user sees week‑old rates without warning.

Order a turnkey currency converter development and get a ready solution with source code and support.

How to Start Integrating API into a Mobile App?

The request goes out, the response doesn't come, timeout — 30 seconds. The user stares at the spinner. No network — mobile card in the subway. Or the network is there, but the server returns 200 with an HTML error page instead of JSON — and the app crashes on JSONDecoder.decode(). We see such cases on every second project. So integrating API into a mobile app is not just calling an endpoint, but designing a reliable network layer: error handling, caching, offline mode, certificate pinning. Order an audit of your current network layer — we will evaluate the project in 1 day. Our team guarantees a thorough analysis and provides a detailed roadmap.

Standard libraries like URLSession and OkHttp provide basic HTTP clients, but for production you need retries with exponential backoff, status code validation, typed deserialization, and network state monitoring. Without this, the app loses data and users. We have been doing mobile development for 5 years and implemented more than 30 projects with API integration on iOS, Android, and Flutter — from startups to enterprise solutions.

How to Choose a Protocol for API Integration?

REST remains the standard for most projects. But when a profile screen needs 5 fields out of 40, GraphQL eliminates over-fetching and reduces traffic by 30–60%. gRPC is justified for thousands of requests per minute (trading, IoT) — binary serialization is 3–5 times faster than JSON. WebSocket is the only choice for real-time without polling (messages, notifications).

Practical example: For a fintech app, we replaced REST (40 fields) with GraphQL — response size dropped from 12 KB to 2.5 KB, screen render time decreased by 70%. Traffic savings were significant. Our certified iOS and Android developers have deep experience with all these protocols — you can rely on proven solutions.

How to Ensure Reliable Connection and Offline-First?

Users lose network in the subway, elevator, tunnel. A mobile app must work without internet — at least in read-only mode. We implement the offline-first pattern:

1. On screen open, first show data from the local cache (Core Data / Room).
2. Simultaneously perform a network request, update UI after response.
3. If network is unavailable — show cached data and a 'no connection' label.
4. When network is restored, automatically synchronize changes.

For HTTP response caching we use URLCache (iOS) and OkHttp Cache (Android) with Cache-Control support. For structured data — SwiftData / Room. NWPathMonitor / ConnectivityManager.NetworkCallback monitor network state and trigger updates.

REST and Client Library Selection

Alamofire (iOS) — de facto standard for Swift projects. On top of URLSession it adds request chaining, response validation, automatic retry, certificate pinning via ServerTrustManager. AF.request() with .validate() returns an error for any status code outside 200–299. Without .validate(), Alamofire considers 404 and 500 as successful responses. With Swift Concurrency — async version via serializingDecodable.

Retrofit (Android) — annotation-based HTTP client on top of OkHttp. An interface with annotations compiles into implementation. @GET, @POST, @Path, @Query, @Body — declarative API description. OkHttp under the hood: connection pooling, transparent gzip, HTTP/2 multiplex. HttpLoggingInterceptor — logging in debug builds. Authenticator — automatic token refresh on 401.

Ktor (KMM/Flutter) — multiplatform HTTP client. On iOS it works via Darwin engine (URLSession), on Android — via OkHttp. Single code for both platforms with KMM architecture.

GraphQL: When REST Falls Short

REST returns a fixed structure. A profile screen needs name, avatar, email — the server sends 40 fields. Over-fetching. GraphQL solves this: the client requests exactly the needed fields. This is critical for mobile where traffic and parsing time are real constraints. Apollo iOS and Apollo Kotlin generate typed classes from schema: schema.graphql + query files → strict types at compile time. Subscriptions via WebSocket — real-time without polling. Limitation: GraphQL is harder to cache at the HTTP level. Apollo uses a normalized in-memory cache InMemoryNormalizedCache — requests with overlapping data update the cache without duplication.

WebSocket: Real-Time Without Extra Traffic

Polling (setInterval every 5 seconds) — battery and traffic waste. WebSocket is a persistent bidirectional connection. iOS: URLSessionWebSocketTask (native, iOS 13+). Android: OkHttp WebSocket. Mandatory reconnect handling: on onFailure — exponential backoff (1s → 2s → 4s → 8s → max 60s). Socket.IO is an overlay with automatic reconnect, but for new projects native WebSocket is preferable (fewer dependencies).

gRPC: For High-Load Services

gRPC with protobuf — binary serialization: smaller size, faster parsing. grpc-swift for iOS, grpc-kotlin for Android. The protobuf schema compiles to typed classes. Streaming (server-side, client-side, bidirectional) is a native feature. Application threshold: high request frequency (trading, IoT) or critical latency. For regular CRUD, REST is simpler to debug and monitor.

Certificate Pinning and Security

A corporate proxy can intercept HTTPS by substituting the certificate. Certificate pinning prevents this: the app accepts only a specific certificate or public key. Alamofire: ServerTrustManager with PinnedCertificatesTrustEvaluator. OkHttp: CertificatePinner with SHA-256 hash. Apple's App Transport Security documentation recommends pinning certificates for sensitive data. Operational complexity: on certificate rotation, older app versions stop working. Solution — pinning to the CA public key or support multiple pins with a grace period.

What Is Included in the Work

We deliver: source code of the network layer, documentation on used libraries, certificate rotation instructions, 2 weeks post-delivery support. Our experience guarantees that the solution will be stable and maintainable.

Timeline and Cost

Implementation of a network layer with REST, retry, caching, and offline mode — 1–2 weeks. Adding GraphQL or WebSocket — another 1–2 weeks. gRPC — 2–3 weeks, including code generation. The cost is calculated individually after analyzing the API and offline behavior requirements. We will evaluate the project in 1 day — contact us for a consultation. Get a reliable API integration with guaranteed quality.