Robo-Advisory Software Development Services

Investors can create an account with the robo-advisory platform and add the necessary information (personal data, billing details, proofs of identity and residence, beneficiary information, IRA/ISA, preferred payment methods, etc.) using a step-by-step self-registration form. The solution automatically localizes the form’s language, app time zone, and KYC/AML questions based on the investor’s declared residency, nationality, and verified geolocation data.

The platform can use image analysis technology to extract and structure investor data provided in the submitted forms. It will then validate the investor data against trusted external sources (e.g., ID registries), internal eligibility policies (investor age, residency, etc.), and jurisdiction-specific KYC/AML requirements. Qualified accounts are approved automatically, while non-standard and edge cases are routed for manual review.

Verified investors are navigated to an interactive questionnaire that gathers inputs on their investment goals, time horizon, financial capacity, risk appetite, and preferences (e.g., ESG, sector-specific investing). The robo-advisor automatically processes responses, composes investor profiles, and segments investors based on demographic, financial, and behavioral criteria.

The robo-advisor can scrape and screen asset-specific market data in real time or according to a preset schedule. Custom robotic tools can be connected to any chosen market data platforms and liquidity venues and automate investment research across various asset classes (stocks, bonds, ETFs, including fractional shares, crypto tokens, etc.). Screening results are stored for background analysis and can be presented in investor dashboards.

The robo-advisor’s portfolio management engine analyzes investor profiles and investment options and constructs optimal baseline portfolios for each investor, taking into account pre-defined asset selection, diversification, and position limit rules tied to supported investment strategies. Custom advisors can automate conventional approaches like passive indexing and buy & hold, as well as alternatives like smart beta, direct indexing, and factor-based investing.

Discretionary investor portfolios are rebalanced automatically based on pre-configured triggers, e.g., when an asset drifts beyond target bands or when returns for a particular lot decline during a certain period. Custom rebalancing logic can incorporate portfolio- and sleeve-level statistical algorithms that draw on MPT, PMPT, mean-variance optimization, risk parity, Black-Litterman, and other portfolio optimization frameworks.

Investors can configure specific criteria and constraints for the robo-advisor, e.g., to invest only in blue-chip stocks, to prioritize units matching environmental, social, and governance (ESG) goals, or to adhere to particular rebalancing methods. The solution automatically applies each investor’s individual settings when executing portfolio actions.

Trades are executed automatically, with order timing, buy/sell size, venue, and execution algorithm choices guided by preset best execution policies and investor instructions. Prior to trade, the robo-advisor validates each order for accuracy and compliance. It can connect to brokerages and trading venues for instant order placement, execution, and continuous trade monitoring.

The robo-advisor evaluates investment positions for their potential tax implications, taking into account allocation dates, asset cost basis, sale prices, and FX rates. It automatically identifies tax-efficient lots to invest in, constructs portfolios for minimal tax liability, adjusts holdings through tax-aware rebalancing, and generates investor tax forms (e.g., IRS Forms 1099 and 8949). The platform can also recommend the best timing for withdrawal to further reduce the investor’s tax burden.

The platform calculates and tracks key investor portfolio metrics like total portfolio value, time- and money-weighted returns, volatility, standard deviation, Sharpe ratio, and more. Interactive dashboards provide investors with a real-time overview of portfolio KPIs, transactions, and balances (by asset class, period, etc.). Benchmarking tools allow investors to compare their portfolios against market indices and anonymized, aggregated portfolio cohorts.

Custom robo-advisors can support multiple investor account top-up methods, including ACH transfers, cards, digital wallets, and crypto. Deposits and withdrawals are instantly processed via the connected payment gateways. Digital advisory tools can also be configured for automated funding via direct debit, recurring payouts to designated investor accounts, and cash sweep.

Robo-advisory fees are calculated automatically based on the advisory scope and the platform’s charging models (e.g., an annual flat fee, a wrap fee based on assets under management, a percentage of order amount per trade). The solution can be designed to support automated billing and custodian-authorized, scheduled fee auto-withdrawal from investor accounts.

Investors can submit support requests through embedded forms or use a live chat to reach out to support agents. AI agents automatically process support inquiries 24/7 and assist users in handling routine issues. A built-in knowledge base with FAQs and educational content helps users troubleshoot common concerns independently.

​​​​​Configurable dashboards provide robo-advisor admins with insight into investor account activities and essential platform KPIs, such as the number of new investors, the volume of investment deals, AUM, and revenue. The solution supports automated report generation and trend-based analytics to forecast investor behavior and platform performance.

The solution should capture and log all investment-related activity in an audit-ready ledger, which can be centralized or decentralized (e.g., blockchain-based). Custom compliance modules can be designed to continuously vet robo-advisory operations for compliance with internal policies and regulatory rules (e.g., SEC, FINRA, CMA, MiFID II). Any anomalies and policy breaches are immediately flagged and escalated to platform admins.

Investment data and the robo-advisory software are protected via role-based access control, multi-factor authentication, data encryption at rest and in transit, data minimization, data masking, key rotation, automated threat detection, and other robust security mechanisms. Custom solutions can be engineered for compliance with GLBA, SOX, CCPA, NYDFS, SOC1/SOC2, GDPR, PDPL, and other regulations.

Machine learning (ML) can be applied to analyze large volumes of capital market data in real time, spot trends and latent signals (behavioral, risk, market), and forecast any required metrics and events, from time-sensitive technical indicators to long-term asset fundamentals to market-level corrections. The revealed insights can inform rule-based portfolio allocations.

When powered by artificial intelligence (AI), robo-advisors can dynamically analyze investment strategies and suggest refinements. AI engines automate asset correlation and performance attribution analysis, identify return and loss drivers, and can auto-adjust diversification bands, allocations, order timings, and investment styles for higher portfolio profitability.

AI-powered robo-advisors for institutional investors can be designed to sense real-time asset prices across execution venues and spot minor price discrepancies on identical assets, which may not be apparent to human traders. Smart algorithms can immediately enforce arbitrage trades to capitalize on micro-profit opportunities, e.g., buy low on one brokerage and sell high on another.

Robo-advisors can be equipped with large language models (LLMs) to enable natural language software-investor conversation. LLM-powered tools can instantly process textual and voice investor inquiries about portfolio performance, account status, or market data and communicate the requested information in regular human language.

Robo-advisors can include financial modeling tools to evaluate liquidity needs and visualize financial goal fulfillment across the investment cycle. Investors can input yield targets, recurring income, liabilities, and projected spending, simulate time-framed cash flows from investment activities, and assess investment sufficiency for their goals.

A robo-advisor can be built to combine automation with human guidance to cater to investors who need reassurance or want expert input at key decision points. Such software will require live collaboration tools for investors and human wealth advisors, as well as tailored logic for investor routing to human experts based on portfolio size, goals, and risk profile.

Deep-learning fraud detection models can be added to recognize emerging fraud schemes that may go unnoticed by traditional engines, like investor identity deepfakes produced using generative AI. They also help detect model and data tampering and prompt injection attacks across robo-advisory AI components.

Mobile robo-advisory solutions can incorporate biometric user authentication (e.g., facial or fingerprint recognition) to minimize risks of third parties accessing an investor account. Biometric matching can be proposed as a standalone login method or combined with other factors to enhance the protection of investor accounts.