Financial services are absorbing new technologies at an accelerating pace each year. Artificial intelligence in the back office, autonomous agents capable of managing portfolios, alternative data integrated into risk models: technical finance is no longer limited to price charts. It now encompasses software infrastructure, automated compliance, and real-time decision-making tools.
Autonomous agents and decision-making AI in asset management
You have already seen a chatbot respond to a question about your bank balance. Now imagine a program that does not just respond but acts: it monitors a portfolio, detects an anomaly on a security, adjusts a position, and generates a report for the manager. This is what is called an autonomous agent in finance.
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Unlike a traditional trading algorithm that follows fixed rules, the autonomous agent adapts its behavior based on the context. It combines multiple data sources (market flows, news, macroeconomic indicators) to formulate a recommendation or execute a transaction.
The deployment of these agents remains regulated. Regulators require that each decision can be explained retrospectively, which hinders opaque models. Institutions following the news on Finance Technique find that algorithmic transparency is becoming a selection criterion for institutional investors.
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Financial planning also benefits from generative AI. An advisor can submit a client’s profile to a language model that produces several allocation scenarios. The advisor retains control over the final decision, but the analysis time is reduced from several hours to just a few minutes.
Fintech investment cycle: selectivity prevails over volume
The global fintech market has gone through three years of funding contraction. In 2025, a clear inflection occurred: the total funding volume rose to about $116 billion, compared to $95.5 billion the previous year. The paradox is that the number of transactions continued to decline, reaching an eight-year low.
Why this discrepancy? Investors are concentrating their tickets on more mature deals, with proven recurring revenues and solid regulatory compliance. Seed rounds based solely on a pitch deck are no longer sufficient.
KPMG documented this trend: the first half of 2025 represents the weakest half-year in five years in cumulative amount, with $44.7 billion for 2,216 operations. Fewer deals, but larger tickets – this signals a market shifting from a quantity logic to a quality logic.
For French companies in the sector, this selectivity has direct consequences:
- Fintechs that have not yet reached profitability must demonstrate a credible path to financial balance to raise funds
- Strategic acquirers (banks, insurers) regain the upper hand in buyout negotiations against more realistic valuations
- The best-funded segments are those related to regulatory compliance (regtech) and data management, rather than consumer neobanks
Alternative data and real-time risk scoring
Traditional risk analysis relies on balance sheets, credit histories, and ratings published by agencies. These data share a common flaw: they look in the rearview mirror.
Alternative data changes the game. This refers to unconventional information: satellite images of shopping center parking lots to estimate foot traffic, anonymized geolocation data, transaction flows on payment platforms, or signals derived from a company’s web traffic.
A scoring model powered by this data detects weak signals several weeks before traditional indicators. For example, a sudden drop in traffic on a borrower’s e-commerce site can alert a lender well before the publication of quarterly results.
The integration of these flows raises governance questions. Companies must verify the provenance of the data, its compliance with GDPR, and the statistical robustness of the correlations used. Without a data governance framework, the model loses all regulatory credibility.
Back-office automation and regulatory compliance
Transaction processing, accounting reconciliation, fraud detection: these tasks mobilize entire teams in banks and asset management companies. AI automation significantly reduces manual errors and processing times.
The next step is to move from supervised automation to real-time risk assessment. A system that detects a suspicious transaction no longer simply sends an alert: it blocks the operation, queries regulatory databases, and generates the corresponding regulatory report, all in a matter of seconds.
Regtech (regulatory compliance technologies) are among the best-funded segments at the moment. Their promise: to transform compliance from a cost center into a smooth process integrated with existing systems. For finance departments, the gain is not only measured in savings but also in reduced risk of sanctions.
- Automated accounting reconciliation processes millions of lines without human intervention, with an error rate lower than manual processes
- Continuous transaction monitoring replaces sampling controls, which allowed anomalies to slip through
- Regulatory reports are automatically generated in the format required by supervisory authorities, reducing reporting delays
Sustainable finance and green structured products: beyond the label
Labelled sustainable financial products are multiplying, but technical finance provides a different perspective on this market. Measuring the real impact of a green investment requires granular data, not just a label or a statement of intent.
Next-generation ESG analysis tools cross-reference the declarative data of issuers with independent sources (emissions measured by satellite, energy consumption of industrial sites, media controversies). The gap between the two reveals the most blatant cases of greenwashing.
Structured products linked to climate criteria are gaining ground in France. Their mechanics combine a conditional yield (linked to the performance of a stock index, for example) and an impact commitment verified by a third party. The structured products market has indeed reached record levels in recent months.
The convergence of alternative data, AI, and regulatory compliance shapes a technical finance where technology does not replace human judgment but provides faster and more reliable verification tools. Institutions investing in this software infrastructure are gaining an edge over those that merely digitize existing processes.