The European fintech landscape is abuzz with a fervent hunt for AI talent, as leading fintech unicorns are aggressively recruiting to leverage the power of artificial intelligence. Recent data reveals that out of the region’s top 20 most valuable fintech unicorns, 14 actively seek AI professionals, with a strong focus on enhancing customer services and bolstering anti-fraud measures. AI’s ascendancy in the fintech realm is evidenced by the fact that it has swiftly overtaken other tech sectors, claiming the throne of the most popular and hyped-up domain.

Infiltrating fintech with AI’s Growing Influence

AI has unleashed a wave of innovation in the fintech sector, prompting neobanks and payments companies to embrace its potential wholeheartedly. The primary areas of AI integration include customer service improvement and fraud detection. By harnessing machine learning capabilities, these fintech players invest significantly in technologies that promise to enhance operational efficiency and provide a competitive edge. However, the fruition of these investments remains to be seen, as AI’s true impact is still unfolding.

AI roles at a premium of salaries up to £140k

The demand for AI expertise is so high that salaries for AI roles in the European fintech scene are reaching staggering heights, with base pay soaring up to £140k. Glassdoor reviews indicate that these roles command substantial remuneration due to the specialized skill sets they require. While the fintech industry is still in its nascent stage of AI recruitment, job boards predict that within six months, the most common AI roles and their average salaries will be established, providing a comprehensive snapshot of the sector’s AI talent landscape.

Leading fintech on the prowl for AI talent

The top European fintech unicorns are leaving no stone unturned in their quest to secure AI talent. Here’s a rundown of some of the frontrunners:

Top European fintech players and Their AI Endeavors

1. SumUp leads the charge

With 10 open AI roles, SumUp spearheads the drive for AI talent. The roles predominantly encompass data analysts, data engineers, and data scientists. The company’s AI team currently boasts 25 members, and their efforts are concentrated on curbing fraud, detecting money laundering, and risk assessment. SumUp also delves into generative AI, employing tools like GitHub Copilot and genAI assistants for advanced analytics and internal documentation searches.

2. Revolut for AI in action

Revolut is fervently recruiting seven data scientists to bolster its AI team, which already comprises 300 members. The roles are spread across different units, including Fincrime Data Science, focused on combating fraud, and Computer Vision Engineers, striving to detect fraudulent activity by leveraging AI models. The Credit and Risk Data Science team also pioneers models for assessing credit and investment risks.

3. Monzo for delving into data

Monzo is seeking AI expertise for its data team, with seven open roles. The company’s AI team size remains undisclosed, but its application of machine learning spans customer experience prediction to auto-completing search queries, thereby enhancing user engagement.

4. Starling

Though specific details are pending, Starling is making strides in AI with a current AI team of 35 professionals. Its data science team is diligently working on enhancing its account application process and in-app features through AI-driven solutions.

5. Qonto for anti-risk focus

Qonto has posted a single open role for a machine learning engineer, signaling its intent to expand its AI endeavors. Currently operating around 10 machine learning models for anti-risk, anti-money laundering, and fraud detection purposes, Qonto strives to automate matching inbound transactions with generated invoices to streamline financial management for its business clientele.

6. Zepz for fighting financial fraud

With one open AI role, Zepz utilizes machine learning models to combat fraud and predict financial time series and churn rates. The company employs a tech stack that includes Airflow, Fivetran, DBT, BigQuery, and BigTable, with a core emphasis on Python.

7. OakNorth for a holistic AI adoption

OakNorth boasts a data science team with several dozen members. It harnesses AI models for customer interactions, industry forecasting, risk assessment, and more, contributing to its holistic approach to AI implementation.

8. Mollie for embracing AI’s future

Mollie’s founder, Adriaan Mol, envisions an AI-infused future, and the company strives to stay ahead. While details on their current AI team and applications remain scarce, the company’s bullish outlook on AI’s potential is evident.

9. Checkout.com for combatting fraud through AI

Checkout.com is seeking a machine learning engineer to bolster its fraud detection efforts. With a history of AI-driven product launches, the company is focused on providing near-real-time transaction fraud predictions for its merchants.

10. N26 for prioritizing banking security

N26’s AI development is centered on banking security. Their machine learning-powered fraud probability models actively detect suspicious customer behavior, significantly reducing fraud and money laundering cases.

11. Klarna for AI’s hyper-personalized future

Klarna’s AI efforts extend to hyper-personalization and product recommendations, as it forays into the all-in-one shopping app arena. The company envisions a future involving AI-driven personalization, AI shopping assistants, and innovative shopping experiences.

12. Trade Republic for data platform advancements

Trade Republic’s data platform and ML model applications remain under wraps, but the company’s pursuit of a senior data engineer indicates a commitment to leveraging data-driven insights.

13. Wefox for prioritizing broker productivity

Though specific details are limited, Wefox’s AI team focuses on boosting insurance broker productivity.

14. GoCardless for AI-enhanced payment recovery

GoCardless employs AI to enhance its “GoCardless Success+” feature, aiding businesses to recover failed payments.

The European fintech realm’s rapid embrace of AI technology is palpable, as the industry’s top players clamor for AI talent. The surge in recruitment efforts, accompanied by substantial salaries, underscores the pivotal role AI is poised to play in redefining the fintech landscape. With applications ranging from fraud detection to customer experience enhancement, AI’s integration into fintech promises efficiency and innovation, cementing its status as the tech sector to watch in the region.

The European fintech landscape is abuzz with a fervent hunt for AI talent, as leading fintech unicorns are aggressively recruiting to leverage the power of artificial intelligence. Recent data reveals that out of the region’s top 20 most valuable fintech unicorns, 14 actively seek AI professionals, with a strong focus on enhancing customer services and bolstering anti-fraud measures. AI’s ascendancy in the fintech realm is evidenced by the fact that it has swiftly overtaken other tech sectors, claiming the throne of the most popular and hyped-up domain.

Infiltrating fintech with AI’s Growing Influence

AI has unleashed a wave of innovation in the fintech sector, prompting neobanks and payments companies to embrace its potential wholeheartedly. The primary areas of AI integration include customer service improvement and fraud detection. By harnessing machine learning capabilities, these fintech players invest significantly in technologies that promise to enhance operational efficiency and provide a competitive edge. However, the fruition of these investments remains to be seen, as AI’s true impact is still unfolding.

AI roles at a premium of salaries up to £140k

The demand for AI expertise is so high that salaries for AI roles in the European fintech scene are reaching staggering heights, with base pay soaring up to £140k. Glassdoor reviews indicate that these roles command substantial remuneration due to the specialized skill sets they require. While the fintech industry is still in its nascent stage of AI recruitment, job boards predict that within six months, the most common AI roles and their average salaries will be established, providing a comprehensive snapshot of the sector’s AI talent landscape.

Leading fintech on the prowl for AI talent

The top European fintech unicorns are leaving no stone unturned in their quest to secure AI talent. Here’s a rundown of some of the frontrunners:

Top European fintech players and Their AI Endeavors

1. SumUp leads the charge

With 10 open AI roles, SumUp spearheads the drive for AI talent. The roles predominantly encompass data analysts, data engineers, and data scientists. The company’s AI team currently boasts 25 members, and their efforts are concentrated on curbing fraud, detecting money laundering, and risk assessment. SumUp also delves into generative AI, employing tools like GitHub Copilot and genAI assistants for advanced analytics and internal documentation searches.

2. Revolut for AI in action

Revolut is fervently recruiting seven data scientists to bolster its AI team, which already comprises 300 members. The roles are spread across different units, including Fincrime Data Science, focused on combating fraud, and Computer Vision Engineers, striving to detect fraudulent activity by leveraging AI models. The Credit and Risk Data Science team also pioneers models for assessing credit and investment risks.

3. Monzo for delving into data

Monzo is seeking AI expertise for its data team, with seven open roles. The company’s AI team size remains undisclosed, but its application of machine learning spans customer experience prediction to auto-completing search queries, thereby enhancing user engagement.

4. Starling

Though specific details are pending, Starling is making strides in AI with a current AI team of 35 professionals. Its data science team is diligently working on enhancing its account application process and in-app features through AI-driven solutions.

5. Qonto for anti-risk focus

Qonto has posted a single open role for a machine learning engineer, signaling its intent to expand its AI endeavors. Currently operating around 10 machine learning models for anti-risk, anti-money laundering, and fraud detection purposes, Qonto strives to automate matching inbound transactions with generated invoices to streamline financial management for its business clientele.

6. Zepz for fighting financial fraud

With one open AI role, Zepz utilizes machine learning models to combat fraud and predict financial time series and churn rates. The company employs a tech stack that includes Airflow, Fivetran, DBT, BigQuery, and BigTable, with a core emphasis on Python.

7. OakNorth for a holistic AI adoption

OakNorth boasts a data science team with several dozen members. It harnesses AI models for customer interactions, industry forecasting, risk assessment, and more, contributing to its holistic approach to AI implementation.

8. Mollie for embracing AI’s future

Mollie’s founder, Adriaan Mol, envisions an AI-infused future, and the company strives to stay ahead. While details on their current AI team and applications remain scarce, the company’s bullish outlook on AI’s potential is evident.

9. Checkout.com for combatting fraud through AI

Checkout.com is seeking a machine learning engineer to bolster its fraud detection efforts. With a history of AI-driven product launches, the company is focused on providing near-real-time transaction fraud predictions for its merchants.

10. N26 for prioritizing banking security

N26’s AI development is centered on banking security. Their machine learning-powered fraud probability models actively detect suspicious customer behavior, significantly reducing fraud and money laundering cases.

11. Klarna for AI’s hyper-personalized future

Klarna’s AI efforts extend to hyper-personalization and product recommendations, as it forays into the all-in-one shopping app arena. The company envisions a future involving AI-driven personalization, AI shopping assistants, and innovative shopping experiences.

12. Trade Republic for data platform advancements

Trade Republic’s data platform and ML model applications remain under wraps, but the company’s pursuit of a senior data engineer indicates a commitment to leveraging data-driven insights.

13. Wefox for prioritizing broker productivity

Though specific details are limited, Wefox’s AI team focuses on boosting insurance broker productivity.

14. GoCardless for AI-enhanced payment recovery

GoCardless employs AI to enhance its “GoCardless Success+” feature, aiding businesses to recover failed payments.

The European fintech realm’s rapid embrace of AI technology is palpable, as the industry’s top players clamor for AI talent. The surge in recruitment efforts, accompanied by substantial salaries, underscores the pivotal role AI is poised to play in redefining the fintech landscape. With applications ranging from fraud detection to customer experience enhancement, AI’s integration into fintech promises efficiency and innovation, cementing its status as the tech sector to watch in the region.