Explainable AI in the hands of financial services
The financial services sector is constantly moving, adapting to new policies and regulatory compliance, and to the ongoing digital transformation.
Rulex puts XAI in the hands of financial services, helping institutions and business users approach current and new challenges.
By providing transparent and explainable data-driven insights, our no-code platform improves key processes from data management to decision-making.
Why financial services choose Rulex
Build trust and credibility
Rulex’s eXplainable AI platform allows financial institutions to work with reliable sources. Its human-centered technology provides users with insights that are transparent and easy to understand. Leaders can trust data and use them for making decisions with great confidence.
Empower business users
Our software is no-code and has a user-friendly interface. It provides business users with explainable results that do not require the help of the IT team to be understood. This means improved workflow management and efficient collaboration between corporate teams.
Rulex’s software enables experts to engage more with strategic tasks by freeing them up from repetitious tasks. It provides experts with quick automated results that they can easily access and work on. Our software unlocks employee potential while increasing professional satisfaction.
Compliance and data governance
Using eXplainable AI to build trust in business data and to empower users is what makes Rulex platform so competitive for compliance. All processes are transparent and explainable; this facilitates the creation of solutions in compliance with customer privacy and industry regulations.
Thanks to eXplainable AI, integrated with legacy rules, our solution can identify human behavior and suggest potential fraud while identifying new patterns in fraudulent operations. We offer vertical solutions for claims for detection – e.g. an integrated anti-fraud solution related to road accidents – and for antimoney laundering – by combining the rules imposed by legislators, domain expert knowledge, and insight emerging from machine learning analysis of data. Two shortlists are created: the first with flagged transactions, as required by law, and the second with potential suspect cases. The results are expressed in clear explainable rules, so fraud analysts can understand the reasoning behind all proposed decisions.
PAD (Payment Account Directive)
Those who work closely with customers must know their client portfolio, monitor it constantly, and simulate possible future scenarios in real time. Thanks to eXplainable AI, experts can see the bigger picture and can therefore make more accurate proposals to their clients.
Lending and credit risk
Using explainable algorithms allows to better understand and monitor all stages of the lending process, from loan origination to early warning signals to management of non-performing loans.
In the initial stage it is crucial to understand the risk associated to debt. Our solution allows institutions to improve the risk validation process thanks to the use of explainable algorithms. By combining traditional methodologies with machine learning logic, institutions can now integrate historical decisions on policy rules and manage approvals and exceptions with improved precision.
Marketing & commerce
Rulex outlines customer profiles and prospects in a clear and simple way, so sales experts and marketing teams can better manage customer relationships.
Cross-selling is one of the biggest opportunities for sellers. Everyone knows that it is easier to sell products to existing customers than to attract new ones. Why? The customer trusts you, and knowing his preferences means you can offer the right product at the right time. Thanks to our eXplainable AI and augmented decisioning, we can support your marketing departments in offering the best products to the right people.
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What businesses really need is not so much predictive algorithms, but a solution that helps them take decisions: a Digital Decision platform which combines artificial intelligence, heuristic rules and explainability.