Industry
Private banks, wealth managers and asset managers, where AI supports advisers, research, portfolio operations and client reporting.
26 organizations in 9 countries run these use cases in public. 61% of those 33 deployments disclose a measurable outcome.
An AI first line contact centre agent answers inbound customer contact on phone, chat and messaging, resolving general and routine questions end to end in the customer's own language. It routes everything complex, sensitive or regulated to the right human team, with the context attached.
AI source of wealth diligence is an AI agent that reads a prospective private client's documents and extracts how their wealth was built, for private banking compliance teams. It also corroborates that account, checks plausibility against benchmarks and external sources, and drafts the source of wealth and enhanced due diligence narrative for the relationship manager and compliance analyst, who decide on the risk rating and the relationship.
AI analysis of earnings calls and company text reads earnings call transcripts, filings and other unstructured disclosures at scale to produce an investment signal for a portfolio manager or analyst. The underlying large language model, either fine tuned or prompted within a structured scoring framework, scores a company on a dimension such as business quality or exposure to a market theme, or forecasts how markets will react to what was said, so the signal is systematic and repeatable to weigh alongside traditional quantitative data.
AI deal sourcing and due diligence is an AI assistant that screens the market for acquisition or investment targets and speeds up due diligence for a deal team. It builds company profiles, reads data room documents, extracts key terms and risks, and drafts the investment or diligence memo, for the team to verify and decide.
A digital onboarding assistant is a customer facing AI that guides a new applicant, a person or a small merchant, through opening a digital account, card or relationship. It collects and checks identity and supporting documents, orchestrates the know your customer and anti money laundering checks, prefills what it can and sends only the unclear cases to a human reviewer with a summary. The ownership research for complex corporate clients is a separate back office job.
An AI assistant for goal based financial planning is an AI assistant that turns a client's goals into projections and what if scenarios using a rules based planning engine. It explains the trade offs in plain language and prepares the plan for an advisor to validate, with every assumption disclosed and reproducible.
A suitability assessment assistant is an AI assistant that checks whether a proposed product or portfolio fits a client's risk tolerance, objectives, knowledge, experience and financial situation. It checks this against the firm's rules, flags mismatches, and drafts the suitability rationale and report for the advisor to confirm, while hard rule failures are decided by deterministic checks, not by the model.
AI Shariah compliance screening is an AI assistant that checks Islamic financing contracts, deal structures and investments for Shariah compliance risks such as riba and gharar, for compliance teams. It also flags exposure to prohibited activities, retrieves the relevant standards and fatwas, and drafts the Shariah review documentation. The Shariah board keeps sole authority over any ruling.
An AI copilot that helps relationship managers, mainly in corporate and commercial banking, prepare for client meetings and write up call reports afterwards. It builds a briefing pack from filings, news, internal notes, product holdings and upcoming maturities, then turns the banker's notes into a structured call report and CRM update. Unlike a meeting notetaker, it centres on credit and cross sell context, not just the conversation; wealth advisor tools that also prepare meetings overlap with it, and the banker reviews every output.
AI marketing content and compliance copilot drafts campaign copy and checks it against advertising rules before a human approves it for publication. It writes campaign copy, product explainers and social posts on brand and in the customer's language from approved product facts, then runs a first pass compliance check against advertising rules and required disclosures, flagging unsupported claims and missing warnings before a human in marketing compliance approves publication.
AI model risk validation is a copilot that supports independent review of a bank's models, used by a validation function, an external tester or a supervisor. It checks model documentation against the model risk standard, generates and scores challenger tests (for generative AI, often with an LLM as a judge calibrated against human experts), watches production models for drift, and drafts and consistency checks the validation report. An accountable validator owns every conclusion.
Enterprise knowledge search is an AI assistant that lets any employee ask a question in plain language and get a synthesized answer from the organization's own documents. It draws the answer from policies, procedures, product manuals and research, with citations to the source documents, and only from documents the employee is allowed to see.
AI account servicing execution is AI that reads and acts on servicing requests landing in operations queues, such as address or beneficiary changes, for back office staff. It checks each request against policy and entitlements, then prepares or makes the change, such as mandate changes, standing instructions, reissues, payoff and reference letters and loan maintenance, in core systems under dual control.
AI for outbound notice drafting writes the letters and notices operations must send at scale, such as arrears notices or decline letters. It also covers complaint responses, servicing confirmations and product change notices, from case data and approved templates and clauses, in the customer's language, for a person to approve where the notice is regulated.
AI for ledger and payment reconciliation matches financial records to each other and flags the exceptions for a human to review. It matches entries across nostro and vostro statements, card and scheme settlement files, the general ledger and suspense accounts, proposes the matches and clearing journals, and routes only the genuine breaks to an operator with a plain language explanation.
AI market abuse surveillance triage helps surveillance analysts triage market abuse and conduct alerts such as spoofing, layering, wash trades, ramping and insider dealing. It gathers the trade, order, news and communications context, explains in plain language what triggered each alert, and drafts the investigation narrative for the analyst to disposition.
AI PEP and adverse media screening continuously scans news, court records, registries and other open sources for negative information and political exposure tied to customers, counterparties and beneficial owners. It works in many languages, discards look alikes, and summarises the credible risk for the analyst with the sources attached.
Perpetual KYC is AI that keeps each customer's due diligence file current by replacing calendar driven reviews with continuous, event driven refreshes. It watches for trigger events such as an ownership, address or behaviour change or a new adverse finding, refreshes the file automatically where it can, and involves an analyst only when something material changes. The risk rating and the first file for a new business client are separate use cases.
Settlement fail prediction is AI that scores each pending securities settlement instruction for its likelihood of failing and names the probable cause. The cause can be an unmatched instruction, wrong settlement details, or a lack of securities or cash. It then helps operations teams work the exceptions and counterparty queries before the intended settlement date, so fewer trades fail and fewer late settlement penalties are paid.
Portfolio reporting and commentary is AI that drafts each client's periodic portfolio report and commentary in plain language, for wealth and asset managers. The narrative covers performance, attribution, what drove returns, positioning and outlook, written in the client's language, where every figure comes from the portfolio system of record and a reviewer approves the text before delivery.
An AI knowledge assistant for wealth advisors and relationship managers answers their questions in seconds from the firm's own research, house view, product documentation and policies. Every answer links to the source document, so the advisor can check it before using it with a client.
An AI notetaker that turns a wealth advisor's client meeting into a file note, follow up message and CRM record the firm needs to evidence its advice. The meeting is recorded with the client's consent, and the notetaker drafts a structured note with the client's goals, circumstances, decisions and action items, then writes it into the CRM once the advisor approves it; unlike a general meeting summarizer, its output becomes part of the regulated client record.
AI next best action for advisors is an engine for wealth advisors, not customers, that scans an advisor's whole book and surfaces a short, ranked list of client specific prompts. Prompts include idle cash, a maturing deposit, a concentration to review, a life event or an early sign of attrition, each with the reasoning and data behind it, for the advisor to act on or dismiss.
Portfolio drift monitoring and rebalancing is AI that continuously checks each client portfolio against its mandate or model and prepares a rebalancing proposal, for advisors and portfolio managers. It detects drift beyond agreed bands and prepares a tax aware, low turnover proposal with its rationale, which an advisor or portfolio manager approves before any trade is placed.
Regulatory horizon scanning is AI that continuously reads publications from the regulators and standard setters an organization answers to and classifies each item by relevance and urgency. It breaks new rules into individual obligations and maps them to the internal policies and controls that meet them, so compliance owners see what changed and where the gaps are.
Estate and trust document drafting is an AI assisted workflow for wealth advisors that extracts and summarizes what a client's existing will, trust and power of attorney documents say. It flags where documents disagree or contain an error, for an advisor to review. Some platforms in this category also fill an attorney reviewed, jurisdiction specific template with the client's facts to produce a new draft estate document; whether that filling step itself runs on a model, or is document assembly outside the AI feature, is a vendor by vendor question the evidence on this page does not settle.
Investment research summarization is an AI assistant that condenses long research reports, overnight market moves and the house view into short, sourced briefings for advisors and analysts. It answers "what is our view on X" on demand and adapts approved research for different client segments and languages, with every figure traced to the original research.
Dynamic customer risk rating is explainable machine learning that computes and continuously updates each customer's money laundering risk rating itself, from due diligence data, products, geography, behaviour and screening results. It also shows which factors drive the rating and when enhanced due diligence is warranted.
An internal audit copilot is AI that helps internal auditors plan and write up audits, from drafting planning materials to summarising evidence and drafting findings. It drafts planning memos and document request lists from prior audits, summarises large evidence sets, builds risk and control matrices from policies and process documents, and drafts findings and reports, with every statement traceable to evidence and a qualified auditor accountable for every conclusion.
Free PDF playbook
29 use cases with deployments, value, playbooks and governance, in one document for your team.
Computed from the 33 public deployments behind these use cases at wealth and asset management organizations. Numbers update with every checked record.
115 public deployments at 105 organizations outside wealth and asset management run these use cases too. They are not counted in the numbers above; each use case page shows them.
