How might we use emerging technologies to reliably distinguish genuine documentation from fabricated, manipulated or AI‑generated materials and apply this intelligence to detect manipulation and reduce false positives in fraud controls, while maintaining customer trust and supporting ongoing confidence in customer identity?​

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Background:​

Building societies, banks, credit unions and other legal and professional institutions handle large volumes of critical documents across underwriting, conveyancing, onboarding and ongoing account management throughout the customer lifecycle. These include identity evidence, income verification, property information and supporting case files, often submitted through multiple channels and in inconsistent formats. This creates operational pressure and gives fraudsters opportunities to exploit gaps using increasingly sophisticated fabricated, altered or AI‑generated materials. At the same time, legitimate customers can be slowed down or incorrectly flagged due to poor‑quality scans, formatting issues or minor discrepancies that trigger unnecessary alerts that drive manual review effort, delays and friction.​

Firms need smarter ways to detect manipulation with high accuracy, reduce false positives and maintain customer trust, while also strengthening protection against synthetic identities, deepfake‑enabled impersonation and attacks on verification infrastructure.​

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We are interested in solutions that may include:​

• AI‑driven document forensics to authenticate materials and detect manipulation​

• Detection of synthetic or AI‑generated content across images, PDFs and scanned documents​

• Identification of synthetic identities or deepfake‑enabled impersonation attempts​

• Context‑aware risk scoring that separates genuine customer mistakes from malicious intent​

• Reducing false positives through explainable anomaly classification and triage recommendations​

• Continuous identity assurance beyond the initial verification event​

• Resilient verification infrastructure that can withstand direct attack or manipulation​

• Seamless integration into onboarding, underwriting, conveyancing, pension administration and case‑handling workflows​

• Capability to operate across diverse document types, formats and submission channels​

How might affordable, intelligence‑led digital identity and fraud‑control capabilities help credit unions enhance digital onboarding, strengthen fraud resilience and better protect vulnerable members, while preserving the trusted community‑centred service that defines the sector?​

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Background:​

Credit unions are increasingly supporting members through digital channels across onboarding, lending and ongoing account management. These journeys involve identity checks, eligibility assessments and behavioural interactions that have traditionally relied on personalised, face‑to‑face processes. As more of this activity moves online, institutions must ensure that trusted, member‑focused verification can be delivered consistently and safely in digital environments. Digital onboarding can be exposed to impersonation attempts, synthetic identities and inconsistent verification outcomes when identity checks are not standardised or supported by accessible digital tools. At the same time, staff need adaptable, context aware fraud controls that reflect the scale and products of credit unions, enabling confident, real‑time decisions without creating friction for genuine members. Frontline teams also work closely with individuals who may be vulnerable to scams or coercion, and intuitive detection alone is no longer sufficient as fraudsters adopt more sophisticated behavioural manipulation techniques. Credit unions therefore need smarter, proportionate ways to enhance identity assurance, strengthen behavioural and scam‑risk detection and support consistent decision‑making across digital journeys. Solutions should augment, not replace the human touch, integrating seamlessly with existing systems, supporting vulnerable or digitally excluded members and enabling institutions to deliver safe, modern digital experiences while maintaining customer trust.​

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We are interested in solutions that may include:​

• Digital identity verification suitable for loans and hybrid onboarding​

• Tools to detect synthetic identities, manipulated documents, or deepfake‑enabled impersonation​

• Continuous identity assurance for account changes or loan top‑ups​

• Risk‑tiered onboarding and loan‑approval workflows​

• Lightweight, plug‑and‑play fraud controls that adapt to member behaviour​

• Real‑time decisioning tools that flag anomalies or high‑risk actions​

• Scam‑susceptibility indicators or behavioural‑risk signals​

• Behavioural nudges during loan applications, withdrawals, or digital interactions​

• Member‑facing prompts or education that build fraud awareness​

How might firms move beyond binary allow/block decisions by applying dynamic, graduated controls that balance speed, customer protection and commercial pressures, enabling proportionate friction based on real‑time behavioural and transactional risk signals?​

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Background:​

Fraud‑control decisions are often binary, relying on full approvals or complete blocks that can either allow harmful transactions or create unnecessary disruption for genuine customers. As fraudsters adapt quickly and exploit moments of urgency, financial institutions and legal and professional services firms need more flexible ways to respond to risk in real time. Customers also expect fast, low‑friction journeys, and excessive intervention can damage trust, increase abandonment and strain operational teams.​

Graduated controls offer a more adaptive approach. By combining behavioural, transactional and contextual signals, firms can apply proportionate friction such as partial freezes, dynamic limits, stepped‑up verification or temporary restrictions only when risk indicators justify it. This enables firms to slow down suspicious activity without fully interrupting legitimate customer behaviour.​

To achieve this, institutions need real‑time decisioning, consistent cross‑channel intelligence and controls that adjust automatically as risk changes. They must also balance commercial pressures for speed with protection obligations, ensuring interventions remain fair, explainable and aligned with customer expectations.​

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We are interested in solutions that may include:​

• Dynamic, real‑time risk‑assessment models that support proportionate, graduated controls. ​

• Partial freezes, dynamic limits or temporary restrictions that slow high‑risk activity without blocking genuine behaviour. ​

• Behavioural and contextual‑signal fusion that strengthens decisioning across channels. ​

• Proportionate friction mechanisms that help customers pause and reflect during high‑risk moments. ​

• Controls that adapt automatically as risk changes, balancing speed, protection and commercial performance. ​

• Approaches that ensure graduated decisions remain explainable, fair and aligned with regulatory expectations. ​

• Solutions that integrate smoothly with existing fraud‑control systems and customer journeys.​

How might legal and professional services firms and financial institutions ensure strong identity integrity across distributed access channels such as service desks, relationship management teams and duty partner or out‑of‑hours support where potential gaps in HR verified checks and authorisation workflows may create opportunities for impersonation and urgent request social engineering, while still enabling staff to access sensitive systems quickly and securely to maintain operational continuity?​

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Background:​

Legal firms and financial institutions rely on distributed, multi‑channel support across phone, email, messaging platforms and remote portals, often at times when HR systems, identity verification tools or managerial authorisation workflows may not be accessible. This leaves service desks, relationship management teams and duty partner or out‑of‑hours support relying on trust, caller familiarity or partial records to validate identity. Attackers exploit these gaps through authoritative impersonation, synthetic personas, deepfake voice calls and urgent request social engineering, targeting high risk workflows such as matter management systems, payment platforms and customer account access. As operations become more flexible and decentralised across both sectors, inconsistencies in verification practices create vulnerabilities that fraudsters probe systematically. Firms must balance timely access for legitimate staff with strong identity assurance, reducing reliance on subjective judgement and ensuring consistent, secure and auditable verification across every channel.​

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We are interested in solutions that may include:​

• Real time identity assurance across phone, email, messaging, Teams and remote portals, ensuring consistent verification processes reducing reliance on trust, familiarity or seniority. ​

• Secure delegated or assisted verification for account unlocks, MFA resets and access requests, particularly when managerial approval or HR systems are unavailable.​

• Detection of authoritative impersonation, urgent request social engineering and synthetic personas supported by deepfake voice calls and manipulated media, with heightened scrutiny for high profile or sensitive access attempts. ​

• Behavioural, device, contextual and compliance‑based signals to assess identity confidence, incorporating user role, device compliance, location & request sensitivity.​

• Adaptive access controls that adjust verification requirements based on risk and context to balance operational continuity with strong identity assurance.​

• Low friction access for legitimate staff combined with strong protection for matter management systems, payment platforms, customer account workflows and other sensitive environments. ​

• Integration with enterprise identity, workflow and device‑management platforms to automate controls, approvals, evidence capture and auditable identity decision records aligned to client assurance requirements and ISO 27001 compliance.​

How might legal and professional services firms and financial institutions ensure strong identity integrity across distributed access channels such as service desks, relationship management teams and duty partner or out of hours support models, where potential gaps in HR verified checks and authorisation workflows may create opportunities for impersonation and urgent request social engineering, while still enabling staff to access sensitive systems quickly and securely to maintain operational continuity?​

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Background:​

Legal firms and financial institutions operate through distributed, multi-channel access models where internal teams support staff across phone, email, Teams, messaging platforms, and remote access portals. These interactions often occur at times or in contexts when standard HR systems, identity verification tools or managerial authorisation workflows may not be accessible. As a result, service desks, client relationship managers and duty partner or out of hours arrangements frequently rely on trust, caller familiarity or partial records to validate identity and grant access. Fraudsters can exploit these gaps. Attackers may attempt to impersonate partners, senior fee earners or high privilege banking staff, claiming urgent need for access to matter management systems, client files, payment authorisation platforms, customer account systems or other high-risk workflows. They use authoritative impersonation, synthetic personas, deepfake voice calls and urgent request social engineering to pressure staff into bypassing controls. Distributed channels, especially those mediated by internal teams, become high trust and high-risk pathways where identity integrity can be compromised. As operations become more flexible and decentralised across both sectors, inconsistencies in verification practices create vulnerabilities that attackers probe systematically. Yet firms must still support legitimate staff who need timely access to perform essential duties. This creates a tension between operational continuity and identity assurance. Both sectors require adaptive and context aware identity integrity that works across distributed access channels, detecting impersonation and anomalous behaviour in real time while enabling secure and controlled access for authorised staff. Firms need ways to reduce dependency on internal teams making judgement calls based on requester familiarity, and instead ensure consistent, secure and auditable identity verification across every channel.​

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We are interested in solutions that may include:​

• Real time identity assurance across phone, email, messaging, Teams and remote portals, ensuring consistent verification processes reducing reliance on trust, familiarity or seniority. ​

• Secure delegated or assisted verification for account unlocks, MFA resets and access requests, particularly when managerial approval or HR systems are unavailable.​

• Detection of authoritative impersonation, urgent request social engineering, synthetic personas & deepfake voice calls, with heightened scrutiny for high profile or sensitive access attempts. ​

• Behavioural, device, contextual and compliance‑based signals to assess identity confidence, incorporating user role, device compliance, location & request sensitivity.​

• Adaptive access controls that adjust verification requirements based on risk and context to balance operational continuity with strong identity assurance.​

• Low friction access for legitimate staff combined with strong protection for matter management systems, payment platforms, customer account workflows and other sensitive environments. ​

• Integration with enterprise identity, workflow and device‑management platforms to automate controls, approvals, evidence capture and auditable identity decision records aligned to client assurance requirements and ISO 27001 compliance.​

How might firms use behavioural intelligence, life‑event signals and contextual risk indicators to identify customers at heightened susceptibility to scams or coercion, enabling proactive, ethical and privacy‑preserving interventions that prevent harm before it occurs?​

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Background:​

Fraud prevention has traditionally focused on spotting malicious transactions or identifying suspicious activity after harm has occurred. Yet a growing share of losses now comes from scams, coercion and social‑engineering techniques that exploit customer psychology rather than system weaknesses. Criminals target people experiencing life events, emotional stress or financial pressure and use personalised manipulation to persuade them to authorise payments, disclose credentials or override security controls.​

Customers who are digitally less experienced, socially isolated or navigating significant life changes can be more vulnerable to persuasive fraud narratives. These risks often surface through subtle behavioural cues, shifts in interaction patterns or changes in digital engagement. Frontline staff may notice hesitation, scripted responses or unusual urgency, but these indicators are difficult to capture consistently across digital channels, contact centres and in‑person interactions.​

Firms need ways to identify heightened susceptibility early, using behavioural intelligence, contextual signals and ethically designed analytics that respect privacy and avoid stigmatisation. Shifting from reactive detection to proactive protection, applying supportive friction, enhanced monitoring or tailored interventions only when risk signals justify it.​

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We are interested in solutions that may include:​

• Behavioural‑intelligence models that surface early indicators of scam susceptibility, coercion or manipulation across digital, contact centre and in‑person interactions. ​

• Life‑event and contextual‑risk analytics that highlight periods when customers may be more vulnerable to persuasive fraud narratives.​

• Proactive, ethical interventions such as supportive friction, enhanced monitoring or tailored messaging that help customers pause and avoid harm. ​

• Privacy‑preserving techniques that detect risk without intrusive monitoring or stigmatising specific groups. ​

• Tools that help frontline staff recognise behavioural red flags and confidently escalate concerns during high‑risk interactions​

• Cross‑channel behavioural‑signal fusion so indicators observed in one environment strengthen protection in another. ​

• Solutions that integrate smoothly with existing journeys, providing protection for vulnerable customers without adding unnecessary friction for genuine activity.​