An interesting dicussion that the Credit and Collections Technology Think Tank for 2024. Certainly some bit themes around data, transparency of process and honesty in communication, all to build trust with customers over the longer term.
Regulation and regulatory compliance was a big topic, reflecting the volume of change underway. Likely to continue as a theme into 2025.
The Global Collections Benchmarking study is also out. If you would like a copy of the 2023 report and would like to take part in 2024, click on the QR code/link here.
Key takeaways from each session
Session 1: Credit and Collections Risks
- The ongoing cost-of-living crisis has led to financial strain and higher arrears, especially in council tax and priority debts.
- Some consumers are adapting to financial pressures by changing spending habits or using alternative credit options such as “buy now, pay later.”
- Persistent regulatory developments are adding administrative costs and complexity, with a record number of FCA publications this year.
- The regulatory approach, particularly through the Consumer Duty principles, is intended to protect consumers but is perceived as sometimes stifling flexibility in the credit sector.
- New regulatory expectations focus on consumer vulnerability and financial difficulty, impacting both compliance strategies and operational costs.
- Data and real-time analytics are essential for effectively managing customer engagement, especially for understanding consumer affordability and vulnerability.
- Open banking is enabling lenders and collectors to assess consumers’ real-time financial situations, aiding in compliance and enhancing customer interactions.
- Discussion about the FCA’s capacity to handle extensive data due to its high regulatory ambitions, including potentially becoming a de facto credit reference agency.
- Advances in AI and technology, particularly in data handling, are promising for enhancing customer engagement and compliance but may face retrospective regulatory scrutiny.
- The regulatory environment could hinder access to credit for certain consumer segments, as lenders may retreat from subprime or near-prime lending.
- There is a push within the industry to use data insights more effectively to tailor approaches for diverse consumer financial situations.
- The evolving regulatory landscape is encouraging a transition from traditional collections practices to customer-centric financial difficulty management strategies.
New Ideas
- Increased use of open banking and real-time data analytics to provide lenders with a more precise understanding of consumer financial situations.
- Development of Consumer Duty dashboards to help firms evidence compliance, track consumer engagement, and monitor outcomes over time.
- A shift toward real-time affordability assessments, replacing static data points with current financial insights to improve credit and collections decisions.
- AI-driven segmentation and personalisation of collections strategies to better align with individual financial situations and regulatory requirements.
Key Statistics
- Over 1.6 million council tax arrears cases were passed to enforcement agents in 2022, slightly up from 1.5 million in 2019.
- Cost-of-living and council tax arrears are on the rise, with overall consumer vulnerability heightened by economic pressures.
- The FCA issued ~19 publications in 2023, amounting to over ~1,560 pages of new regulatory content, surpassing the length of War and Peace.
Session 2: Fraud’s Impact on Credit and Collections
- Fraud incidents have increased sharply, with identity theft and synthetic fraud becoming more sophisticated and pervasive.
- Synthetic identity fraud is growing, combining real data with fabricated elements to bypass traditional checks.
- Account takeover fraud has surged, with organised fraudsters targeting existing accounts with increasing precision.
- Fraud detection techniques, like “fraud as a service,” allow fraudsters to refine methods rapidly and share information.
- The balance between frictionless customer experience and necessary security checks is critical to reducing fraud without disrupting legitimate users.
- Customisable friction enables adaptive, risk-based fraud prevention measures for enhanced security.
- Proactive communication with customers on fraud protocols can help mitigate trust erosion in case of a fraud incident.
- Collaboration and data sharing among institutions are essential for tackling fraud across industries, with fraud intelligence shared in real-time.
- Economic stress has increased fraud risks, especially in first-party fraud, where individuals misuse credit due to financial pressures.
- Financial crime and vulnerability overlap, with socially engineered individuals often pressured into committing fraud.
- AI is both a tool for fraud prevention and an enabler for fraudsters, making continuous adaptation necessary.
- Regulatory frameworks need updates to manage emerging fraud types and the nuances of synthetic identity fraud.
New Ideas
- Customisable Friction: Tailoring security measures to individual customer risk levels, providing both security and minimal disruption.
- Real-Time Synthetic Identity Detection: New technologies identify synthetic identities as they form by analysing unusual data patterns and inconsistencies.
- AI-Driven Fraud Detection: Leveraging advanced AI models for real-time monitoring and rapid response to fraud indicators.
- Enhanced Device Recognition: Unique device identifiers track device behaviour patterns to detect potential fraud.
- Public-Private Data Collaboration: Proposals to improve cross-sector fraud intelligence sharing, especially between financial institutions and public bodies.
Key Statistics
- 15% rise in total fraud incidents in the first half of 2023, compared to the same period in 2022.
- 99% increase in account takeover fraud.
- 527% rise in synthetic identity fraud from 2020 to 2023.
- Synthetic identity fraud loss is estimated at £15,000 per incident on average in the UK.
- Synthetic identities bypassed fraud checks in 85% of cases due to insufficient detection tools.
- Collections show that up to 15% of all cases may be fraud-related, indicating a high proportion of uncollectible debts due to fraudulent accounts.
Session 3: Customer Engagement
- Shift from Traditional to Multi-Channel Engagement: Traditional phone-based approaches are giving way to multi-channel strategies, including SMS, WhatsApp, and self-service digital portals.
- Personalisation at Scale: Personalising engagement methods to customer preference is essential, though complex at scale, especially for organisations with legacy systems.
- Digital Transformation Requires Data Integration: Effective digital engagement involves integrating multiple communication points into a cohesive experience with a unified customer view.
- Early Interaction Insights: Early-stage customer interactions provide valuable data that can guide later engagement, improving personalisation and customer satisfaction.
- AI and Advanced Analytics: AI is increasingly used to support agents through “co-pilot” tools, as well as for sentiment analysis, enabling agents to deliver more empathetic responses.
- Cost-Efficient Engagement through Self-Service: Digital self-service portals allow customers to engage at their convenience, reducing operational costs while respecting customer preferences.
- Empathetic Collections Approach: Businesses are adopting an empathetic approach to collections, with an emphasis on helping customers resolve debts without aggressive tactics.
- Regulatory Compliance in Customer Engagement: Companies must balance customer preferences with regulatory requirements, ensuring transparency and documenting engagement outcomes.
- Optimised Customer Communication: Simplified, transparent communication styles resonate better with customers, building trust and improving engagement.
- Continued Importance of Human Interaction: Despite digital advancements, human agents remain critical, particularly for cases involving vulnerability disclosures and complex resolutions.
- Long-Term Trust Building: Initiatives such as “early nudges” or regular non-transactional engagement can build customer trust and loyalty over time.
- Outcome-Driven Engagement: Engagement efforts should aim for constructive financial outcomes, prioritising sustainable solutions over temporary fixes to minimise customer detriment.
New Ideas
- AI-Driven Agent Support: AI co-pilot tools that provide real-time, context-specific support to agents help ensure consistent and knowledgeable responses, even from less-experienced agents.
- Sentiment Analysis in Calls: Using AI to monitor and analyse customer sentiment enables agents to adjust tone and approach dynamically, improving customer satisfaction.
- Customer Personas for Engagement Strategy: Leveraging detailed customer personas, organisations can customise engagement channels and messages to meet varying needs effectively.
- Integration of Self-Service Portals with Traditional Channels: A seamless switch between digital and agent-assisted support allows customers to engage on their terms, reducing friction and improving overall satisfaction.
Session 4: The Role of Technology
- Digital-First Engagement Growth: The financial services industry is seeing a strong shift towards digital-only customer engagement, with some organisations reporting 90% digital interaction.
- Blending AI with Human Interaction: Combining automation with human support enhances customer outcomes, especially in complex situations that require nuanced decision-making.
- Data-Driven Personalisation: Effective use of data is essential for customising customer interactions, but legacy systems can limit data accessibility and impact personalisation.
- Emerging Digital Channels: Platforms like Rich Business Messaging (RBM) on iOS and Android may soon replace traditional SMS with richer, branded experiences by 2025.
- Agent Skills in a Digital Landscape: Shifting to digital channels demands new agent training as digital interactions differ from phone-based skills.
- Practical AI Applications: While promising, AI currently functions best in supportive roles, helping with data analysis and simple tasks rather than direct customer interactions.
- Explainable AI for Compliance: To meet regulatory standards, AI-driven decisions need transparency, particularly when used in financial services and debt collections.
- Future of Hyper-Personalisation: AI-driven hyper-personalisation could redefine customer interactions, allowing more tailored support and improved customer experience.
- Focus on Financial Inclusion: AI could potentially enhance financial inclusion by offering credit to underserved populations, aligning with regulatory goals.
- Omnichannel Communication Complexity: Managing multiple customer interaction channels requires strategies tailored to different customer preferences and regulatory compliance.
- Risk of AI-Driven Communications: Transparency in AI use is essential for maintaining customer trust, especially in sensitive areas such as debt collections.
- Growing Regulatory Scrutiny: Regulatory bodies are increasingly focusing on technological applications, necessitating robust compliance frameworks and data-driven decision documentation.
New Ideas
- Rich Business Messaging (RBM): A new digital communication platform allowing richer, branded SMS-like messaging set to be widely available by mid-2025.
- Conversational AI with Human Back-Up: Using conversational AI for initial customer interactions, with human agents stepping in for complex cases, balances efficiency with personalised service.
- Explainable AI for Compliance: AI models that can articulate their decision-making process help meet regulatory transparency standards.
- Personal Credit Matching Model: Arrow’s machine-learning-based tool matches customers with the credit products they’re most likely to receive, enhancing customer satisfaction and engagement.
Key Statistics
- 90% of Fin Tech customers engage digitally, with minimal use of phone calls.
- 47% of customer conversations in the UK collections industry show traits of vulnerability, highlighting the need for personalised, sensitive engagement.
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