Summary
The new age technologies, artificial intelligence (AI) and automation, are reforming the method in which utilities used to manage debts. Caring for the customer is kept on equal footing with maintaining a cash flow. Also, the new technology has enabled conveniences for both the sector and the customers, like early-warning risk detection, AI-powered chatbots to flexible repayment tools and Open Banking integration.
- Function of AI and Automation in Collections
- Advantages to Utility Providers
- Benefits to Customers
- Smart Customer Engagement:
- Challenges and Considerations
- Strategic Pillars of a Reformed Collections Framework
Introduction: A Turning Point for UK Utility Collections
According to First Source’s data in the article- Rethinking Debt Collection in the Utilities Sector, UK households owe £3.7 billion in unpaid energy bills and over £2 billion in water arrears[i]. This data regarding unpaid bills is clear evidence of the increasing pressure on the UK utilities sector. The energy costs are constantly rising, as is inflation and economic stress. In such a scenario, when households are struggling to manage expenses, the traditional collection model that is based on a stringent process and restricted personalization fails to cater to the purpose. The utility sector sails in a sea of challenges where it has to recover unpaid bills and also maintain customer experience, empathy and also complaint with regulations.
The Status Quo: Why the Old Collection Model is not efficient now
- Manual and obsolete- it depends on call centre agents, typed letters and a constant process.
- Expensive- Operational costs are high, low and inefficient recovery.
- Inflexible- One yard stick for all, customers’ financial situations and preferences are overlooked.
- Stressful and non-empathetic- lead to lawsuits, complains and consumer disbelief.
- Compliance issues- Inspected often by regulators like Ofgem and Ofwat for failing to treat customers justly.
The Growth of AI and Automation – A Smarter Way Frontward
AI and automation are transforming debt collection across the main junctures in the customer journey.
- PredictiveAnalytics : Perceiving who needs assistance- Beforehand
The AI models analyse data points such as payment history, economic indicators, usage patterns to identify factors such as:
- Detection of high-risk customers
- Predicting the likelihood of default
- Categorising customers based on behaviour and financial circumstances
- Suggests hands-on outreach strategies
According to TransUnion’s research report- More Than Half of Debt Collection Companies Saw Increased Volume of Accounts in Past 12 Months– in 2024, 18% of debt collectors invest in AI/ML. And also, substantial investments in technology are made by 52% of debt collection agencies to[ii] .
Smart Customer Engagement: Automating with Compassion
The AI powered tools replace the monotonous and tedious, manual contact approaches:
- Chatbots offer 24/7 assistance and are widely available on websites, apps, and messaging platforms.
- Voice assistants can manage inbound and outbound calls while using natural language processing (NLP) to comprehend and reply with human-like empathy.
- Automated email and SMS campaigns are personalized to individual customer requirements, tone, and financial situation.
As per Globenewswire’s article More Than Half of Debt Collection Companies Saw Increased Volume of Accounts in Past 12 Months– In 2024, debt collection companies using a self-service online portal for consumers reached 88%[iii].
Convenient Repayment Choices: Flexibility for Real Life
With the integration of open banking and automation, the utility sector is now proposing:
- Flexible payment dates.
- Pay-by-link functionality.
- Personalized instalment plans.
- Secure, variable recurring payments
This enables customers to handle debts without embarrassment or pressure, thereby reducing the conflict that often leads to missed payments.
Human + Machine – The Power of Hybrid Collections
Although AI surpasses at swiftness, scale, and constancy we can’t deny the comfort and empathy offered by human touch, particularly when it involves economically and emotionally vulnerable customers.
According to a Fast Company’s article Oh great, now debt collectors are embracing AI too, 11% of debt collection companies use AI in their tasks[iv].
This is the reason why the blend of automation with human touch in the Debt collection strategies is considered efficacious.
- AI segregates and marks the accounts
- AI handles general outreach and follow-up
- In intricate, vulnerable, and emotionally challenged cases, human agents intervene
This amalgamation of approaches successfully promotes trust, resolution rates, and customer satisfaction.
Challenges & Considerations
Undoubtedly, AI and automation offer significant benefits; however, their implementation is not risk-free.
Let’s see some of the general drawbacks
- Below-par data quality-occasionally leads to erroneous forecasts.
- Over automation– offers emotionless, unsatisfying experiences.
- Issues of integration– with legacy IT systems
- Prejudice in AI models– may unintentionally maltreat vulnerable groups.
- Governing complication- from Ofgem, FCA, and GDPR
Overcoming the challenges
- Initiate with fresh, structured data.
- Test AI with customer-facing staff feedback.
- Invest in platforms with human-dominated controls.
- Review AI choices frequently for impartiality.
- Collaborate with vendors who specialize in ethical AI.
As per Market.us data in the report AI for Debt Collection Market Soar to USD 15.9 Billion By 2034– The AI debt collection market is anticipated to grow at a CAGR of 16.9%, reaching $15.9 billion by 2034 from $3.34 in 2024[v].
The Future of Collections in the UK
With increased deployment of AI, the utility sector in the UK can expect:
- Hyper-personalized repayment plans: These plans will be based on the customer’s income, payment pattern, behaviour, and location.
- Integrated voice bots: These bots will assist in carrying on settlement negotiations in real time
- Open Banking: It is becoming a new normal, where payment options will be dynamic and adjust with the customer’s income.
- Machine learning: These models that can proactively identify vulnerabilities and offer instant assistance.
- AI-powered dashboards: for internal teams to measure outcomes, compliance, and productivity.
Strategic Pillars of a Reformed Collections Framework | ||||||||||||
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Conclusion: From Collection to Compassion
The reformation of UK utility collections is not just limited to technology updates. It’s more about gradual movement from call centres to conversational AI and from impersonal processes to thoughtful, empathetic engagement. Utility companies that embrace AI and automation are statistically more successful
Frequently Asked Questions
1. Why is there a need for reformation in the collection processes of the UK utility providers?
Traditional collection processes are reactive and do not consider factors like vulnerability or financial hardship.
With the rising cost of living and inflation, the utility sector needs a recovery method that is both empathetic and smart.
2. What is the role of automation in collections?
Automation frees up agents from monotonous tasks such as:
- Sending payment reminders
- Fixing a payment plan
- Classifying communication exchanges for compliance
This reduces operational costs and increases the speed of the collection cycle.
3. Can AI and automation affect customer experience?
Yes. AI and automation enable proactive, personalized communication.
Assistance is tailored to the customer’s financial situation, which builds trust and reduces disputes or complaints.
4. What are the compliance and regulatory considerations in collections that need to be adhered to?
There are guidelines and regulations like FCA, GDPR, and OFGEM rules that need to be adhered to by the AI-driven collections.
Sources :
Rethinking Debt Collection in the Utilities Sector
More Than Half of Debt Collection Companies Saw Increased Volume of Accounts in Past 12 Months
Oh great, now debt collectors are embracing AI too
AI for Debt Collection Market Soar to USD 15.9 Billion By 2034
