Sanlam Limited · JSE:SLM

Sanlam — Sanlam Benchmark Survey 2019

45 slides from Sanlam's conference presentation, 2019

  1. Slide 1: Make big data small

    Make big data small by Barend le Grange Head: Individual Member Support Sanlam Employee Benefits

  2. Slide 2: Making big data small

    C MAKING B G DATA sma

  3. Slide 3: Choice

  4. Slide 4: We are not the same

    WE ARE NOT THE SAME Very different: Paths Lives Priorities Expectations

  5. Slide 5: Size of word represents amount of times mentioned

    Size of word represents amount of times mentioned STOP WORKING GREY E LDERLY INVESTMENTS TAX FREE LIFESTYLE FREEDOM rnabiso ®t COMFORT. nowNSi7ING orth AMIEY oT RAVEL EXCITEMENT FE AR MEDICAL EXPENSES FINANCIAL SECURITY POVERTY DEBT FREE GET THERE FINANCIAL CONCERN *LPAGE ENOUGH MONEY seuoos secs wo

  6. Slide 6: Individual needs

    INDIVIDUAL NEEDS Most Important Important Least Important Lower Income Funeral Cover Short Term Debt Tax Free Savings Higher Income Retirement Funding Life Insurance & Medical Aid Funeral Cover

  7. Slide 7: Sanlam Financial Resilience Index

    SANLAM FINANCIAL RESILIENCE INDEX Diagnostic Tool Identify Financial Obstacles Move From Intuitive Generalisations to Empirical Specifics Measures a Funds’ Financial Resilience Against the Industry Across 6 Categories Findings from 5,000 respondents

  8. Slide 8: SFRI findings

    SFRI FINDINGS 65.3% SFRI 2017 63.1% SFRI 2018 61.1% SFRI 2019

  9. Slide 9: SFRI findings: financial resilience by category

    SFRI FINDINGS Average of: Financial Resilience Percentage 90% 80% Income and package composition 70% 60% Financial Wellness 50% Level of indebtedness 40% 30% Budgeting 20% Provision for retirement 10% 0% Advice and financial planning Financial Resilience Category

  10. Slide 10: SFRI findings: demographics analysis

    SFRI FINDINGS Demographics analysis of Financial Resilience: Older employees are 9% more financially resilient than younger employees. Males are 4% more financially resilient than females. Employees with an Honours degree or higher are 12% more financially resilient than those with matric or lower.

  11. Slide 11: Needs change

    NEEDS CHANGE. Retirement is not a product … It is a lifestyle Help them create the lifestyle they aspire to and instill financial resilience in members to take on life’s challenges

  12. Slide 12: Are we doing enough in considering the individual?

    ARE WE DOING ENOUGH IN CONSIDERING THE INDIVIDUAL?

  13. Slide 13: Actual lived experience

    ACTUAL LIVED EXPERIENCE Disappointment Advice Providers Themselves

  14. Slide 14: Actual lived experience

    ACTUAL LIVED EXPERIENCE Shock Tax Net outcomes

  15. Slide 15: Actual lived experience

    ACTUAL LIVED EXPERIENCE Regret Vehicles Behaviour

  16. Slide 16: Key challenges

    KEY CHALLENGES Insufficient Information Lack of accessibility Options Progress Values

  17. Slide 17: Key challenges

    KEY CHALLENGES Insufficient Information Lack of accessibility Options Progress Values

  18. Slide 18: Key challenges

    KEY CHALLENGES Insufficient Information Jargon Lack of accessibility Options Progress Values

  19. Slide 19: Key challenges

    KEY CHALLENGES Insufficient Information Jargon Lack of accessibility Feel isolated Options Progress Values

  20. Slide 20: Member engagement

    MEMBER ENGAGEMENT

  21. Slide 21: Engagement with members

    ENGAGEMENT WITH MEMBERS Who What How When … and then it changes

  22. Slide 22: Analytics enable engagement

    ANALYTICS ENABLE ENGAGEMENT Administrative Capability Analytical Horsepower Ability to Apply

  23. Slide 23: What people want?

    WHAT PEOPLE WANT? On-line capability for values & transactions Human interaction for information and guidance Access to trusted financial advice Written information ineffective to engage and influence

  24. Slide 24: Digital experience

    DIGITAL EXPERIENCE Pages Articles Description Unique Hits Description Unique Hits My Benefits 250,000 7 Golden Rules 31 My Investments 52,000 The Impact of Costs 7 My Beneficiaries 41,000 Good Investment Choices 5 Retirement Calculator 24,000 Starting Early 3 Life Events 15,000 Setting a Goal 33

  25. Slide 25: Retirement benefits counselling

    RETIREMENT BENEFITS COUNSELLING Standalone Written 51% HR 20% Administrator 47% EB Consultant 25% 2019 Sanlam Benchmark Consultant Survey IFA 22% 88% believe that RBC will assist in improving retirement outcomes

  26. Slide 26: Hesitance to use humans?

    HESITANCE TO USE HUMANS? 69% wary of cost

  27. Slide 27: Hesitance to use humans?

    HESITANCE TO USE HUMANS? 69% wary of cost 13% believe that setting up own infrastructure is too cumbersome

  28. Slide 28: Hesitance to use humans?

    HESITANCE TO USE HUMANS? 69% wary of cost 13% believe that setting up own infrastructure is too cumbersome 31% still unaware of what Retirement Benefits Counselling entails

  29. Slide 29: Hesitance to use humans?

    HESITANCE TO USE HUMANS? 69% wary of cost 13% believe that setting up own infrastructure is too cumbersome 31% still unaware of what Retirement Benefits Counselling entails 4% ran out of time to properly consider Counselling

  30. Slide 30: Maintain standard of living

    MAINTAIN STANDARD OF LIVING 0 - 30% 31 - 60% 61 – 100% Don’t know Standalone 68% 22% 4% 6% Umbrella 75% 10% 9% 6%

  31. Slide 31: It's not too late… Impactful Retirement Benefits Counselling

    It’s not too late… Impactful Retirement Benefits Counselling

  32. Slide 32: How do you ensure fair treatment?

    Retirement Benefits Counselling Becoming New Product Push? HOW DO YOU ENSURE FAIR TREATMENT? If an annuity strategy contains annuity products from various providers One single provider… cannot provide Retirement Benefits Counselling at withdrawal and retirement Retirement Benefits Counselling should

  33. Slide 33: How do you ensure fair treatment?

    HOW DO YOU ENSURE FAIR TREATMENT? Retirement Benefits Counselling Becoming New Product Push? Measuring Experience at Withdrawal & Retirement Incentivisation Model Disclosure Ability to Audit

  34. Slide 34: What gets measured … gets done

    WHAT GETS MEASURED … GETS DONE. Measuring what was put into counselling Measuring actual member outcomes Feedback from members

  35. Slide 35: Basic counselling – inbound calls

    BASIC COUNSELLING – INBOUND CALLS Advice General Retirement Withdrawal Retrenchment requests queries Nov 15% 44% 9% 2% 30% 2018 Dec 22% 53% 3% 3% 19% Jan 0% 82% 0% 0% 18% Feb 10% 74% 2% 2% 12% 2019 Mar 3% 81% 1% 1% 13% Average amount of calls per month of 120 Apr 5% 89% 0% 0% 5%

  36. Slide 36: Pro counselling – outbound calls

    PRO COUNSELLING – OUTBOUND CALLS May 2018 – April 2019 Withdrawal Retirement Member contacted and counselled 45% 54% No contact details available 22% 15% Member unable to contact after 3 attempts 33% 35% >4,500 withdrawals and >600 retirements

  37. Slide 37: Measuring member outcomes – retirement

    MEASURING MEMBER OUTCOMES - RETIREMENT Impact of Retirement Benefits Counselling at Retirement 90% 80% Percentage of Members 70% 78% 60% 50% 55% Counselled 40% 39% Not Counselled 30% 20% 18% 10% 5% 3% 1% 1% 0% In-Fund Phased Retiree Out-of-Fund Cash Choice at Exit

  38. Slide 38: Measuring member outcomes – withdrawal

    MEASURING MEMBER OUTCOMES - WITHDRAWAL Impact of Retirement Benefits Counselling at Withdrawal 100% 90% 90% 80% Percentage of Members 70% 72% 60% Counselled 50% 40% Not Counselled 30% 26% 20% 10% 10% 2% 0% 0% In-Fund Preservation Preservation/RA/Other Fund Cash Choice at Exit

  39. Slide 39: Feedback from members

    FEEDBACK FROM MEMBERS "Thanks so much for your "Thank you so much for your assistance. "I wanted to save my funds time and effort in helping me! I I contacted the call centre but they were not as but had no idea what to do, so appreciate people like you helpful as you. so I am really happy that you

  40. Slide 40: Big data

    Artificial Intelligence Machine Learning Analytics Insights… Big data

  41. Slide 41: Opportunity to go even smaller

    OPPORTUNITY TO GO EVEN SMALLER Machine learning Artificial Intelligence Propensity Models All depend on Data… … Predictive Proactive Retirement Benefits Counselling

  42. Slide 42: Predictive proactive retirement benefits counselling

    PREDICTIVE PROACTIVE RETIREMENT BENEFITS COUNSELLING Use Machine Learning model to predict who to call If there was 100 members in a fund, we called everyone, but counselled only 50 members 50 Now we can reduce fees by only calling 48 members, but still reach 40 of the 50 members 40 Basically, reduc

  43. Slide 43: Benefits

    BENEFITS Individualize the member experience If How When Increase effectiveness of Retirement Benefits Counselling Enable Financial Resilience

  44. Slide 44: Making big data small

    MAKING BIG DATA SMALL Systems Data and analytical skills Ability to implement …to make the most of interventions

  45. Slide 45: Trust

    TRUST

Sanlam — Sanlam Benchmark Survey 2019 on 6ix